1. business and industrial

Author: Anne Nielsen
Academic Supervisor: Palle Nierhoff
Number of characters with space: 127.984
MSc Finance and International Business
BAVARIAN NORDIC A/S
EXPANDED NET PRESENT VALUE AND SHARE PRICE
Department of Economics and Business Administration, School of Business and
Social Sciences, Aarhus University
February 2013
I
Executive Summary
In this paper, the share price for Bavarian Nodic A/S is calcualted based on the
expanded net present values (eNPV) of the company’s vaccine candidates
PROSTVAC© and MVN-BN© RSV. The focus is on the calculation of real
options since this is considered difficult by managers. In this paper, a six-step
approach for the calculation of eNPV is developed. The six-step approach
involves the calculation on the traditional NPV in step 1-3 and the calculation of
real options in step 4-6. The calculation of real options is based on the project
volatility from management estimates and simulation, the risk-neutral probability
and binomial trees.
The calculated eNPV of PROSTVAC© was different from the eNPV of MVA-BN©
RSV. PROSTVAC© had an eNPV 956 DKK million and no RO value whereas
MVA-BN© RSV had a lower eNPV of 35,25 DKK million. RSV had a static NPV
of -4,81 DKK million and a real option value of 40,06 DKK million. This may
illustrate that projects with higher uncertainty have higher RO values. In the
binomial trees, which shows management actions, PROSTVACs© abandonment
options should never be exercised whereas it could be beneficial to exercise
MVA-BN© RSVs options in some circumstances before phase 3 development.
From the eNPV of PROSTVAC© the share price for Bavarian Nordic A/S is
calcultated. Jyske Bank estimates that PROSTVAC© constitutes 45% of their
target share price of 80 DKK/share. Therefore, from the eNPV calculation, the
value of PROSTVAC is 36,64 DKK per share. If PROSTVAC is worth 45% then
Bavarian Nordic A/S share price is 81,41 DKK/share the 31st of December
2012.
Investment companies rarely price projects in early development which is why
Jyske Bank does not set a value on MVA-BN© RSV. From the eNPV calculation
it is clear that RSV does have a significant value and this value should be
included in the share price. The value of 35,25 DKK/million adds an extra 1,35
DKK/share to the above share price. Bavarian Nordic A/S shares were traded at
49,80 DKK/share on the 31st of December 2012 and therefore it can be
recommended to buy Bavarian Nordic A/S shares if investors preferences
towards risk is disregarded.
II
Contents
1. Introduction ............................................................................................................................. 1
1.1 Problem Statement .......................................................................................................... 2
1. 2 Delimitation ...................................................................................................................... 3
1. 3 Methodology .................................................................................................................... 5
1. 4 Structure ........................................................................................................................... 6
2. Bavarian Nordic A/S .............................................................................................................. 6
2. 1 Pipeline ............................................................................................................................. 6
3. The Biotechnology Industry .................................................................................................. 8
3. 1 Clinical Stages................................................................................................................. 8
3. 2 Patents ........................................................................................................................... 11
3. 3 Royalties......................................................................................................................... 11
3. 4 Milestones ...................................................................................................................... 12
3. 5 Sales Curve ................................................................................................................... 13
4. Real Option Theory .............................................................................................................. 13
4.1 Use of Real Options ...................................................................................................... 14
4. 2 Real Options VS. Financial Options .......................................................................... 15
4. 3 Types of Real Options: ................................................................................................ 16
4. 4 Real Option Criticism.................................................................................................... 18
5. Step-Wise Approach to Valuing Real Options ................................................................. 19
5. 1 Step 1: Identify and Calculate Base Variables ......................................................... 20
5. 2 Step 2: Strategic Analysis............................................................................................ 22
5. 3 Step 3: Forecasting and Net Present Value ............................................................. 23
5. 4 Step 4: Project Volatility ............................................................................................... 23
5. 4. 1 Management Estimates:...................................................................................... 24
5. 4. 2 Simulation .............................................................................................................. 25
5. 5 Step 5: Real Option Valuation .................................................................................... 26
5. 5. 1 Binomial Tree 1 – Value of Underlying Asset .................................................. 26
5. 5. 2 Binomial Tree 2 – Value of Real Option ........................................................... 27
III
5. 5. 3 Binomial Tree 3 – Management Options .......................................................... 29
5. 5. 4 Calculate Expanded Net Present Value ........................................................... 29
5. 6 Sensitivity Analysis ....................................................................................................... 29
6 Real Option Valuation........................................................................................................... 30
7. Valuation of PROSTVAC© .................................................................................................. 30
7. 1 Step 1: Calculate Base Variables ............................................................................... 31
7. 2 Step 2: Strategic Analysis............................................................................................ 32
7. 2. 1 External Analysis (PROSTVAC) ........................................................................ 32
7. 2. 2 Internal Analysis (Bavarian Nordic) ................................................................... 35
7. 2. 3 SWOT Analysis ..................................................................................................... 38
7. 3 Step 3: Forecast ............................................................................................................ 39
7. 4 Step 4: Project Volatility ............................................................................................... 40
7. 5 Step 5: Real Option Valuation .................................................................................... 42
7. 6 Step 6: Sensitivity Analysis ......................................................................................... 46
8. Valuation of MVA-BN© RSV ............................................................................................... 46
8. 1 Step 1 and 2: Base Variables & Strategic Analysis ................................................. 47
8. 2 Step 3: Forecast ............................................................................................................ 49
8. 3 Step 4: Project Volatility ............................................................................................... 50
8. 4 Step 5: Real Option Valuation .................................................................................... 52
8. 5 Step 6: Sensitivity Analysis ......................................................................................... 56
9. Share Price ........................................................................................................................... 58
10. Conclusion .......................................................................................................................... 59
Bibliography
Appendix
IV
Table of Figures:
Figure 1: Bavarian Nordic Pipeline 2012 ............................................................ 7
Figure 2: Overview of Clinical Phases .............................................................. 10
Figure 3: Sales Curve ....................................................................................... 13
Figure 4: Six-step Approach to Valuing the Expanded Net Present Value ....... 19
Figure 5: SWOT Analysis ................................................................................. 39
Figure 6: Step 4 - Simulation on Project Volatility for PROSTVAC ................... 42
Figure 7: Step 5 - Binomial Tree 1 - Underlying Value of PROSTVAC............. 43
Figure 8: Step 5 - Binomial Tree 2 - Abandonment Value of PROSTVAC ....... 44
Figure 9: Step 5 - Binomial Tree 3 - Management Actions for PROSTVAC ..... 45
Figure 10: Step 4 - Project Volatility for RSV .................................................... 51
Figure 11: Step 5 - Binomial Tree 1 - Underlying Value of RSV ....................... 53
Figure 12: Step 5 - Binomial Tree 2 - Value of Sequential Abandonment Option
for RSV ............................................................................................................. 54
Figure 13: Step 5 - Binomial Tree 3 - Management Actions for RSV ............... 55
Figure 14: Tornado Diagram over Input Variables for RO Calculation ............. 57
Figure 15: Step 6 - Sensitivity Analysis: Strike Price and Project Volatility ....... 58
V
1. Introduction
Bavarian Nordic A/S is a Danish biotech company that develop various vaccine
treatments. Before a vaccine can be sold in the market, it must to go through
different phases of development. These phases are very costly and have low
success rates. Therefore, it is very important that managers make the right
investment decisions before they decide whether to invest in a vaccine project
or not. In the past, the net present value approach has be used as a tool to
valuate such projects, but the net present value approach neglects the fact that
managers can change the course of a project after the initial investment
decision has been made. The net present value approach is a static approach
which only should be applied in projects where there is no uncertainty. If there is
uncertainty in a project it has been suggested to apply the expanded net
present value approach. This approach acknowledge that managers may make
decisions, which impact the project, after the initial investment decision. For
instance, a manager may discontinue the development of a vaccine and sell the
intellectual property rights because the phase results were bad. This
management flexibility adds value to projects through real options. The extra
value may change the investment decisions compared to the traditional net
present value approach. Some managers, however, do not apply the expanded
net present value approach because they argue it is too complicated to apply
real options as a valuation tool. Therefore, it is necessary to develop an easy
model for the calculation of the expanded net present value or more specific the
value of real options. If managers apply the expanded net present value
approach a company’s projects may increase in value and thereby maximize
shareholder value.
Bavarian Nordic A/S is developing a number of new vaccines and it is
interesting to see if the calculation of the expanded net present value add value
to these vaccine projects. Projects in Bavarian Nordic A/S go through many
different phases of development and management flexibility is vital in such a
small biotech company. Bavarian Nordic A/S is currently in phase 3
development of a vaccine against advanced prostate cancer (PROSTVAC ©)
and has just started the development of a vaccine against respiratory syncytial
1
virus (MVA-BN RSV©). These vaccines are in different phases of development
and the added value from flexibility may be very different between them.
1.1 Problem Statement
Based on the calculation of the expanded net present value for Bavarian
Nordic’s vaccine candidates PROSTVAC© and MVA-BN© RSV; what is
Bavarian Nordic’s estimated share price the 31st of December 2012?
The objective of this paper is to calculate Bavarian Nordic’s share price based
on the eNPV. The calculation will reveal if the extra value from real options will
increase Bavarian Nordic’s share price. In order to reach that objective a
number of research questions will be answered.
The first part of the research questions are concerned with an analysis of real
options. In the second part of the research questions, questions related to the
calculation of the expanded net present value are identified. The research
questions in the third part are concerned with an analysis of Bavarian Nordic
and the chosen vaccine candidates. The last part of the research questions
focus on the sensitivity of variables and recommendations based on the
calculations and final eNPV.
Research questions related to the analysis of real options:

What are real options?

Should real options always be applied in a valuation?

Do companies use real options as a valuation tool?

Is the expanded net present value approach a better valuation tool than
the traditional net present value approach?
Research questions related to the calculation of the expanded net present
value:

How can managers use real option valuation as a decision making tool?

How can the expanded net present value easily be calculated?
2

Is it possible to develop a model for the calculation of eNPV and can it be
applied to case specific projects?
Research questions related to Bavarian Nordic A/S and the two vaccine
candidates:

What are the strengths and weaknesses of Bavarian Nordic A/S?

What are the opportunities and threats for PROSTVAC© and MVA-BN©
RSV?

Which industry specific factors are relevant for the calculation of eNPV
for PROSTVAC© and MVA-BN© RSV?
Research question related to the final expanded net present values and
recommendations:

Which project specific decisions should management make based on the
real option valuation of PROSTVAC© and MVA-BN© RSV?

Are there any difference in the real option value from projects in different
phases of development?

What will happen to the real option value if a variable changes?

Can it be recommended to buy Bavarian Nordic’s shares?
1. 2 Delimitation
In this paper, the focus will be on real options and how to calculate these.
Therefore, it is assumed the reader has knowledge of the traditional valuation
tools such as how to calculate the traditional NPV and the discounted cash
flows.
The valuation will be conducted on one of Bavarian Nordic A/S most important
vaccine candidates PROSTVAC© and a lesser known vaccine candidate MVABN© RSV. These two vaccine candidates will in this paper be referred to as
PROSTVAC and RSV. Bavarian Nordic A/S will be referred to as BAVA or
Bavarian Nordic and the expanded net present value will be referred to as
3
eNPV. The two vaccine candidates are chosen in an expectation that they will
reveal different result. No other vaccine candidates will be evaluated in this
paper. There has been no contact with Bavarian Nordic A/S wherefore
management estimates are based on the objective beliefs of the writer.
It is assumed, the value of PROSTVAC constitutes 45% of Jyske Banks target
value of 80 DKK. This estimate is given by senior share analyst, Frank
Andersen, from Jyske Bank. RSV is given no value by Jyske Bank.
The role of investor preferences towards risk is not a part of the analysis.
Therefore, a recommendation on whether to but BAVAs shares will solely be
based on the share price calculated from the eNPV.
The calculations will be in DKK since this is the currency used in BAVAs
financial reports. Most of the industry specific variables are estimated in USD
and these will be converted into DKK using the exchange rate USD 5,62/DKK
from the 31/12-2012.
No data or articles published after the 13th of November 2012 will be used in
this paper; except for important date specific inputs such as the exchange rate
and the risk free rate which are from the 31st of December 2012. Further, the
mail correspondence with Frank Andersen took place in December 2012.
The data, in this paper, stems largely from secondary material such as Bavarian
Nordic’s financial statements, articles found via the search engine Business
Source Complete and data extracted from DataStream. It has been important to
read the financial statements and articles with a critical view since these may be
biased. Data from DataStream is considered unbiased. Further, articles on
industry structure, vaccines specific information and clinical phases come from
competitor and government web-pages, these may also be biased. The
important books in this paper are Mun 2006 and Copeland & Antikarov 2003,
these books area quite old but they are still considered to be some of the best
for real option valuation.
4
1. 3 Methodology
There are many variables which have to be estimated for the calculation of the
eNPV. Many of these variables are impossible to identify without having contact
to the respective company. Therefore, it is possible to use estimates based on
historic studies. Since projects are unique these historic estimates should, if
possible, not be used. Given that there are no certain estimates from BAVA
these base variables will be used, even if this make the project less unique. The
historic estimates are based on numbers from the biotechnology and
pharmaceutical industries.
It is argued that it is necessary to conduct a strategic analysis in order to identify
company specific strategies for the forecast. In this paper, an internal analysis
based on Porter’s Value Chain framework (on company level), and an external
analysis on factors of market attractiveness will be conducted. The internal and
external analysis will be combined in a SWOT matrix. There are many other
ways a strategic analysis can be conducted, for instance with a PEST or
resource based analysis. It is up to the managers to evaluate which model is
the best.
The focus is on how to calculate the expanded net present value (eNPV), the
calculation of traditional NPV is not that important, but the calculation of the
option premium is quite important since this has proved to be difficult for
managers. There are different approaches to the calculation of option values. In
this paper, the risk neutral probabilities together with binomial trees are applied.
One important assumption that is used in the real option calculation is the
market asset disclaimer assumption (MAD), this assumption states that the
value of the underlying asset without flexibility (static NPV) is the best unbiased
estimate of the market value of the project. It is impossible to find identical
projects for valuation and therefore this assumption is necessary.
The project volatility is estimated in a Monte Carlo simulation where the input
assumptions are based on management estimates. Instead of using
management subjective estimates, one could use historic data if they existed.
5
1. 4 Structure
This paper begins with an introduction to Bavarian Nordic and the biotechnology
industry in which BAVA operates. From general assumptions about the biotech
industry, variables for future calculations are identified
The paper continues with a brief discussion of real options in paragraph 4; what
are real options? Are they applied by companies? And what do critics say about
real options. In paragraph 5, a six-step approach to valuing real options through
the eNPV is introduced. This approach will be applied in the valuation of the
expanded net present value of PROSTVAC and RSV in the latter parts.
Paragraph 6 is a short introduction the next two paragraphs where the actual
eNPVs of PROSTVAC and RSV will be calculated with the help of the six-step
approach.
In paragraph 9, Bavarian Nordic’s share price is estimated and it can be seen
how much value each of the vaccine candidates contribute to BAVAS share
price. Paragraph 10 concludes.
2. Bavarian Nordic A/S
Bavarian Nordic A/S was founded in 1994 by Asger Aamund, who is the current
chairman on the board of directors. Bavarian Nordic A/S also known as BAVA is
a vaccine-focused biotechnology company which develops and produces
vaccines for the treatment and preventions of life-threatening diseases such as
smallpox, prostate cancer and respiratory syncytial virus. BAVA is listed on
NASDAQ QMX Copenhagen and has more than 450 employees. The
company’s primary operations are in Denmark, United States, Singapore and
Germany (Bavarian Nordic, 2012a).
2. 1 Pipeline
BAVA has a very promising pipeline with two vaccines in phase 3 development;
IMVAMUNE© and PROSTVAC. BAVA has no vaccines approved for the market
yet, nevertheless, IMVAMUNE© can be sold because it is considered an
6
emergency vaccine. BAVAs total costs for R&D and production are quite high
and that compared with the low revenue has resulted in negative net profits for
the last five years.
Currently, BAVA is producing and selling IMVAMUNE© a (vaccine against
smallpox) to the US Strategic National Stockpile even though the U.S. Food and
Drug Administration (FDA) has not approved it for commercialization, but since
it is considered an emergency vaccine it may be sold before approval. BAVA
has a contract to deliver 14 million doses of IMVAMUNE© in 2012-2013, these
deliveries increased the production significantly for 2010 and 2011 (Bavarian
Nordic, 2011a).
Another important candidate for FDA approval is PROSTVAC, PROSTVAC is a
vaccine candidate against advanced prostate cancer. PROSTVAC reached
phase 3 in November 2011. Both PROSTVAC© and IMVAMUNE© are in late
phase development and therefore BAVAs R&D costs are quite high. If the two
products are approved for commercialization then there are great sales
prospects.
BAVAs pipeline is divided in two divisions; the cancer division which has six
projects in the pipeline and the infectious diseases division which have four
products in the pipeline.
Figure 1: Bavarian Nordic Pipeline 2012
Source: Bavarian Nordic Report Q2 2012
7
Since BAVA has begun production of IMVAMUNE© (emergency use) and
PROSTVAC© has reached phase 3 development, it can be argued that BAVA is
turning into a pharmaceutical company. Biotech companies are often
characterized as companies with high R&D expenses, operate with a loss for a
period, receive milestone payments from partners and do not have the
resources to commercialize a product. Pharmaceutical companies, on the
contrary, have lower R&D expenses (but still large), they already manufacture
and sell drugs, therefore their sales and marketing expenses are high (Ferrara,
2011). Even though Bavarian Nordic may be in the process of turning into a
pharmaceutical company, it may still take many years to receive FDA approvals
and develop marketing and sales departments. Therefore, in this paper,
Bavarian Nordic will be treated like a biotechnology company.
3. The Biotechnology Industry
As mentioned above, BAVA is a biotechnology company. Biotech companies
within the development of new drugs have to go through different phases of
development in order to launch the drugs on the market. The road to market
approval is time consuming, cost extensive and approval success rates are low.
The different phases of development will be introduced below.
3. 1 Clinical Stages
The major market for Bavarian Nordic is in the USA, therefore, the relevant
approval process goes through the U.S. Food and Drug Administration (FDA).
Europe has a corresponding approval structure which is through the European
Medicine Controls Agency (EMEA). Generally, if a company receives FDA
approval in the USA then it will also get it in Europe. It is the FDAs responsibility
to protect the public safety (not approving bad drugs), but also not to delay
innovative drugs unnecessarily.
8
There are several phases the company must go through in order to get FDA
approval, namely preclinical tests on animals and clinical tests on humans.
Therefore, the company must be very patient and have enough capital to go
through the phases. The following paragraph is based on the study conducted
by DiMasi and Grabowski 2007 (cost estimates) and the e-book by Bogdan and
Villiger 2008 (time estimates and success rates).
Preclinical trials: the compound (drug) is tested in animals to see if it can be
applied to a living organism and whether it causes toxicity. On average,
preclinical trials takes 10-12 months to complete and the average cost for the
preclinical trials, are 59,88 USD million.
Clinical trials – phase 1: a small group of human volunteers (20-80) are tested
to evaluate safety, dose range and side effects. Before the testing of humans
can begin, the FDA requires an ‘Investigational new drug application’ (IND) to
be filed, if the application is approved, then human testing can begin. The cost
in phase 1 is low compared to the cost in other phases because testing only
involves a limited number of volunteers. The average cost for this phase is
32,28 USD million. The probability of entering into phase 1 is according to
DiMasi 100% (in reality, not all drugs enter phase 1, many are discontinued in
preclinical stages, but these drugs are not included in DiMasi’s study) and the
probability of phase 1 success is 83,7%.
Clinical trials – phase 2: here a group of about 100-300 people with the
disease is tested. Phase 2 can be divided into; 2a: where the aim is to define
the dose and 2b: where the aim is to prove the effectiveness of the drug. The
average estimated costs are 37,69 USD million and the success rate for phase
2 projects is only 56,3%.
Clinical trials – phase 3: the drug is tested on 500-20.000 patients in order to
confirm the effectiveness of the treatment. The costs are much larger than in
the other phases because of the large number of patients. The costs are
estimated to be 96,09 USD million and the probability of success is a little
higher than the phase 2 success rate, the success rate for phase 3 projects are
64,2%.
9
Approval phase: if the clinical phases are successful then the company will file
for a Biologic License Application (BLA). FDA evaluates the data and then
rejects or approves the drug. It takes on average a little more than one year to
review the data and the costs are 3 USD million. The approval success rate is
not evaluated by DiMasi & Grabowski 2007, therefore it is necessary to turn to
one of DiMasi’s older studies where the approval success rates for different
therapeutic classes were analyzed. The approval rate for immunology (same
therapeutic class as PROSTVAC) was 81,6% whereas the approval success
rate for respiratory (same therapeutic class as RSV) was lower with 76,9%.
Since the data is quite old it may not reflect the approval success rates today
(Bodgan & Villinger, 2008, p.16).
An overview of the phases, costs, success rates and time estimates can be
seen below. The estimates will be used as variables in the valuation, if no other,
more certain, estimates can be found.
Figure 2: Overview of Clinical Phases
FDA
Costs ($
million)
Time
(months)
Probability
of Success
(%)
Preclinical
59,9
10 - 12
100
Phase 1
32,3
18 - 22
83,7
Phase 2
37,7
24 - 28
56,3
Phase 3
96,1
28 - 32
64,2
BLA Approval
3
16 - 20
81,6/76,9
Source: own construction. Based on DiMasi & Grawbowski 2007 and Bogdan & Villinger 2008
10
3. 2 Patents
The most important assets in biotechnology companies are their intellectual
property (IP). It is very important to protect the IPs since these will form the
basis for future revenue. Therefore, companies should patent protect their
assets. A patent gives the holder the exclusive rights for a period of 20 years.
After the 20 years it is possible to apply for a patent extension, the patent
extension is usually for an extra five years with the exception that the product
may only be patented and on the market for a maximum of 14 years (FDA,
2009). Usually, companies apply for patents when the product under
development is in the preclinical phase. When the product has come through
the clinical phases, the remaining patent period is often no more than ten years.
3. 3 Royalties
Biotechnology companies often lack the knowledge, expertise and capacity to
introduce their products to the market. Therefore, these companies are often
interested in forming an alliance with a partner who can be in charge of the
commercialization. The partner will pay the biotech company a royalty rate for
the rights of the asset. A royalty is a user-based payment and allows the
licensee the right of the asset. There are many different ways in which the
partner agreement can be set up and biotech companies use the partner
agreement as an important strategic tool; maybe access to different markets are
important or maybe it is important to keep production in-house.
There are many factors which can affect the royalty rates and these depend
largely upon; stage of development, strength and scope of intellectual property
rights, exclusivity of rights etc. (Finch, 2001). Evidence from surveys has shown
that royalties paid by larger pharmaceutical companies can be very different
and royalties in the range of 5% to 70% has previously been paid. Further,
evidence has shown that companies typically pay a royalty rate based on sales.
It can be argued that a royalty rate based on sales is not appropriate because
the costs related to the product is rarely known in advance. Therefore, a royalty
rate based on a profit measure may be better. Nevertheless, in this paper, the
11
royalty rate is based on sales since this is the most common way to set royalty
rates.
Royalty rates often depend on the stage of development at the time of
agreement. Early stage royalties are often low, which reflects the risk
associated with the asset. If the royalty agreement is made in late stage
development, the royalty rate will often be larger, which illustrates the
decreased risk. Most royalty rates often lie in the range of 5% to 15%. Royalties
rates given for products in phase 3 development lies in the range of 10% to
20% (Finch, 2001). The royalty rate in the paper will therefore be 15% and
based on sales.
3. 4 Milestones
Milestones are one-time payments paid by the licensee to the licensor and are
triggered when the project reaches a certain milestone. A milestone may be
paid for the completion of phases, filing of patents and receiving positive results.
In that context, milestone payments reflect the diminishing risk associated with
the project. The amount and frequency of milestone payments are very different
between projects and phases. In this paper, I will not include milestones in the
forecast because of the high insecurity related to the amount and frequency of
payments. This will make the forecasts a bit conservative because it is expected
that BAVA will receive milestone payments when they find a partner (from the
financial statements it is clear that BAVA expects to receive milestone
payments from a partnering agreement for PROSTVAC and these payments
should be used to finance other projects (Prospectus, 2011, p. 25)). In
connection with that, milestone payments may also go the other way; BAVA can
make an agreement to pay milestones to a partner, for instance, when the
product has been safely commercialized or when the sales reaches a certain
point. By not including milestones, I follow the approach applied by Jefferies, a
global investment bank, which also disregards milestone payments for
PROSTVAC (Jefferies, 2012).
12
3. 5 Sales Curve
In order to undertake a forecast for the NPV calculation, it is important to
include a sales curve or penetration rate for the new product. Sales curves can
be very hard to estimate for new products because the market size and sales
are uncertain. The calculation of sales curves is not a part of this thesis
wherefore I use the sales curve suggested by Bogdan & Villiger 2010. The
sales curve can been seen below. The sales curve illustrates that new products
will start with little sales and thereafter increase until it reaches 100% just before
patent expiry. After patent expiry the sales will flatten out over approximately
nine years (Bogdan & Villiger, 2010, p. 109-111).
Figure 3: Sales Curve
Year Market share Year Market share
1
5% 12
100%
2
19% 13
99%
3
36% 14
97%
4
51% 15
95%
5
64% 16
72%
6
75% 17
53%
7
84% 18
37%
8
91% 19
24%
9
96% 20
13%
10
99% 21
6%
11
100% 22
1%
Source: Own Construction. Based on Bogdan & Villiger 2010.
4. Real Option Theory
Traditionally, the net present value (NPV) approach has been used to decide on
investment decisions; if the NPV was positive managers should undertake the
investment, it the NPV was negative, the investment should not be decided
upon. However, the traditional NPV approach has limitations.
The traditional NPV approach assumes that future cash flows are certain and
the course of the project cannot change after the investment decision. This
means that managers have a passive role. If there is uncertainty in a project,
the traditional NPV will not reveal the correct value of the project. Uncertainty
13
adds value to a project because active managers can change the course of a
project, for instance, managers may choose to abandon a project and thereby
save future costs. The extra value come from a company’s real options, these
options can be very different both in types and in value. In order to incorporate
the value of real options in the investment decision, the expanded net present
value approach can be applied. The equation for the expanded net present
(eNPV) value can be seen below (Trigeorgis, 2005).
𝐸𝑥𝑝𝑎𝑛𝑑𝑒𝑑 𝑁𝑃𝑉 = 𝑆𝑡𝑎𝑡𝑖𝑐 𝑁𝑃𝑉 + 𝑂𝑝𝑡𝑖𝑜𝑛 𝑝𝑟𝑒𝑚𝑖𝑢𝑚
Equation 1
From the above equation it can be seen that the traditional NPV approach is
also applied in the eNPV but an element is added – the option premium which
can be identified as the value of flexibility or real option value. The value of
flexibility comes from the fact that managers can change the course of a project
after the investment decision, based on NPV, has been made.
The focus of this paper will be to calculate the option premium, this can be done
with a real option valuation. An introduction to real options is presented in the
below paragraphs, here types, definitions, calculations and critique of real
options will shortly be discussed.
4.1 Use of Real Options
It is generally accepted that real options can be a valuable tool for a company’s
strategy and investment decisions, but many companies have been slow to
implement the use of real options. In the mid-1990s Triantis argued that the use
of RO valuation was ready to increase significantly, this however has not been
the case (Copeland, 2003). In a survey, conducted by Block in 2007, it was
found that only 14,3% of the responding managers used real options. The study
was conducted on 279 Fortune 1000 companies. The study revealed large
differences in the use of real options between industries. Companies engaged
in new product introduction (often biotech and pharmaceutical companies) are
14
the most frequent users of real options, 36,2% of these companies applied real
options. At the other end of the spectra were companies engaged in foreign
investments, here only 9,6% of managers applied real options (Block, 2007).
According to the survey there are different reasons why companies do not use
real options
The primary reasons for not applying real options were: lack of management
support (42,7%), DCF is the proven method (25,6%), requires too much
sophistication (19,5%), real options encourage risk taking (12,2%). However,
43,5% of the respondents stated that there was a good chance they would use
real options in the future. In conclusion, there is still a majority of companies
which apply the traditional NPV approach, these companies could benefit
(maximize shareholder value) by applying the eNPV approach (Baker, Dutta, &
Saadi, 2011).
4. 2 Real Options VS. Financial Options
The theory on real options stems from the theory of financial options. The
difference between financial options and real options is that the underlying
asset for a financial option is an intangible asset traded in the market whereas
the underlying asset a for real option is a tangible asset such as a project or
business unit and the asset is not traded in the market. Both types of options
give the right, but not the obligation, to take an action (Berk, 2011).
Generally there are two types of options: call and put options. The owner of a
call option has the right to buy the asset at a specific price (exercise price) for a
specific time period. The owner of a put option has the right to sell the asset
within a specific time period (Mun, 2006 p. 349). Often real options are nontradable, this means, there is no liquid market for the asset as there is for
financial options. Since there is no market for real options they can be quite
difficult to valuate compared to financial options.
Further, there is a difference between American options and European options;
American options can be exercised at any time within a given time period
whereas European options only can be exercised at maturity.
15
If the owner of an American call option finds that the price of the underlying is
higher than the exercise price (i.e. the exercise price is lower than the strike
price) then the option should be exercised and the option will be “in the money”.
If, on the other hand, the value of the underlying is lower than the exercise
price, the option will be “out of the money” (Mun, 2006, p.350).
4. 3 Types of Real Options:
There are many different types of real options and some of the most commonly
used will be described with examples below. As mentioned above, management
can make decisions which have an impact on the project after the investment
decision has been made, but before the end of the project. A flexible
management can make decisions to defer, expand, abandon a project etc.
Real options:
-
The option to abandon: suppose a pharmaceutical company is uncertain
about the development of a new drug; it may not be approved by the
FDA. Therefore, the company can create a strategic abandonment option
for a 10 year time period. If the project is abandoned within the 10 year
timeframe, the company can sell its intellectual property rights to another
pharmaceutical company and save the cost for further development
(Mun, 2006, p. 163). This kind of option in an American put option (the
right to sell).
-
The option to expand: suppose a biotech company is developing a new
drug, if the drug is approved by the FDA, management has an option to
expand production by building a new building. Or management may
decide to expand the use of a drug, for instance by making a pill for a
drug that is currently injected with needles. Such an option is an
American call option; it can be exercised at any time within the given time
period. It gives the holder of the option, the right, but not the obligation to
expand. If the cost of expanding is lower than the estimated profitability
of expanding, then the option will be exercised.
16
-
The option to wait (defer): if uncertainties are large, management can
defer investments until the uncertainties have decreased. For instance,
management may defer a sale because the price may or may not
increase within five years. The management owns an American call
option; if the expected profit is higher than the cost of the option, the
option is in the money and will be exercised.
-
The option to contract: suppose a small biotech company is going into
the clinical phases of development, the company may not have enough
capital to undertake the clinical tests themselves; therefore management
may decide to enter into an agreement/contract with another company to
undertake the development. The management can during the agreed
time period use the option to outsource the clinical test part. Since the
option give the right, but not the obligation to sell off some of the
capacity, it is an American put option (Copeland 2003, p. 135).
-
Sequential compound option: is a more advanced option. The value of
sequential compound options are contingent upon other options; for
instance, in a project with multiple phases, success depend on the
success of previous phases. Sequential compound options are often
used in connection with R&D projects. Sequential compound options can
consist of different option types such as options to expand, abandon,
defer etc. The phase/stage 2 option depends therefore on the previous
phase/stage 1 option (Mun, 2006, p. 421).
In order to value real options it is assumed that the management is competent,
this means, managers act in the interest of the shareholders and the company
through the maximization of wealth and minimization of risk and losses (Mun,
2006, p. 31).
If a real option valuation should be successful, five requirements must be
satisfied (Mun, 2006, p.38):

A financial model must exist
17

Uncertainties must exist. If there are no uncertainties then there are no
real options

Uncertainties must affect decisions when the firm is actively managing
the project and these uncertainties must affect the results of the financial
model

Management must have strategic flexibility or options to make midcourse
corrections when actively managing the projects

Management must be smart enough and credible enough to execute
options when it becomes optimal to do so
If these requirements are not satisfied, then it will be unnecessary to conduct a
real option valuation.
4. 4 Real Option Criticism
Real option valuation is not thoroughly approved as the best valuation tool,
some of the criticism regarding real option valuation has the do with
management actions and the assumption of constant variables.
The criticism regarding constant variables is based on the fact the many of the
input variables used in the real option valuation are not constant during the life
of the project. For instance, project volatility may change quite often because
the input variables use to calculate this measure may change. A change in
project volatility can have a large impact on the RO value.
Further, skeptics argue that managers will choose projects with high risks
because these have higher volatilities and thereby higher option values. Other
people in favor of RO argues that the criticism is incorrect because managers
should hedge negative risk if they have projects with high volatility. It can also
be discussed if managers can exercise the option at the right time (for American
options).
18
5. Step-Wise Approach to Valuing Real Options
As can be seen from above real option valuation is not widely applied by
companies; some managers argue that it requires too much sophistication and
real option valuation is only an exercise for academics. I argue, that the
calculation of real options can be fairly easy if good model exists.
In order to make the real option valuation easier both Mun 2006 and Copeland
& Anitkarov 2003 suggest managers use a step-wise approach to valuing their
real options. The step-wise approach will in time make the valuation of real
options as easy as the calculation of the traditional NPV. Mun and
Copeland/Antikarov’s approaches and steps are a bit different, for instance Mun
suggest an eight-step approach whereas Copeland/Antikarov suggest a fourstep approach. Both agree on using the risk-neutral probabilities because it is
easier than applying the replication portfolio approach. The two approaches will
in theory give the same result.
Below I will develop a six-step approach based on the risk neutral probabilities.
The step-wise approach is similar to the four-step approach suggested by
Copeland/Antikarov. An overview of the six-step approach can been seen
below.
Figure 4: Six-step Approach to Valuing the Expanded Net Present Value
Step 1
Identify and calculate base variables
Step 2
Conduct strategic analysis
Step 3
Set up project forecast
Step 4
Calculate project volatility
Step 5
Real option valuation
Step 6
Sensitivity analysis
•
•
•
•
•
Beta
WACC
Risk free rate
Return on equity
Debt level
• Internal analysis
• External analysis
• SWOT
• Industry variables
• Project specific variables
• Net Present Value
• Tornado diagram
• Management estiamates and implicit volatility
• Monte Carlo simulation of variables --> project volatility
•
•
•
•
•
•
•
Identify real options
Calculate up and down movements
Binomial tree 1
Calculate risk neutral probabilities
Binomial tree 2
Binomial tree 3
Final eNPV
• Sensitivity analysis on RO input variables
Source: Own Construction
19
The first part (step 1-3) are based on the calculation of the traditional NPV, the
second part (step 4-6) are concerned with the valuation of the real options and
final eNPV. As can be seen from the figure, step 5, is the most important step
for the calculation of RO. The calculation of RO is based on two important
assumptions:
The first, is the market asset disclaimer assumption (MAD). This assumption
states that for the asset under valuation, one can assume that the present value
of the asset (without flexibility) can be used as the underlying risky asset. This
assumption means that the traditional NPV is the best unbiased estimate of the
project value (Copeland & Antikarov, 2003, p.94-95). If the MAD assumption
was not used, it would be necessary to find the replication portfolio in order to
conduct the valuation (which is quite difficult because real options are unique
and not traded on the market).
The second assumption is that prices or cash flows follow a random walk, which
means that uncertainties can be simulated for instance with the use of Monte
Carlo techniques (Copeland & Antikarov, 2003, p. 219).
5. 1 Step 1: Identify and Calculate Base Variables
In step 1, the base variables for the forecast in step 3 are identified and
calculated. The goal is to calculate the weighted average cost of capital
(WACC) because WACC will be used as the project discount rate. Before
WACC can be estimated one must calculate or find a number of other input
variables, for instance: beta, the risk free rate, return on equity, and debt level.
WACC will be used to discount the project cash flows. It can be argued that
WACC is not the most appropriate discount rate since the risk of the company is
rarely the same as the risk of the project (Arnold & Crack, 2004). The solution to
that could be to use the opportunity cost of capital. In this paper, however, I will
use WACC because the valuation will be conducted on PROSTVAC a vaccine
that is estimated to be worth 45% of BAVAs share price, therefore, much of the
company risk will be the same as the project risk. An assumption when applying
20
WACC is that the capital structure of the firm doesn’t change – this is a strong
assumption.
WACC is defined as:
𝑊𝐴𝐶𝐶 = 𝑅𝐸 ∗
𝐸
𝑉
𝐷
+ (1 + 𝑇) ∗ 𝑅𝐷 ∗ 𝑉
Equation 2
Where:
RE = Return on equity
RD = Return on debt
V = Market value of the company
E = Market value of equity
D = Market value of debt
T = Corporate tax rate
In the equation RE is unknown (the other inputs can be found in BAVAs financial
statements) and has to be determined with the help of the Capital Asset Pricing
Model (CAPM).
RE = β * (RM – RF) + RF
Equation 3
Where:
RE = Return on equity
β = Covariance with the market portfolio (reflects market risk also called
systematic risk)
RM = Market return
RF = Risk free rate
21
The unknown variables in this equation are β, RM and RF and these will be
determined below.
Beta can be calculated as the covariance with the market portfolio:
β=
𝐶𝑜𝑣 (𝑅𝐴 ,𝑅𝑀 )
Equation 4
𝑉𝑎𝑟 (𝑅𝑀)
Where:
RA = Rate of return from asset
RM = Market return
The forecasts for both PROSTVAC and RSV will have a timeframe for more
than ten years. This timeframe should be reflected in the beta estimate. Since
BAVA may be in the process of turning into a pharmaceutical company with
lesser risk, it can be argued that BAVAs beta will move towards the market
average. To incorporate the lower company risk Bloomberg’s adjusted beta
formula will be used to calculate BAVAs beta (Hiller, 2008, p.159-160).
𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝑏𝑒𝑡𝑎 = 0,66 ∗ 𝑅𝑎𝑤 𝑏𝑒𝑡𝑎 + 0,34
Equation 5
If beta equals 1, the company follows the market. If beta is 0 then there is no
correlation with the market. If beta is greater than one, the company’s return will
vary more than the market return. For instance, if the market decreases with
one, the company will decrease with more than one. It is also possible the beta
can be negative; this means that the company is inversely correlated with the
market.
5. 2 Step 2: Strategic Analysis
For managers it is important to be aware of the company’s strategic options
because it increases the value of the company. In order to identify the strategic
22
options, management can conduct a strategic analysis; the analysis should
consist of an internal and external analysis and conclude with a SWOT analysis
to cover all aspects of the company. There are a number of ways to conduct a
strategic analysis and a company should choose the one that fits their company
the best.
5. 3 Step 3: Forecasting and Net Present Value
By applying the inputs from the above steps, it is now possible to set up a
forecast for the project. From the forecast the traditional NPV should be
calculated.
It is important to notice that the forecast will be used as a mean to conduct a
real option valuation and therefore past events (investments) are not considered
relevant for the forecast. If past events were considered to be relevant, it would
be possible that a tax benefit should be included in the forecast. Biotechnology
companies often experience huge losses prior to the launch of their products;
the tax credit from this loss can be realized when the company increases the
revenue.
Another consideration for the forecast is which measure of profit to include. In
this paper, the net operating profit less adjusted taxes (NOPLAT) will be applied
as the profit measure. Another measure of profit is the free cash flows (FCF).
The calculation of FCF involves calculations of depreciation, net working capital
and provisions. These inputs are more appropriate on a company level and
therefore the FCF is not used as a profit measure. The corporate tax rate is set
to 25% which corresponds to the Danish corporate tax rate.
5. 4 Step 4: Project Volatility
Step 4 is the first step in the second part of the six-step approach. The focus in
the second part was to calculate the RO value. The project volatility is an
important estimate used later in the RO valuation.
23
Volatility is a measure of the variation in variables over time. Volatility adds
value to RO projects because managers can change the course of the project.
There are two approaches to estimating the consolidated volatility: the historical
and the subjective approach. From the consolidated approach it is possible to
get a single estimate of volatility from many uncertainties (Copeland &
Antikarov, 2003, p.244). If there are no historical data for the project it is better
to use the subjective approach i.e. the subjective estimates of management is
used. The first part in estimating the volatility is to identify variables of
uncertainty from the forecast. A good way to do this is to make a tornado
diagram. Tornado diagrams are graphic illustrations which show how much a
difference of for instance +/- 25% (in a variable) will impact the NPV. The most
uncertain variables will be at the top and the variables with low uncertainty will
be at the bottom thus it looks like a tornado.
5. 4. 1 Management Estimates:
If there are no historical data available, which often is the case with real options,
management can provide estimates of the inputs needed to calculate the
implicit volatility. More specifically, management must provide estimates of the
highest (and lowest) values of the variable under consideration, with 95%
confidence. Further, a growth rate of the variable must be determined. This
growth rate, ri, is based on the assumption that the uncertainty (from variables)
follows a Geometric Brownian Motion. The assumption of Geometric Brownian
Motion means that the value of the variable in the next period, Vt+1, is equal to
the value in the previous period, Vt, multiplied by the growth factor. A further
assumption from the Geometric Brownian Motion is that there is no
autocorrelation at the beginning (Copeland & Antikarov, 2003, p. 260).
The implicit volatility can be calculated using the following formula:
𝑢𝑝𝑝𝑒𝑟
𝜎𝑢𝑝𝑝𝑒𝑟 =
𝑉
ln( 𝑇
𝑉0
𝑙𝑜𝑤𝑒𝑟
)− ∑𝑛
𝑖=1 𝑟𝑖
2√𝑇
,
𝜎𝑙𝑜𝑤𝑒𝑟 =
𝑉𝑇
∑𝑛
𝑖=1 𝑟𝑖 − ln(
𝑉0
2√𝑇
)
Equations 6
Where 𝑉𝑇𝑙𝑜𝑤𝑒𝑟 is the value of the variable in period T with 95% confidence and r i
is the growth rate.
24
5. 4. 2 Simulation
Once the uncertain variables have been identified and the corresponding
implicit volatility has been calculated, the project volatility can be estimated
using a Monte Carlo simulation – a simulation will give a more reliable result.
The Monte Carlo simulation can be run with the help of an Excel add-in called
Crystal Ball or some other simulation software, in this paper Crystal Ball will be
applied.
First, in Crystal Ball, the probability distribution for the uncertain variables has to
be selected. There are many different probability distributions for instance:
normal, triangular, uniform, lognormal and beta. Since I use the Geometric
Brownian Motion assumption and the fact that prices will never go negative, the
lognormal distribution is chosen. The lognormal distribution requires two more
inputs; the mean value, which can be found in the forecast as the first value in
the variable, and the implicit volatility for the variable. The goal of the simulation
is to forecast the percentage change in the return of the project from one time
period to the next. The variable for the percentage change will be called z. The
formula for z is:
𝑃𝑉
𝑧 = ln(𝑃𝑉1 )
Equation 7
0
To calculate z, the value of PV0 must be held constant while the simulation is
run (Copeland & Antikarov, 2003, p. 249). After the Monte Carlo simulation for z
the statistics for z can be seen. It is in this statics the project volatility is shown
as the standard deviation. Biotech projects often have volatilities above 50%
because of the high uncertainty. If a project volatility was estimated to be 0 it
would imply that there is no uncertainty in the project and the RO value would
be zero, therefore the traditional NPV analysis can be seen as a special case of
the real option analysis (Bogdan & Villiger, 2010, p. 101).
When the project volatility has been estimated the final part of the real option
valuation can begin.
25
5. 5 Step 5: Real Option Valuation
In this step the final eNPV is calculated, but before that calculation the value of
the real option must be estimated. The real option value is estimated with the
help of binomial trees, up/down movements and the risk neutral probability.
5. 5. 1 Binomial Tree 1 – Value of Underlying Asset
There are different approaches to estimating the value of an option. The most
applied methods are closed-form solutions, partial-differential equations, and
binomial lattices (Mun, 2006, p. 123). A common approach for valuing real
options is by applying binomial trees because they are easy to implement and
explain. Closed-form solutions such as the Black-Scholes model are difficult to
explain and use complicated mathematics.
There are two approaches to solving a binomial lattice; the two methods give
the same result:
Market-replicating portfolios: assumes there are a number of traded assets in
the market which can be replicated and match the project payout policy. This is
often the case for financial options.
Risk-neutral probability: the idea with the risk-neutral probability is to risk-adjust
the probabilities on the expected cash flows. When the cash flows are risk
adjusted it is possible to discount them with the risk free rate. Compared to the
market replicating portfolio this approach is not as risky because it does not use
a risky set of cash flows (Mun, 2006, p. 128).
In option models which apply the risk-neutral probability there is a minimum
requirement of at least two binomial lattices; one showing the value of the
underlying asset and the other showing the value of the option. The lattice for
the underlying asset starts with the traditional NPV at time zero without
technological uncertainty (a discussion on the role of uncertainty can be seen in
paragraph 5.5.2.1). The value of the underlying asset is then multiplied with the
up and down factors from left to right making the branches on the binomial tree
recombining.
26
The risk-neutral probability (p) and the up (u) and down (d) factors are
calculated from the below formulas:
𝑢 = 𝑒 𝜎√∆𝑡
𝑑 = 𝑒 −𝜎√∆𝑡 =
1
𝑝=
𝑢
𝑟 ∆𝑡
𝑒 𝑓∗ −𝑑
𝑢−𝑑
Equations 8
T= time to expiration
σ = volatility
rf = risk free rate
ΔT = time steps
The risk-neutral probability is not the probability of increasing stock prices.
Rather, it is a number that illustrates how the actual probability should be
adjusted to keep the share price the same in a risk-neutral world (Berk, 2011).
5. 5. 2 Binomial Tree 2 – Value of Real Option
After the first lattice which shows the value of the underlying asset, a second
lattice for the value of the option has to be made. To calculate the value of the
option one should use a process called backward induction. Backward induction
means that the value of the option is calculated backwards i.e. the nodes at the
end of the lattice (terminal nodes) are calculated first – from right to left (Mun,
2006, p. 165).
The value of an abandonment option at the terminal node (which is a put option
– see paragraph 4.3) is thus calculated as the max of zero and the cost which
can be saved by abandoning the project less the value of the underlying asset
multiplied with the technological risk. If the value is positive, management will
abandon the project (the put option is in the money). If the value is zero, the
management will continue with the project. The values at the intermediate
nodes can be calculated as:
27
𝑉𝑎𝑙𝑢𝑒 𝑜𝑓 𝑖𝑛𝑡𝑒𝑟𝑚𝑒𝑑𝑖𝑎𝑡𝑒 𝑛𝑜𝑑𝑒𝑡 =
𝑀𝑎𝑥(0; (
𝑝∗𝑈𝑝 𝑚𝑜𝑣𝑒𝑚𝑒𝑛𝑡𝑡+1 +(1−𝑝)∗𝐷𝑜𝑤𝑛 𝑚𝑜𝑣𝑒𝑚𝑒𝑛𝑡𝑡+1
𝐷𝑖𝑠𝑐𝑜𝑢𝑛𝑡 𝑓𝑎𝑐𝑡𝑜𝑟
)
Equation 9
From equation 9, it is seen that the value of the intermediate node is the
discounted value of the up and down movements from the previous period
multiplied with p and 1-p respectively. This calculation assumes that the option
is a European option because European options can only be exercised at the
end of expiration.
The inputs for the second lattice are: values from the first lattice, the risk neutral
probability, a discount factor and the technological uncertainty. Since
technological uncertainty has been kept separate from the calculation of the
value of the underlying asset it is possible to discount the value of the option
with a discount factor based on the risk free rate.
5. 5. 2. 1 Uncertainties
In biotech projects there are two types of uncertainties, these different types of
uncertainties must be kept separate in order to get a correct RO valuation – this
is called the separation approach (Copeland & Antikarov, 2003, p. 221). The
two types of uncertainties derives from market and technological factors. Market
uncertainty is characterized by factors that are known today but will become
more diffuse through time; market uncertainty can for instance be the price.
Technological uncertainty is diffuse now but will resolve in time. For instance, a
biotech company may have a 70% probability of FDA drug approval today, but
the probability will be less diffuse in a few years. Since the technological risk is
independent of the market, it can be discounted with the risk-free rate
(Copeland & Antikarov, 2003, p. 271 + 276). Whereas the market risk should be
discounted with a project specific discount rate, in this paper WACC was
suggested to be the best discount rate.
Therefore, the present value of the underlying asset, S_0, at the beginning of
binomial tree 1 is the traditional NPV, without R&D costs and technological risk.
In binomial tree 2, technological risk will be added by multiplying it with the real
28
option value. When only the technological risk is added, the RO value should be
discounted with the risk free rate.
5. 5. 3 Binomial Tree 3 – Management Options
The third binomial tree is not really a part of the real option valuation, it is
included in this paper because it illustrates how managers should act. For
instance, if an abandonment option shows a positive value, managers should
exercise the option, if, on the contrary, the value is zero, managers should hold
the option.
5. 5. 4 Calculate Expanded Net Present Value
Now the values of the real option and the static NPV have been estimated, the
final eNPV can thus be calculated by adding the option premium with the static
NPV. If the option has no value than eNPV will equal NPV.
5. 6 Sensitivity Analysis
After the RO analysis it is important to evaluate how the input variables such as
the project volatility and strike price influence on RO value.
A sensitivity analysis can be used to analyze what will happen to the RO value if
a variable change with 5%, 10% or 15%. It is also possible to set up a two or
three factor model where it is possible to see what will happen to the RO value
if there is a five percent increase in one variable and a 20 percent decrease in
another variable. Therefore, the final RO value should be seen as matrix of
values since input variables may change over time. The sensitivity analysis will
be conducted on the RO value since ROs are the focus in this paper. It is,
however, also possible to conduct a sensitivity analysis on the variables for the
traditional NPV. A limit to this RO sensitivity analysis is that it is not possible to
see where the change comes from. For instance, it is possible to analyze what
will happen if the project volatility change 5% but the analysis does show where
the 5% change stems from. A change in project volatility may come from
changed assumptions in one or more of the forecast variables.
29
For managers, the change in a project’s RO value is important because the RO
value can be a significant factor in the investment decision. Therefore, a
sensitivity analysis on the share price is irrelevant in this case.
6 Real Option Valuation
Now the steps for valuing real options have been explained it is time to apply
them to two real cases. The first case is a vaccine candidate against advanced
prostate cancer called PROSTVAC, PROSTVAC is in phase 3 development.
PROSTVAC is estimated to constitute 45% of the value of BAVAs target share
price of 80 DKK. The estimate comes from senior investor in Jyske Bank, Frank
Andersen (the short e-mail correspondence can be seen in appendix 2). The
second vaccine is RSV which is in the preclinical phase of development.
Following the argumentation in paragraph 4, the hypothesis is that RSV will
have a higher RO value than PROSTVAC because there are more uncertainty
related to RSV than PROSTVAC.
7. Valuation of PROSTVAC©
PROSTVAC is an immunotherapeutic vaccine candidate for the treatment of
advanced prostate cancer. Immunotherapeutic treatments use the body’s own
immune system to fight the cancer. PROSTVAC is currently in phase 3 clinical
trials where it is going to be tested in 1200 patients from more than 20 countries
(Bavarian Nordic, 2011a). PROSTVAC has been developed in collaboration
with the National Cancer Institute (NCI) of the United States. There are many
different ways to treat prostate cancer and often the treatment consists of a
combination of different treatments.
PROSTVAC will be an off-the-shelf vaccine; it should be taken seven times over
a five months period (Investor Presentation, 2011). Tests have shown that on
average patients live 8,5 months longer when they use PROSTVAC compared
to placebo. Further, the risk of death is reduced with 44% compared to placebo.
30
7. 1 Step 1: Calculate Base Variables
In order to calculate WACC, the expected return on equity, RE, must be
estimated. One of the inputs needed to calculate return on equity is the market
return. The market return can be found with the help of a market benchmark, I
have chosen to use the MSCI World Index. MSCI also have a benchmark for
Denmark, but the Danish market is heavily weighted with Maersk and Novo
Nordisk wherefore it is considered not to fully reflect the market. The time frame
for estimating the variables have been set to three years. However, according to
theory, a five-year time frame should be applied. If a five-year time frame is
applied in this paper, the market return will be negative. The reason for the
negative market return is the economic crisis which begun a little more than five
years ago. In other publications it has been suggested to use the historical
market premium (between 5-7%) to overcome this problem (McKinsey, Inc.,
Koller, Goedhart, & Wessels, 2010). With a three year time frame (26/10-2009
to 26/10-2012) the market return is estimated to be 6,77% (see CD-ROM).
The calculations of beta can also be seen in the CD-ROM. The adjusted beta is
estimated to 1,22 which means that BAVA is more volatile than the market.
The risk free rate for a 10-year government bond was 1,76% on the 31st of
December 2012 (U.S. Department of the Treasury, 2012). In a perfect world
one should use a government bond with different maturity for each year of cash
flow, since this can be very comprehensive, an approximation is often used
(McKinsey et al., 2010). The risk free rate should be in the same currency as
the company’s cash flows in order to incorporate inflation. It can be discussed
whether the Danish or the US government bond should be applied. I use the US
bond because most of the income will come from the sales in the US.
Biotech firms are often financed 100% with equity, therefore RE = WACC. The
reason why biotech companies are equity financed is that banks will require a
high interest rate on loans since they cannot be sure whether the development
will be successful or not. For biotech companies it is cheaper to get equity
finance. Bavarian Nordic is also a 100% equity financed:
31
From BAVAs annual report in 2011 it can be seen that BAVA had borrowings of
99 DKK million, this amount dropped to 96,2 DKK million in 2012. Since BAVAs
net debt can be calculated as borrowing less cash and other financial assets it
is clear that BAVA has a large negative net debt which implies that BAVA is in
essence 100% equity financed (the calculations are not shown, the numbers
are found in BAVAs annual report for 2011).
Therefore, the WACC used for further calculations will be WACC =
1,76%+1,22*(6,77%-1,76%) = 7,90%.
Since BAVA disclose a lot of information about PROSTVAC it is possible to
include more accurate base variables than the base variables identified as
industry specific. The time frame for PROSTVAC and phase 3 testing is a little
more than four years: the enrolment of PROSTVAC in the phase 3 study was in
November 2011 and the estimated completion date for the phase 3 study is in
the second half of 2015 (Health, 2012). In order to allow for a little delay in the
phase 3 study it is assumed that phase 3 testing will end in December 2015.
Therefore, the total testing time for PROSTVAC in phase 3 will be 50 months
which is more than the average testing time seen in paragraph 3.1. Further,
BAVA estimates the cost of phase 3 will be $150 USD million.
7. 2 Step 2: Strategic Analysis
In the following I will conduct an external analysis for PROSTVAC and an
internal analysis for BAVA. The internal analysis will be based on Porters Value
Chain Framework and the analysis will be made on company level since an
internal analysis for both assets (PROSTVAC and RSV) will overlap. Further, a
SWOT analysis will be included in order to identify the strengths, weaknesses,
opportunities and threats, these observations will be important for strategic and
forecasting reasons.
7. 2. 1 External Analysis (PROSTVAC)
The external analysis will be based on factors of market attractiveness, such as
market potential, customer characteristics and the competitive environment.
32
Porters 5 Forces is not used as a method for analyzing PROSTVACs external
environment because the model gives a static overview of the current industry
situation. For the purpose of setting up a forecast for PROSTVAC an overview
of the current industry situation is not appropriate.
Market Potential: In the U.S., prostate cancer is the second most common
cancer in American men. The American Cancer Society estimates that there
will be 241,740 new cases of diagnosed prostate cancer in 2012 (American
Cancer Society, 2012) and on the world level 780,000 men will be diagnosed
with prostate cancer (Bavarian Nordic, 2011b) (Prospectus, 2011, p. 49). During
the recent years the number of people diagnosed with prostate cancer has
increased, this doesn’t necessarily mean that more people develop prostate
cancer, it may also mean that tools for detecting prostate cancer have
improved. According to cancer.dk the risk of developing prostate cancer has
increased with 8,2% during the last 10 years (Kræftens Bekæmpelse, 2012).
BAVA, on the contrary, expects the growth to be closer to 2% (Investor
Presentation, 2011).
PROSTVAC is for the treatment of people with advanced prostate cancer, on
average almost 14% of the people diagnosed with prostate cancer will be
suitable for treatment. This calculation is based on the average number of US
men diagnosed with prostate cancer each year (214.730) and the people
suitable for treatment with Provenge© (30.000) (Beasley, 2012). Provenge© is
an FDA accepted competitor to PROSTVAC and it is assumed that PROSTVAC
will have the same customer base. Therefore people suitable for treatment are:
(30.000*100)/214.730 = 13,97%
The price for PROSTVAC is not certain yet, it depends on the price-strategy
BAVA choose in the future; managers at BAVA can either set a high price (but
below Provenge©) and receive a high profit. Or they can set a low price so they
can increase their market share fast. There is no doubt that PROSTVACs costs
will be a lot lower than $60.000USD which is the cost for Provenge © – the
selling price is $93.000 USD (Baghdadi, 2010). Even if BAVA was to sell
PROSTVAC at a price of 40.000 – 50.000 USD they would still have a very high
profit margin (Investor Presentation, 2011). Jyske Bank estimates the future
33
price for PROSTVAC to be around 60.000 DKK (Jyske Bank, 2010) other
people guess that the costs for producing PROSTVAC is 1/6 of the production
cost for Provenge©. Given these statements the cost for producing PROSTVAC
is assumed to be 10.000 USD and if BAVA applies the same mark-up as
Provenge© (approx. 35%) the selling price for PROSTVAC will be $13.500 USD
per treatment.
Customer Characteristics: The customers for PROSTVAC will be private and
public hospitals. Most of the customers are located in high-income countries
and will therefore be able to pay for the treatment. The customers do not have a
large bargaining power because they are many and small. This is in contrast to
the customers of IMVAMUNE (Bavarian Nordics successful smallpox vaccine),
here the customers are government and organizations which need to stockpile
a large quantity of the vaccine in order to prevent a bio attack.
Competitive Environment: The development of immunotherapeutic cancer
treatments is quite new; therefore there are a limited number of competitors.
Currently there is only one vaccine in the market, Provenge© developed by
Dendreon. Provenge© was approved in April 2010 and there has been huge
expectations for sales, the sales has, however, not been nearly as good as
expected. This may be due to the high price; a treatment which consists of 3
treatments in a month costs $93.000 and extends life for four months. Expected
net revenue for Provenge© was $350-400 million in 2011 but the net revenue
was in fact $213,5 million (Dendreon, 2011). Both Dendreon and BAVAs share
prices fell after that announcement, the reason was that the market size might
be lower than assumed by Dendreon.
As an alternative to immunotherapy, Johnson and Johnson has developed a pill
called Zytiga. Zytiga works by interrupting the androgen-making process
(androgen feeds the tumor) (Zytiga, 2012). Zytiga is to be taken once a month
for 8 months and the total cost is $40.000 which is a lot cheaper than Provenge
(Forbes, 2012).
A new product that was approved by the FDA in July 2012 is Xtandi which also
interrupts the androgen-making process. Studies show that patients live on
34
average 4,8 months longer compared to placebo drugs. Xtandi should be taken
on a daily basis for a month and the total cost is $7450 (Pollack, 2012).
Both Progenics Pharmaceuticals and BioSante Pharmaceuticals (GVAX
Prostate) have treatments for prostate cancer under development and is
currently in phase 2. Another treatment that was developed by Onyvax has
been suspended.
In conclusion, there are a number of competitors in the market, which offers
different treatments for prostate cancer patients in the advanced stage. Since
PROSTVAC will be cheaper and has shown fewer side effects than Provenge, it
is expected that BAVA will gain market share from Provenge©. The other two
competitors, Zytiga and Xtandi, can pose a threat if they show better results
than immunotherapy. The treatments under development will not be considered
as a threat to PROSTVAC© because they still need to be fully developed and
that will take years. If one should place PROSTVAC in the Boston Consulting
Group matrix (BCG matrix), then it would be a STAR; there are huge growth
opportunities and the possibility of gaining a large market share is possible
because PROSTVAC is a superior product compared to all of the other
products on the market or under development.
7. 2. 2 Internal Analysis (Bavarian Nordic)
The internal analysis on BAVA will be conducted by applying Porter’s Value
Chain framework. The value chain framework was suggested by Michael Porter
and the goal is to undertake an assessment of the overall added value of the
business. Normally, the strategic analysis should be conducted on product level
because it is important to identify how each part of the organization contributes
to the whole organization (Lynch, 2009). Even though I analyze two of Bavarian
Nordic’s products, I will conduct the value chain analysis on company level. The
reason for this is that BAVA has no project specific estimations in their financial
statements. In connection with that, BAVA is still a relatively small company
wherefore, some product and support activities may be done for both products
35
at the same time. The analysis will however have focus on PROSTVAC and
RSV.
Primary Activities:
The value chain is composed of primary activities and support activities. The
primary activities are: Inbound logistics, operations, outbound logistics,
marketing & sales and service. Since BAVA does not sell its products on a
commercial scale (except for IMVAMUNE which is not that relevant for this
report) outbound logistics, marketing and sales are not a part of BAVAs value
chain and are therefore considered a weakness. Instead I will focus on inbound
logistics, operations and the support activities.
Inbound logistics/procurement: Suppliers are very important for BAVA and
BAVA strives to have at least two suppliers for critical commodities. BAVA
estimates that if a supplier of a critical commodity fails to deliver, it will delay
production with 3-6 months (Prospectus, 2011, p.22). BAVA must eliminate the
possibility of supplier failure by continually searching for possible partners.
Depending on the role of suppliers this can either be a strength or weakness.
Currently it is something in between; BAVA have the needed suppliers but they
are still vulnerable if a supplier fails to deliver.
Operations: the development of PROSTVAC takes place at BN
ImmunoTherapeutics located in California, USA. The current production of
PROSTVAC takes place at IDT Biologika in Germany. IDT Biologika is not large
enough to produce PROSTVAC on a commercial scale and since BAVA is
inexperienced in production, it is very important to find a partner which has
enough production capacity.
Support activities:
Firm infrastructure: here the role of management and the board, legal
capabilities and the financial resources will be analyzed:
Owners and management: the chairman of the board is Asger Aamund,
Aamund founded BAVA in 1994. Aamund has great experience in the Danish
36
biotech sector where he has been involved in, among others, Ferrosan and
NeuroSearch. Asger Aamund is also the chairman of A.J. Aamund which has
an ownership share of more than five percent in BAVA. A.J. Aamund is in
financial trouble and had a deficit of 297 DKK million in 2011. Nordea Bank will
protect A.J. Aamund for the rest of 2012 (Frovst, 2012). Therefore, Aamund is
very dependent on the success of BAVA (increase in share price) if A.J.
Aamund should survive in the near future. Asger Aamund has often been
considered to be a good profile for BAVA but his good reputation has decreased
after the financial trouble with A.J Aamund.
The rest of the board is also very experienced in the pharmaceutical and
biotechnological sector. The current CEO is Anders Hedegaard, Hedegaard
joined BAVA in 2007 and has experience from Alk-Abello A/S and Novo
Nordisk. The competences of the board and management is considered a
strength for Bavarian Nordic.
Legal capabilities: in the biotech industry it is very important a company can
develop and protect its assets. One way to do this is to apply for patents and
other intellectual property rights. BAVA is very competent in this area and it has
patent portfolio of more than 750 patents and 350 applications for patents
(Prospectus, 2011, p. 70). BAVA is very concerned about protecting existing
rights; in 2005 BAVA filed a lawsuit against Acambis, a competitor they accused
of stealing company secrets about the MVA-BN technology used for smallpox.
The lawsuit was settled in 2007 (Bavarian Nordic, 2007). Another dispute
concerning MVA-BN was with Oxford BioMedica this was settled in 2010
(Prospectus, 2011, p. 35).
Financial resources: BAVA cannot finance its R&D and operations from
product sales. Therefore, BAVA have had a number of share emissions to
increase capital, the latest in 2011. The capital raised in 2011 was used to
finance phase 3 development for PROSTVAC. BAVA expected to find a partner
that would finance and pay milestones for PROSTVAC before phase 3 trials. A
partner was not found and BAVA had to finance PROSTVACs phase 3 trials
themselves thus the share emission. Now BAVA expects to find a partner for
the commercialization of PROSTVAC but so far no partner has been found.
37
BAVA expects a partner to pay milestone and royalties, the milestones are
important because they should to finance BAVAs other vaccine developments.
BAVA is lacking capital and may have to postpone the development of their
vaccines (Prospectus, 2011, p. 9). Lack of financial resources is certainly a
weakness of BAVA.
Human resource management: one of the most important resources in BAVA
is their employees. In order to attract the best employees, BAVA offers flexible
working hours (important for the work-life balance), a competitive salary
package, good retirement, insurance and international experience (Bavarian
Nordic, 2012b). At the time of writing, BAVA has more than 450 employees and
only four vacancies which may imply that employees are happy to work at
BAVA.
Technology development: BAVA owns the patent rights to the MVA-BN
(Modified Vaccinia Ankara – Bavarian Nordic) platform. MVA-BN is used in
most of BAVAs development programs and have proven to be very successful.
Further, BAVA is also interested in in-licensing for the development of anticancer, infectious disease products and technologies. Technology development
is an important strength of BAVA and should continue to be a focus area for
future success.
In conclusion, BAVA has its strengths in the technological development, board
of directors, employees, legal capabilities and management. BAVA lacks
financial resources and may have to postpone development activities if a
partner for PROSTVAC is not found. Operations is also an area that needs
attention, so far with a smaller production there are no problems, but if BAVA
experience success with their vaccines production facilities may turn into a
weakness.
7. 2. 3 SWOT Analysis
The SWOT analysis, which can be seen below, give managers a good overview
of strategic factors, such as strengths, weaknesses, opportunities and threats.
Management should identify ways in which to combine the identified factors and
38
improve them. For instance, management could find a partner for the production
of PROSTVAC thereby removing the current weakness ‘lack of large scale
production facilities’ and reducing the future cost of PROSTVAC.
Figure 5: SWOT Analysis
STRENGTHS (company level)

WEAKNESS (company level)
Management very experienced

Financial capacity
within biotech & pharma

Distribution

Large patent portfolio

Sales & marketing

Skilled employees

Supplier relations

Legal knowledge

Large scale production facilities

Technology & intellectual
property rights
OPPORTUNITIES
THREATHS
PROSTVAC
PROSTVAC

Attractive market

No partner agreement

High profitability

Competing products

New treatment therapy

Lower prices

Low costs
RSV
RSV

High profitability

High costs

Attractive market

No partner agreement

Few competitors

Few years on the market
Source: Own Construction
7. 3 Step 3: Forecast
Based on the inputs from step 1 and 2 it is possible to set up a forecast for
PROSTVAC, the forecast begins in 2013 where PROSTVAC is in phase 3
development (appendix 3). Since phase 3 development is estimated take up to
50 months, the annual R&D costs are 202 DKK million (843,73 DKK million
39
/50*12). In the forecast, it is assumed that BAVA will receive a patent extension
of five years due to the long development time. The patent for PROSTVAC was
received in 2004 and will expire at the end of 2023 where the patent extension
begins. PROSTVAC is expected to be ready for commercialization in 2017.
After patent expiry BAVA will continue to sell PROSTVAC but the sales will
slowly decrease (see paragraph 3.5). BAVA is very keen on finding a partner for
the commercialization of PROSTVAC and that combined with the fact that
BAVA has limited financial resources, it is assumed BAVA will find a partner
which pays a royalty. The royalty rate is set to 15% of sales because that is an
appropriate rate (see paragraph 3.3). No milestone payments are included
because these are very uncertain. Jefferies, an investment banker company,
also ignore potential milestones in their valuation of PROSTVAC. It should,
however, be mentioned that BAVA expects a future partner to pay milestones
(can be seen in the annual reports) but so far it is far from certain that they will
receive any.
BAVAs market share for PROSTVAC is assumed to be 35%. This illustrates
that PROSTVAC is a superior product which decreases the risk of death,
extends life and is a lot cheaper than competing products.
The corporate tax rate is 25% and the tech. risk is based on the findings in
paragraph 3.1
The static NPV with technological uncertainty is 956 DKK million. According to
this estimate, managers should continue the development of PROSTVAC
because NPV is high and positive. Even though PROSTVAC is in late state
development there is still a little uncertainty involved, this uncertainty may add
more value to PROSTVAC and therefore a real option analysis should be
conducted. It is, however, expected that the RO value will be very low or 0
because PROSTVAC already is in phase 3 development.
7. 4 Step 4: Project Volatility
In order to identify the uncertain variables, a tornado diagram has been made in
Excel (see appendix 5). The variables chosen for the tornado diagram are:
40
people suitable for treatment, royalty rate, price, BAVA market share and
growth. Other inputs such as WACC and technologic risk etc. will not be
evaluated here but in stage 6 where the sensitivity on the RO value will be
analyzed. From the tornado diagram it can be seen that the number of people
with prostate cancer is not that volatile compared to the other variables. None of
the variables will push the NPV below 600 DKK mill which is a good sign.
The variables of uncertainty will be used to estimate the project volatility. The
project volatility is based on the implicit volatilities from the above variables of
uncertainty. The implicit volatilities are based on subjective management
estimates because there are no historical data available (see appendix 6). The
implicit volatilities are based on the lower estimate of management. The implicit
volatilities are in the range of 8,73% and 54,93% the highest implicit volatility
comes from the royalty rate. The royalty rate is high because it is assumed that
an agreement on the royalty rate only can be made once which means that
there is no growth rate. The lowest volatility is based on the variable with
number of people with prostate cancer, this low volatility was expected because
the variable is quite certain and the growth rate is low.
Next, the estimated implicit volatilities are used in the spreadsheet for
simulation. For the Monte Carlo Simulation the variables of uncertainty must be
defined. All variables are defined as lognormal distribution, the standard
deviation is the implicit volatility and the mean value is the first number in the
forecast variable. In the simulation spreadsheet, assumption variables are
green and the decision variable is blue (see appendix 7).
In order to run the simulation a few changes must be applied to the
spreadsheet; first, a variable called z(return) is included as the decision
variable, this variable illustrates the difference between the NPV in period t=0
and t=1. The difference can be interpreted as the percentage change in the
return from one time period to the next. Second, R&D costs are not included in
the spreadsheet, this has been done in order to avoid negative numbers for the
z value.
41
By running the simulation 50.000 times we see that the project volatility is
55,80% (seen as the standard deviation in the statistics below). The volatility is
high but in accordance with the expectations from paragraph 5.4.2.
Figure 6: Step 4 - Simulation on Project Volatility for PROSTVAC
Source: Own construction
7. 5 Step 5: Real Option Valuation
There are a number of real options that can be included in the valuation of
PROSTVAC. First, it is uncertain that PROSTVAC will get a phase 3 approval
since it is still under development. If the results from PROSTVAC turns out to be
bad managers can choose to abandon the development of PROSTVAC and
thereby save the costs for the BLA. This is an abandonment option where the
management has the option but not the obligation to abandon the project (a put
option), where the exercise price will be the cost of BLA. Further, if the results
for PROSTVAC are bad the management can choose to sell the patent rights to
a competitor; this option is also an abandonment option. In the forecast, it has
been assumed that BAVA will find a partner for the production and
commercialization of PROSTVAC, but this could also have been included in the
valuation as an option: BAVA could invest and build production facilities
themselves instead of finding a partner; this would be a call option.
42
The real option valued in this case is the option to abandon the project before
approval (BLA), which means, if the results for phase 3 are not satisfactory
BAVA can abandon the project and save the BLA cost. An option of the salvage
value has not been included since it is very doubtful that BAVA will sell the
patents rights because BAVA expect to use the patents for other research.
Binomial Tree 1: The first step in the RO calculation is to estimate the
underlying value of the asset. In order to do that the up and down movements
must be calculated
𝑢 = 𝑒 𝜎√∆𝑡 = 𝑒 55,80%√0,25 = 1,3218
The up factor, u, is:
Where the volatility is the project volatility, delta t is the number of sub periods
in a year – here four sub periods are used. The larger the number of sub
periods the more accurate the binomial tree will be, four sub periods have been
chosen because they correspond to four quarters in a year. The down factor, d,
is 1/1,3218 = 0,7564. The NPV value with no technological uncertainty is 2.666
DKK million and will be used at the start of the binomial tree. The binomial tree
is constructed by adding the up and down values to the value of the underlying
asset moving from left to right.
Figure 7: Step 5 - Binomial Tree 1 - Underlying Value of PROSTVAC
STEP 5: BINOMIAL TREE 1 - VALUE OF UNDERLYING ASSET
Phase 3
2014
2013
q1
2666
q2
3524
2017
q3
4658
2666
1526
Input
Value of underlying asset (s_0)
Duration of subperiod, years ΔT
Yearly volatility, σ
Factor up, u
Factor down, d
q4
q1
6157
3524
2017
1154
8138
4658
2666
1526
873
BLA
2016
2015
q2
q3
q4
q1
q2
q3
q4
q1
10757
6157
3524
2017
1154
661
14219
8138
4658
2666
1526
873
500
18795
10757
6157
3524
2017
1154
661
378
24843
14219
8138
4658
2666
1526
873
500
286
32838
18795
10757
6157
3524
2017
1154
661
378
216
43405
24843
14219
8138
4658
2666
1526
873
500
286
164
57373
32838
18795
10757
6157
3524
2017
1154
661
378
216
124
75836
43405
24843
14219
8138
4658
2666
1526
873
500
286
164
94
2666
0,25
55,80%
1,321807
0,75654
Source: Own Construction
43
q2
100241
57373
32838
18795
10757
6157
3524
2017
1154
661
378
216
124
71
q3
132500
75836
43405
24843
14219
8138
4658
2666
1526
873
500
286
164
94
54
q4
175139
100241
57373
32838
18795
10757
6157
3524
2017
1154
661
378
216
124
71
41
As can be seen from the above figure, the value of the underlying asset can be
very different dependent on the development of PROSTVAC. The option
expires just before market commercialization where it was assumed that BAVA
has found a partner. In binomial tree 2 the value of the abandonment option will
be calculated.
Binomial Tree 2: The inputs needed for the second binomial tree is the
discount factor, exercise price, risk neutral probability and technological
probabilities. The risk neutral probability is calculated as follows:
𝑝=
𝑒 𝑟𝑓∗ ∆𝑡 − 𝑑
𝑒 1,76%∗0,25 − 0,7565399
=
= 0,4385
𝑢−𝑑
1,3218 − 0,7565399
Where u and d are already know from binomial tree 1, the risk free rate was
1,76% and the number of sub periods was four.
The value of the abandonment option is calculated using backward induction
see paragraph 5.5.2 The value in top right corner (Q4, 2016) is calculated as
the max of zero and exercise price less the strike price multiplied with the
technological risk, since BAVA cannot save any cost from not entering the
market, the value is zero: Max (0,0-175139)*81,6% = 0.
Figure 8: Step 5 - Binomial Tree 2 - Abandonment Value of PROSTVAC
STEP 5: BINOMIAL TREE 2 - VALUE OF ABANDONMENT OPTION
Phase 3
2013
2014
q1
q2
q3
q4
q1
q2
q3
0
0
0
0
0
0
Input
Yearly risk free rate
delta t
Risk neutral probability
Exercise price, abandon BLA
Tech risk phase 3
Tech risk BLA
Discount factor
Exercise price, abandon market
0
0
0
0
0
0
0
0
0
1,76%
0,25
0,4385
16,87
64,20%
81,60%
1,00441
0
0
0
0
0
0
0
q4
0
0
0
0
0
0
0
q1
0
0
0
0
0
0
0
0
Source: Own construction
44
q2
0
0
0
0
0
0
0
0
0
2015
q3
0
0
0
0
0
0
0
0
0
0
q4
0
0
0
0
0
0
0
0
0
0
0
q1
0
0
0
0
0
0
0
0
0
0
0
0
q2
0
0
0
0
0
0
0
0
0
0
0
0
0
BLA
2016
q3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
q4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Discounting the values from right to left reveals no real option value for
PROSTVAC at all. In the calculations, I have assumed that we use a European
option, which means, that the holder of the option can only exercise it at the
expiration date. This means that BAVA, we entering phase 3, already has made
the commitment to spend 150 USD million. In reality, however, BAVA may have
the option re-evaluate the project every year and decide on whether they should
continue or not. Even if this was the case, the real option would have no value
because the value of the underlying asset is always higher than the cost that
could have been saved.
The real option value of 0 was almost expected because PROSTVAC is in late
stage development. The only cost that could have been saved (assuming a
European option) was 16,87 DKK million by not entering BLA.
Binomial Tree 3: Management can use the above real option valuation to make
decisions: If the value of the option is higher than zero, the managers should
exercise the option because the exercise price would be higher than the strike
price i.e. the value of the cost savings would be greater than the value of the
underlying asset. From the below figure it can be seen that managers should
choose to hold the option in all circumstances.
Figure 9: Step 5 - Binomial Tree 3 - Management Actions for PROSTVAC
STEP 5: BINOMIAL TREE 3 - MANAGEMENT ACTIONS
q1
q2
2013
q3
q4
q1
q2
Phase 3
2014
q3
q4
q1
Source: Own Construction
45
q2
2015
q3
q4
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
q1
q2
BLA
2016
q3
q4
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
Expanded Net Present Value of PROSTVAC
The value of PROSTVAC from the traditional NPV was 956 DKK million. The
RO valuation revealed no extra value to the project and therefore the expanded
net present value for PROSTVAC is 956 DKK million.
7. 6 Step 6: Sensitivity Analysis
From above we see that the eNPV of PROSTVAC was estimated to 956 DKK
million and it was clear that the real options had no value. The above estimate,
however, does not take into consideration what will happen if one of the input
variables changes. A change in one variable can have a huge impact on the RO
value. In order to see which input variables have the most impact on the RO
value, the data for a tornado diagram can be seen appendix in 8. From the
diagram it is clear that none of the variables will have an impact on the RO
value if they change with +/-25%. Even if the volatility increases with 25%
(higher volatility, higher RO value) and the strike price decreases with 25% the
RO value will still be 0 (lower strike price, higher RO value). Therefore,
managers need not to worry about a 25% change in the variables. One could
choose to make a tornado diagram of +/-50% changes but it is quite unrealistic
that variables will change that much in four years.
8. Valuation of MVA-BN© RSV
Respiratory syncytial virus (RSV) is a virus that causes respiratory tract
infections in both children and adults. RSV is the main reason for serious
infections in children under the age of two. RSV is often the triggering cause of
asthmatic bronchitis (Jensen, 2007) In elderly people, respiratory syncytial virus
infections may cause severe cases of pneumonia. Each year 64 million people
suffer from respiratory syncytial virus infections and the infections causes
approximately 160.000 deaths (Bavarian Nordic, n.a.).
46
Bavarian Nordic is in the process of developing a new vaccine against
respiratory syncytial virus infections. The MVA-BN© RSV vaccine candidate is
based on the MVA-BN© platform, the earlier MVA-BN© vaccines (against
measles) has proved to be well tolerated in children of the age of six months to
five years old. The vaccine candidate is currently in the preclinical phase but an
IND is expected to be handed to the FDA at the beginning of 2013 and it is
expected that phase 1 development will start in 2013.
8. 1 Step 1 and 2: Base Variables & Strategic Analysis
The base variables calculated in step 1 for PROSTVAC will also be used as
base variables in the valuation of RSV, the argumentation for this was given in
paragraph 5.1. WACC was estimated to be 7,90% and the 10-year risk free rate
for a US Government bond was 1,76%. Since the development and sales of
PROSTVAC will take place in the US, the US government bond was used. It
may be argued that the risk free rate for RSV should be the Danish risk free rate
since the current activities regarding RSV takes place in Denmark. But BAVA
usually aim their products at the US market (get FDA approval) first and
therefore most of the future cash flow is expected to be in US dollars even
though the production may take place in Denmark.
Since the base variables are calculated, the next step in the valuation of RSV, is
to conduct an external analysis (the internal analysis for BAVA was conducted
in 7.2.2). In paragraph 7.2.1 it was argued that the external analysis should be
conducted based on factors of market attractiveness, the same argumentation
applies for the external analysis of RSV. The factors are: market potential,
customer characteristic and competitive environment.
Market Potential: There is a large unmet market for prophylactic vaccines
against respiratory syncytial virus: on average, children will at least get the
infection once before they turn 2 years old. Further, half of the children will
experience a recurrence of the infection. From the summary of a report called
Respiratory Syncytial Virus (RSV) Prophylactic – Pipeline Assessment and
Market Forecast to 2019 it is estimated that the global RSV prophylactic market
to be worth $798.8 million in 2011 and the Compound Annual Growth Rate is
47
3,3% for the next eight years. Therefore, the market for prophylactic RSV in
2019 is estimated to reach more than one billion USD (ASDReports, 2012).
Customer characteristics: Since the majority of infections happen in children,
the customers or decision makers for the purchase of RSV vaccines will be
hospitals and medical clinics. Marketing efforts should be aimed at these
smaller buyers. BAVA is not used to market their products to small decision
makers (compared to countries and governments as decision makers as is the
case for IMVAMUNE) and BAVA has to make a decision on whether to market
the RSV vaccine themselves or find a partner. The same rationale can be
applied to the distribution; currently BAVA only deliver large amounts of
IMVAMUNE to the US and Canada. When the customers for RSV vaccines are
hospitals and medical clinics there will be many deliveries and the requested
quantity of vaccines will be low. This will require BAVA to invest in distribution
systems or find a partner for it.
Competitive environment: Currently, there are no approved vaccines for the
treatment of RSV. The only drug that has been approved by the FDA is Synagis
(Palivizumab) which is for the prevention of Lower Respiratory Tract (LRT)
caused by RSV – i.e. it is only for children with a high risk of RSV. Synagis was
approved in 1998 and the patent expires in 2015. The costs for Synagis are
high (a shot of Synagis cost around $1000 in Denmark and a child requires one
shot every month in winter season (Medicin.dk, 2012)) and therefore most of
the treatment with Synagis will take place in high income countries.
There are a number of RSV development projects most of them (76% of the
total pipeline of 21) are in the preclinical and discovery stages. No RSV drugs
under development has reached phase 3 illustrating the difficulty of developing
such a vaccine.
There are two project in phase two development; RSV-604 developed by
Novartis and ALN-RSV01 developed by Alnylam (Olszewska & Openshaw,
2009). These may be future competitors but there is still a lot of insecurity about
the development of a drug for the prevention (not necessarily a vaccine) of
RSV. Due to the fact that many RSV compounds have been discontinued and
the difficulty of developing such a drug, it is reasonable to believe that BAVA
48
can acquire a large market share if their product receive FDA approval – the
competition is low and the profitability will be high.
In conclusion, it is very difficult to develop a RSV vaccine and many
companies have a history of discontinued projects. Currently, the competition
for being the firsts company with an FDA approved drug for the prevention of
RSV is fierce and an approval will first be relevant in more than five years (only
phase two development projects). If BAVA develops a FDA approved RSV
vaccine the potential market share will be large due to few competitors and a
growing market. An approved RSV vaccine can be identified as a STAR in the
Boston-Consulting-Group matrix (BCG matrix). Stars are characterized with
high market shares in industries with high growth rates. Stars can become
CASH COWS if the growth slows but the market share is obtained. If BAVA is
one of the first companies to develop an effective vaccine against RSV it is
possible that the vaccine will become a cash cow in the future.
8. 2 Step 3: Forecast
A large part of the input for the forecast is based on assumptions since it is very
difficult to know what the future will look like. As can be seen in appendix 9 the
forecasted period start in January 2013, BLA approval is expected in 2019 and
market launch is expected the following year. The RSV vaccine is based on the
MVA-BN© technology and the patents for this technology are given from 2004 to
now (Prospectus, 2011, p. 71).
From the forecast it can be seen that RSV will be in the market for ten years
(including patent extension). The short time in the market will have an impact on
the sale of RSV which will never reach 100%. These few years on the market
may scare a potential partner because it will lower their profits. Therefore, a
partner may pay BAVA a low royalty rate. On the other side, BAVA may apply
for new and more important patents related to RSV and thereby extending the
time in the market. The forecast ends in 2039 where RSV will have no sales.
The market size and growth rate was identified in the strategic analysis. The
market size was assumed to be high and in the forecast it is assumed to be
49
35%. The 35% illustrates a large market share but it also illustrates that there
will be other competitors in the market.
The royalty rate is set to 15% this implies that it is expected BAVA will find a
partner for the commercialization and distribution of RSV since these factors
have been identified as a weakness. The 15% may also illustrate that BAVA will
find a partner in later stages of development because the higher the risk, the
lower the royalty rate (see paragraph 3.3). Milestone payments are shown as an
entry in the forecast but no amount has been added, as with PROSTVAC
milestones are expected but will not be included.
The development of RSV is quite new and only limited information from BAVA is
available, therefore, the base variables identified in paragraph 3 will be applied
in the forecast. No costs are included in 2013 because it is assumed that BAVA
already has made the obligation to invest the money. The cumulative probability
of the RSV vaccine to get FDA approval is only 23,3%.
The probability weighted traditional NPV the 31st of December 2012 has been
estimated to -4,81 DKK million. From the negative NPV managers may decide
to discontinue the development of RSV. This decisions should, however, not be
made without an real option valuation for RSV. The value of real options may
increase the eNPV suggesting that development should continue.
8. 3 Step 4: Project Volatility
In order to identify the uncertain variables a tornado diagram has been
constructed (see appendix 11). A change in one variable with +/- 25% can have
a large impact on the static NPV. For instance, a 25% increase in the market
share will increase the NPV to 54,80 DKK million, whereas a 25% decrease in
the market share will give a negative NPV of -64,43 DKK million.
From these estimates it is clear that changes in the forecasted values can have
a huge impact on the NPV. In order to incorporate this uncertainty in the RO
valuation, management estimates with 95% confidence level have been
conducted and the implicit volatilities have been calculated (see appendix 12).
These implicit volatilities are the base for the project volatility.
50
The project volatility of RSV is expected to be higher than the volatility for
PROSTVAC because RSV is in early stage development. The implied
volatilities (based on lower estimates) are: market share 22,93%, market growth
34,29% and royalty rate 54,93%. The estimated implicit volatilities are quite high
compared to PROSTVAC and this illustrates the higher level of uncertainty.
After the implied volatilities have been calculated they are used as inputs for the
assumption variables in the Monte Carlo simulation. Again, assumption
variables follow a lognormal distribution and the return variable z is calculated.
R&D costs are not included in the simulation spreadsheet because this will give
negative z values in the simulation. The simulation spreadsheet can be seen in
appendix 13.
By running the simulation 50.000 times we get a project volatility of 51,71%
which is lower than the project volatility for PROSTVAC. The result of the
simulation can be seen in the figure below. Even though the implicit volatilities
were higher for RSV than PROSTVAC, PROSTVAC has a higher project
volatility, this is because more variables of uncertainty were included in
PROSTVAC.
Figure 10: Step 4 - Project Volatility for RSV
Source: Own Construction – Monte Carlo simulation
51
8. 4 Step 5: Real Option Valuation
It is possible to identify many options for the RSV project; finding a partner for
distribution and commercialization versus make investments and do it
themselves, stop and sell the patent rights, partnership for the clinical trials tests
etc.
As before, the option valuated here is abandonment options. There are a
number of abandonment options in the RSV project thus making it a sequential
compound option; the second option depends on the first option.
The options for RSV are:

Option 1: Abandon the RSV project before initiating phase 2 – saving the
cost of 212 DKK million.

Option 2: Abandon the RSV project before initiating phase 3 (given that
option 1 has not been exercised) – saving a total cost of 541 DKK million

Option 3: Abandon the RSV project before applying for BLA (given that
option 2 has not been exercised) – save 17 DKK million in BLA costs

An option 4 can be considered: abandon market after BLA approval 
since I have assumed that BAVA will find a partner there is in reality no
cost to be saved therefore the market phase should always be initialized.
If BAVA wants to undertake the production and distribution themselves it
is possible to extend this analysis with an option to finding a partner
versus do it themselves.
Binomial Tree 1: To estimate the underlying value of the asset one must
calculate the up and down movements. The inputs needed are: the project
volatility, value of the underlying asset and the sub periods. The larger the
number of sub periods the more accurate the binomial tree will be.
The up factor, u, is
𝑢 = 𝑒 𝜎√∆𝑡 = 𝑒 51,71%√0,25 = 1,295
The down factor can be calculated as 1/u which gives a down factor of 0,7722.
The value of the underlying asset was 1025 DKK million with no technological
52
risk. Now the first binomial tree can be constructed be multiplying the value of
the underlying asset with the up and down factors.
Figure 11: Step 5 - Binomial Tree 1 - Underlying Value of RSV
STEP 5: BINOMIAL TREE 1 - VALUE OF UNDERLYING ASSET
Phase 1
2013
q1
q2
q3
q4
q1
1025
1327
1719
2226
2883
791
1025
1327
1719
611
791
1025
472
611
364
Input
Value of underlying asset (s_0)
Duration of subperiod, years ΔT
Yearly volatility, σ
Factor up, u
factor down, d
2014
q2
3733
2226
1327
791
472
281
q3
4835
2883
1719
1025
611
364
217
q4
6262
3733
2226
1327
791
472
281
168
q1
8109
4835
2883
1719
1025
611
364
217
130
Phase 2
2015
q2
q3
10502
13600
6262
8109
3733
4835
2226
2883
1327
1719
791
1025
472
611
281
364
168
217
100
130
77
q4
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
q1
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
2016
q2
29539
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
36
1025
0,25
51,71%
1,2950509
0,7721704
q3
38255
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
27
q4
49542
29539
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
36
21
q1
64160
38255
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
27
16
Phase 3
2017
q2
q3
83090 107606
49542
64160
29539
38255
17613
22809
10502
13600
6262
8109
3733
4835
2226
2883
1327
1719
791
1025
472
611
281
364
168
217
100
130
60
77
36
46
21
27
13
16
10
BLA
2018
q4
139355
83090
49542
29539
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
36
21
13
8
q1
180472
107606
64160
38255
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
27
16
10
6
q2
233721
139355
83090
49542
29539
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
36
21
13
8
4
q3
302680
180472
107606
64160
38255
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
27
16
10
6
3
q4
391986
233721
139355
83090
49542
29539
17613
10502
6262
3733
2226
1327
791
472
281
168
100
60
36
21
13
8
4
3
q1
507642
302680
180472
107606
64160
38255
22809
13600
8109
4835
2883
1719
1025
611
364
217
130
77
46
27
16
10
6
3
2
2019
q2
q3
q4
657422 851395 1102600
391986 507642 657422
233721 302680 391986
139355 180472 233721
83090 107606 139355
49542
64160
83090
29539
38255
49542
17613
22809
29539
10502
13600
17613
6262
8109
10502
3733
4835
6262
2226
2883
3733
1327
1719
2226
791
1025
1327
472
611
791
281
364
472
168
217
281
100
130
168
60
77
100
36
46
60
21
27
36
13
16
21
8
10
13
4
6
8
3
3
4
2
2
3
1
2
1
Source: Own Construction
The last abandonment option expires just before market commercialization
after that there are no more options. When all the values of the underlying
asset have been calculated the value of the sequential abandonment option
can be estimated.
Binomial Tree 2: The inputs needed for the calculation of the abandonment
option are; the discount factor, risk neutral probability, exercise prices for the
different phases and the tech. risk for the different phase. First the risk neutral
probability is calculated
𝑒 𝑟𝑓∗ ∆𝑡 − 𝑑
𝑒 1,76%∗0,25 − 0,7722
𝑝=
=
= 0,4441
𝑢−𝑑
1,295 − 0,7722
The discount factor is calculated based on the risk free rate and sub periods.
The discount factor is e1,76%*0,25 = 1,00441
53
Figure 12: Step 5 - Binomial Tree 2 - Value of Sequential Abandonment Option for RSV
STEP 5: BINOMIAL TREE 2 - ABANDONMENT OPTION
Phase 1
2013
q1
q2
q3
q4
q1
40,06
25
13
6
2
53
34
19
9
68
46
28
86
62
106
Input
Yearly risk free rate
Delta t
Discount factor
Risk neutral probability
Exercise price, abandon BLA
Exercise price, abandon phase 3
Exercise price, abandon phase 2
Exercise price, abandon market
Tech risk BLA
Tech risk phase 3
Tech risk phase 2
Tech risk phase 1
Phase 2
2015
2014
q2
q3
0
3
14
39
80
128
q4
0
1
6
25
65
121
178
q1
0
0
1
10
37
88
149
203
q2
0
0
0
2
16
54
115
178
225
Phase 3
2016
q3
0
0
0
0
4
25
77
146
205
243
q4
0
0
0
0
0
7
40
107
178
227
257
q1
0
0
0
0
0
0
12
64
143
207
245
268
q2
0
0
0
0
0
0
0
21
98
181
230
260
277
1,76%
0,25
1,00
0,4441536
17
541
212
0
76,90%
64,20%
56,30%
83,70%
BLA
2017
q3
0
0
0
0
0
0
0
0
39
146
210
248
271
284
q4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
q1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
q2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
2018
q3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
4
q4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
2
5
q1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
6
q2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
4
7
2019
q3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
6
8
q4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
7
9
q1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
q2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
q3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
q4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Source: Own Construction
The values at the end of each phase have been calculated as the max of 0 and
the exercise price less the strike price multiplied with the technological risk. The
0 in the top right corner can be calculated as MAX (0, (0-1.102.600)*76,9%) = 0
here the exercise price is zero because BAVA cannot save any cost after the
BLA approval (a partner will pay for the commercialization). Moving to the left
and phase 3 – if BAVA experience bad phase 3 result they can choose not to
apply for BLA and thereby save approx. 17 DKK million. From the results above
it is clear that this option has almost no value because the savings are quite
small. If we, on the other hand, stop the RSV project in phase 2 we can save
the large phase 3 costs. At the end of phase 2, BAVA can choose to exercise
the option, it would be a good idea to exercise the option if they are in one of
the six lower nodes (at the end of phase two). The calculation for the 284 DKK
million follows: Max (0, (540-36)*56,30%) = 284. Since we are valuing a
European real option it can only be exercised at the end of the period, therefore
the values to the left of q2 in 2016 are not that relevant - they are only relevant
if their discounted value is larger than the value of the next abandonment
option. This is the case for the value in q2 2014 phase 1: The exercise price
less the strike price multiplied with the tech. risk is a negative number indicating
that the option (Option 1) has no value (calculations not shown). Even though
Option 1 has no value we still need to find the final value of the abandonment
option, this is done by discounting the values from the previous option. For
instance, in 2014 quarter 1 the value of 128 can be calculated as the
54
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
discounted value of the two previous up and down values:
((121*0,44415+178*(1-0,44415))/1,0041)*83,7% = 128
The RO value of the sequential abandonment option is estimated to 40,06 DKK
million. The value of the real option should be added to the static NPV in order
to include flexibility. RSV is an uncertain project and this uncertainty adds value
to the final value. In contrast, we saw the abandonment option for PROSTVAC
had no real option value, this was because the project was in a late stage
development and no significant cost could be saved. The extra value from the
option may change management decisions if they were uncertain about
whether to continue or discontinue the RSV project.
Binomial Tree 3: Managers can use the results from the second binomial tree
to make decisions; if the value of the abandonment option is positive then the
option should be exercised. From the third binomial tree it can be seen that the
abandonment option should be exercised in the six most pessimistic outcomes
when going from phase 2 to phase 3 and the option should also be exercised in
the four most pessimistic outcomes of phase 3.
Figure 13: Step 5 - Binomial Tree 3 - Management Actions for RSV
STEP 5: BINOMIAL TREE 3 - MANAGEMENT ACTIONS FOR RSV
Phase 1
2013
q1
q2
q3
q4
q1
Phase 2
2015
2014
q2
q3
hold
hold
hold
hold
hold
hold
q4
q1
q2
Phase 3
q3
q4
q1
2016
q2
hold
hold
hold
hold
hold
hold
hold
hold
abandon
abandon
abandon
abandon
abandon
abandon
Source: Own Construction
55
BLA
2017
q3
q4
q1
q2
2018
q3
q4
q1
q2
q3
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
abandon
abandon
abandon
abandon
2019
q4
q1
q2
q3
q4
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
hold
Expanded net present value of RSV
The value from the traditional NPV with technological uncertainties was -4,81
DKK million and the value of flexibility from the abandonment options increases
this value with 40,06 DKK million. The extended net present value (eNPV) for
RSV the 31st of December 2012 was -4,81 + 40,06 = 35,25 DKK million.
If the managers at BAVA had their doubts about whether to continue the
development of RSV or not, the extra RO value may change the no-go decision
to a go decision. The value of flexibility adds significant value to the RSV
project.
8. 5 Step 6: Sensitivity Analysis
Compared to PROSTVAC, RSV does have a RO value, the value is not large
but it adds extra value to the project.
Since the development of RSV will take another 7 years, managers may be very
interested in a sensitivity analysis. The analysis will tell managers what will
happen to the RO value if one of the variables changes. Managers should try to
hedge against negative changes and improve the possibility of positive
changes. In order to identify which variables have the largest impact on the RO
value, a tornado diagram has been constructed (see below figure).
From the tornado diagram, it can be seen that there are three variables which
have a large effect on the RO value. These variables are phase 3 costs, project
volatility and the underlying value of the asset (strike price). A +/- 25% change
in the volatility will increase uncertainty and thereby the RO value. A 25%
increase in the volatility will increase the RO value to 63,56 DKK million. A limit
to the sensitivity analysis is that it does not show where the change in a
variables stems from. A change in the volatility may come from a change in the
market growth in the static NPV (a scenario analysis could have solved this
problem). The technological risk is not relevant for phase 3 and BLA because
the options corresponding to the risk have no value, whereas the risk for phase
2 can change the RO value.
56
Figure 14: Tornado Diagram over Input Variables for RO Calculation
Source: Own construction
Based on the above, it is clear that there are 3 drivers for the RO value. In order
to see how two of these variables impact on each other and the RO value, a two
factor sensitivity analysis has been constructed. The two variables used in the
analysis are the volatility and the strike price. It is expected that the highest RO
value will come from a +25 increase in volatility and a 25% decrease in the
strike price. From the figure below it is clear that this is the case and the RO
value has almost doubled now the RO value is 80,16 DKK million.
The bold numbers in the figure illustrate that the RO values are based on the
value of two options. Before, only option 2 had a value. Now when the volatility
increases and the strike price decrease, option 1, begin to have RO value.
Therefore the RO value of 80,16 DKK million are based on the value of option 1
(3,01 DKK million) and option 2 (77,15 DKK million).
In the upper left corner the lowest RO values are shown, these values are
based on a low volatility and a high strike price. The lowest RO value, from
changes of +/- 25% in the two variables, is 11,47 DKK million. Even though the
RO value is low, it still add extra value to the project and the eNPV will still be
positive, indicating that mangers should continue the project.
57
Figure 15: Step 6 - Sensitivity Analysis: Strike Price and Project Volatility
Two-factor model: Volatility & Strike price (percentage change)
-25%
-20%
-15%
-10%
-5%
38,78%
41,37%
43,95%
46,54%
49,12%
11,47
14,74
18,02
21,3
24,57
12,94
16,16
19,38
22,61
25,83
14,41
17,57
20,75
23,92
27,09
15,88
18,99
22,11
25,23
28,43
17,35
20,41
23,47
26,99
31,88
18,82
21,82
25,75
30,55
35,32
20,28
24,7
29,41
34,1
38,77
23,86
48,47
33,08
37,66
42,21
27,74
32,25
36,74
41,21
45,66
31,63
36,02
40,41
44,77
49,1
35,51
39,8
44,07
48,32
52,55
0
51,71%
27,84
29,04
30,25
33,4
36,73
40,06
43,4
46,73
50,07
53,4
56,74
5%
54,30%
31,09
32,24
35,09
38,32
41,54
44,77
48
51,22
54,45
57,67
61,54
10%
56,88%
34,33
36,96
40,08
43,2
46,31
49,43
52,55
55,67
58,87
62,56
66,25
15%
59,47%
38,99
42
45,01
48,03
51,04
54,05
57,06
60,24
63,8
67,37
70,93
20%
62,05%
44,08
46,99
49,9
52,8
55,71
58,62
61,8
65,24
68,68
72,12
75,57
25%
64,64%
49,11
51,92
54,72
57,52
60,33
63,56
66,88
70,2
73,52
76,84
80,16
Volatility/S_0
1281,101
1229,857
1178,613
1127,369
1076,125
1025
973,6366
922,3926
871,1486
819,9045
768,6605
25%
20%
15%
10%
5%
0
-5%
-10%
-15%
-20%
-25%
Source: Own Construction
9. Share Price
The eNPV values of PROSTVAC and RSV revealed an important difference in
the two projects; PROSTVAC had no RO value whereas RSV had. This
difference stems largely from the fact that RSV can be discontinued before the
initiation of phase 3 wherefore a significant amount can be saved.
The eNPV value of PROSTVAC was estimated to 956 DKK million. Since it is
assumed that PROSTVAC constitutes 45% of the total share price (appendix 2),
the value of PROSTVAC is 36,64 DKK per share. The calculation: PROSTAVC
eNPV divided by number of shares (956 DKK million/26,094361 million shares).
The total share price for BAVA, based on PROSTVAC will then be 81,41
DKK/share which is quite close to Jyske Bank’s target share price of 80
DKK/Share.
Many investment companies do not value projects in early stage development
because the cumulative probability of success is very low. Despite the low
probability of success, RSV still had a positive eNPV which should increase
BAVAs share price. RSV had eNPV of 35,25 DKK million and that should
increase the share price with 1,35 DKK/share. If investor acknowledge this extra
value, BAVAs share price should be 82,76 DKK/share, if not, then the share
price based solely on PROSTVAC was 81,41 DKK/share.
On the 31st of December 2012, BAVAs shares were selling for 49,80
DKK/share, this is a large difference between the actual share price and the
58
estimated share price. One reason for this difference may be that investors are
risk averse which means that investors prefer safe investments.
10. Conclusion
In many companies, the traditional NPV approach is often applied as a decision
making tool. However, the traditional NPV approach fails to incorporate the
value of uncertainty wherefore it is suggested to apply the eNPV as a decision
making tool. This tool, can with advantage, be applied for projects that go
through different phases of development.
In order to increase the use of real options as a part of the eNPV, a six-step
model is developed and tested on two specific projects from Bavarian Nordic.
The first three steps in the model are concerned with the inputs needed for the
traditional NPV calculation. The last three steps are concerned with the
calculation of real options.
The selected cases were those of PROSTAVC and RSV, two vaccine
candidates developed by Bavarian Nordic. The vaccine candidates were
selected because they are in different phases of development.
PROSTVAC, a vaccine treatment for late stage prostate cancer, showed
promising prospects. The market for PROSTAVC is large and PROSTVAC is a
superior product compared to its competitors. The probability of entering the
market is high because it is in late phase development. The static NPV was
estimated to 956 DKK million. Since PROSTVAC is yet to be approved by the
FDA, uncertainties are still relevant. The project volatility was estimated to
55,8% based on management estimates. The high project volatility did however
not influence the real option value, which was 0. The low RO value was
expected because PROSTVAC is quite close to market approval and no
significant cost can be saved. The eNPV for PROSTVAC was therefore the
same as the traditional NPV.
59
BAVA is developing a vaccine treatment against respiratory syncytial virus, the
vaccine is in early phase development and the project is very uncertain. Not a
lot of information is available on RSV wherefore the generic industry variables
form the basis for the NPV calculation. If RSV receives FDA approval, an
attractive market with no competitors is waiting. The future development of RSV
depends on the financial resources of BAVA. BAVA lacks financial resources
and BAVA is seeking partners for both PROSTVAC and RSV, but so far no
partner agreement has been agreed upon. The consequence of this, might be
that the development of RSV will be postponed.
The NPV for RSV was -4,81 DKK million suggesting that managers should
discontinue the development. The value of the sequential abandonment option
was 40,06 DKK million and the eNPV, from the six-step approach, was
therefore 35,25 DKK million suggesting that managers should, in fact, continue
the development of RSV. From the binomial tree on management actions it can
be seen that in some circumstances before phase 3 development, it could be
beneficial to exercise RSVs abandonment option. RSVs higher RO adds value
to the share price.
The share price based on the eNPVs of PROSTVAC and RSV is estimated to
82,76 DKK/share the 31st of December 2012. From this estimate PROSTVAC
contributes with 36,64 DKK/share and RSV contributes with 1,35 DKK/share.
This estimate is almost 30 DKK higher than what BAVAs shares actually were
traded at on the 31st of December 2012, this difference may be a result of
investors’ different preferences towards risk.
60
BIBLIOGRAPHY
American Cancer Society. (2012). What are the Key Statistics about Prostate
Cancer? Retrieved 30/10, 2012, from
http://www.cancer.org/cancer/prostatecancer/detailedguide/prostatecancer-key-statistics
Arnold, Tom, & Crack, Timothy Falcon. (2004). Using the WACC to Value Real
Options. Financial Analysts Journal, 60(6), 78-82.
ASDReports. (2012). The Respiratory Syncytial Virus Prophylactic Market is
Expected to Show Static Growth during the Forecast Period (summary).
Retrieved 14/1, 2013, from
https://www.asdreports.com/news.asp?pr_id=403
Baghdadi, Ramsey. (2010). Dendreon vs CMS: Why the Provenge Coverage
Controversy Is Bigger Than Just One Product. Retrieved 17/11, 2012,
from http://www.cancernetwork.com/display/article/10165/1673614
Baker, H. Kent, Dutta, Shantanu, & Saadi, Samir. (2011). Management Views
on Real Options in Capital Budgeting. Journal of Applied Finance, 21(1),
18-29.
Bavarian Nordic. (2007). Bavarian Nordic og Acambis indgår forlig i alle
ressager om MVA. Retrieved 16/11, 2012, from http://da.web.bavariannordic.com/investor/announcements/2007-27.aspx?langChanged=true
Bavarian Nordic. (2011a). Bavarian Nordic Annual Report Kvistgaard, Denmark.
Bavarian Nordic. (2011b). Prospekt (Fortegningsemission 2011).
Bavarian Nordic. (2012a). About Us. Retrieved 10/11, 2012, from
http://www.bavarian-nordic.com/about.aspx
Bavarian Nordic. (2012b). Working at Bavarian Nordic. Retrieved 16/11, 2012,
from http://www.bavarian-nordic.com/join-us/working-at-bavariannordic.aspx
Bavarian Nordic. (n.a.). MVA-BN© RSV. Retrieved 15/1, 2013, from
http://www.bavarian-nordic.com/pipeline/mva-bn-rsv.aspx
Beasley, Deena. (2012). Dendreon CEO: rival prostate drugs to boost market.
Retrieved 25/1, 2013, from http://www.reuters.com/article/2012/03/13/usdendreon-ceo-idUSBRE82C05T20120313
61
Berk, Jonathan; DeMarzo, Peter. (2011). Option Valuation; Real Options
Corporate Finance (2nd ed., pp. 704-763): Pearson Education.
Block, Stanley. (2007). Are "Real Options" Actually Used in the Real World?
Engineering Economist, 52(3), 255-267. doi:
10.1080/00137910701503910
Bogdan, Boris; Villiger, Ralph. (2008). Valuation in life sciences (pp. 334).
Copeland, Tom; Antikarov, Vladimir. (2003). Real Options: A Practitioner's
Guide: Penguin Group.
Dendreon. (2011). Annual Report.
DiMasi, Joseph A., & Grabowski, Henry G. (2007). The cost of
biopharmaceutical R&D: is biotech different? Managerial & Decision
Economics, 28(4/5), 469-479.
DiMasi, Joseph A., Grabowski, Henry G., & Vernon, John. (2004). R&D Costs
and Returns by Therapeutic Category. Drug Information Journal, 38(3),
211-223.
FDA. (2009). Small Business Assistance: Frequently Asked Question on the
Patent Term Restoration Program. Retrieved 28/1, 2013, from
http://www.fda.gov/drugs/developmentapprovalprocess/smallbusinessas
sistance/ucm069959.htm
Ferrara, J. Susan. (2011). Biotechs vs. Pharmaceutical Companies: What's the
Difference? , from
http://www.valueline.com/Tools/Educational_Articles/Stocks_Detail.aspx
?id=10278
Finch, Sharon. (2001). Royalty rates: Current issues and trends. Journal of
Commercial Biotechnology, 7(3), 224.
Forbes. (2012). A Dendreon Post Mortem? Maybe Not Yet, But... Retrieved
28/10, 2012, from
http://www.forbes.com/sites/edsilverman/2012/08/01/a-dendreon-postmortem-maybe-not-yet-but/
Frovst, Tom. (2012). Banker giver Asger Aamund livline året ud. Retrieved
16/11, 2012, from
http://borsen.dk/nyheder/avisen/artikel/11/24821/artikel.html
62
Health, U.S. National Institute of. (2012). A Phase 3 Efficacy Study of a
Recombinant Vaccina Virus Vaccine to Treat Metastatic Prostate
Cancer.
Investor Presentation. (2011). Bavarian Nordic Investor Præsentation 14/0.
Retrieved 23/1, 2013, from
http://www.proinvestor.com/boards/46511/Bavarian-Nordic-InvestorPraesentation-140
Jefferies. (2012). Bavarian Nordic 1Q12 immaterial & ASCO update likely
minor; Quartlery margin trend key.
Jensen, Mads Radmer. (2007). RSV - Respiratorisk Syncytial Virus. Retrieved
15/1, 2013, from http://www.sundhedsguiden.dk/da/temaer/alletemaer/almene-infektioner-ogparasitsygdomme/infektionssygdomme/rsv---respiratorisk-syncytial-virus/
Jyske Bank. (2010). PROSTVAC is worth DKK 102 per share.
Kræftens Bekæmpelse. (2012). Statistik om prostatakræft. Retrieved 29/10,
2012, from
http://www.cancer.dk/Hjaelp+viden/kraeftformer/kraeftsygdomme/prostat
a/statistik+prostatakraeft/
Lynch, Richard. (2009). Analyzing Resources and Capabilities Strategic
Management (Fifth edition ed.): Prentice Hall.
McKinsey, Inc., Company, Koller, Tim, Goedhart, Marc, & Wessels, David.
(2010). Valuation : Measuring and Managing the Value of Companies
Retrieved from http://asb.eblib.com/patron/FullRecord.aspx?p=554974
Medicin.dk. (2012). Synagis. Retrieved 14/1, 2013, from
http://min.medicin.dk/Medicin/Praeparater/2656
Olszewska, W., & Openshaw, P. (2009). Emerging drugs for respiratory
syncytial virus infection. Expert Opin Emerg Drugs, 14(2), 207-217. doi:
10.1517/14728210902946399
Pollack, Andrew. (2012). New Drug For Prostate Cancer Gets F.D.A. Nod.
Retrieved 22/1, 2013, from
http://www.nytimes.com/2012/09/01/business/fda-approves-prostatecancer-drug.html?_r=0
Prospectus. (2011). Bavarian Nordic Prospectus 2011
63
Trigeorgis, Lenos. (2005). MAKING USE OF REAL OPTIONS SIMPLE: AN
OVERVIEW AND APPLICATIONS IN FLEXIBLE/MODULAR DECISION
MAKING. Engineering Economist, 50(1), 25-53. doi:
10.1080/00137910590917026
U.S. Department of the Treasury. (2012). Retrieved 26/10-2012, from
http://www.treasury.gov/resource-center/data-chart-center/interestrates/Pages/TextView.aspx?data=yield
Zytiga. (2012). About ZYTIGA© Retrieved 28/10, 2012, from
http://www.zytiga.com/about_zytiga/
64
APPENDIX
Appendix 1: Abbreviations
Appendix 2: Mail Correspondence with Frank Andersen
Appendix 3: PROSTVAC – Static NPV
Appendix 4: PROSTVAC – NPV no tech. risk and R&D cost
Appendix 5: PROSTVAC – Tornado diagram
Appendix 6: PROSTVAC – Management estimates
Appendix 7: PROSTVAC – Spreadsheet for Monte Carlo simulation and project
volatility
Appendix 8: PROSTVAC – Tornado diagram and sensitivity analysis
Appendix 9: RSV – Static NPV
Appendix 10: RSV – NPV no tech. risk and no R&D cost
Appendix 11: RSV – Tornado diagram
Appendix 12: RSV – Management estimates
Appendix 13: RSV – Spreadsheet for Monte Carlo simulation
Appendix 1: Abbreviations
BAVA:
Bavarian Nordic A/S
BCG:
Boston Consulting Group
BLA:
Biologic License Application
CAPM:
Capital Asset Pricing Model
DCF:
Discounted Cash Flow
eNPV:
Expanded Net Present Value
FDA:
Food and Drug Administration (USA)
EMEA:
European Medicine Controls Agency
IND:
Investigational New Drug
IP:
Intellectual Property
LRT:
Lower Respiratory Tract
NCI:
National Cancer Institute
NPV:
Net Present Value
MAD:
Market Asset Disclaimer
MVA-BN
Modified Vaccina Ankara – Bavarian Nordic
PEST:
Analysis
Political, Economic, Socio-cultural and Technological
PV:
Present Value
R&D:
Research and Development
RO:
Real Options
ROA:
Real Options Analysis
RSV:
Respiratory Syncytial Virus
SWOT:
Strengths, Weakness, Opportunities, Threats
WACC:
Weighted Average Cost of Capital
Appendix 2: Mail correspondence with Frank Andersen
Hej Anne
Vores kursmål er vægtet af dels vores fair DCF værdi og dels et nyhedsrelateret
element. Derfor er vores kursmål lavere end fair DCF værdi.
Vi estimerer, at Prostvac udgør 45% af værdien.
Venlig hilsen
Frank Hørning Andersen
Senior aktieanalytiker
Analyse
T +45 89 89 70 31
Vestergade 8 - 16 | 8600 Silkeborg
CVR-nr. 17 61 66 17
Tag din økonomi med på farten - hent Jyske Mobilbank
Fra: anne nielsen [mailto:annenielsen12@yahoo.dk]
Sendt: 11. december 2012 11:06
Til: Frank Hørning Andersen
Emne: SV: Bavarian Nordic - info til speciale?
Hej Frank,
Mange tak for svar! Jeg har lige et tillægsspørgsmål jeg også håber at du vil
svare på:
Jeres kursmål for Bavarian Nordic er 80kr - hvor mange procent vil du mene
Prostvac udgør af dette kursmål? (fra uofficielle kilder har jeg hørt at Prostvac
udgør omkring 60% af aktiekursen, men synes det lyder lidt højt)
Venlig hilsen
Anne
Fra: Frank Hørning Andersen <fha@jyskebank.dk>
Til: 'anne nielsen' <annenielsen12@yahoo.dk>
Sendt: 14:16 mandag den 10. december 2012
Emne: SV: Bavarian Nordic - info til speciale?
Hej Anne
Fair DCF værdi på DKK 122 per aktie
Værdi Prostvac DKK 55 per aktie
Værdi IMVAMUNE DKK 50 per aktie
Net cash DKK 17 per aktie
Venlig hilsen
Frank Hørning Andersen
Senior aktieanalytiker
Analyse
T +45 89 89 70 31
Vestergade 8 - 16 | 8600 Silkeborg
CVR-nr. 17 61 66 17
Tag din økonomi med på farten - hent Jyske Mobilbank
Fra: anne nielsen [mailto:annenielsen12@yahoo.dk]
Sendt: 5. december 2012 19:38
Til: Frank Hørning Andersen
Emne: Bavarian Nordic - info til speciale?
Kære Frank,
Mit navn er Anne og til daglig studere jeg Cand. Merc. in Finance &
International Business på Handelshøjskolen i Aarhus. Jeg er i gang med at
skrive speciale om real options og Bavarian Nordic. Mere konkret laver jeg en
real options analyse af et par af deres assets. I den forbindelse vil jeg høre om
du kan komme med et estimat af hvor meget PROSTVAC og (evt. MVA-BN
RSV) udgør af en samlet værdiansættelse for Bavarian Nordic?
Såfremt det ønskes kan estimaterne holdes fortrolige.
Jeg ser frem til dit svar og hvis du har brug for mere information eller andet, må
du endelig skrive tilbage.
Med venlig hilsen
Anne Nielsen
Tlf: 28 49 83 58
E-mail: annenielsen12@yahoo.dk
Appendix 3: PROSTVAC – Static NPV
STEP 3: FORECAST OF PROSTVAC
Input variables
WACC
Tax rate
1US$ equals (exchange rate 31/12-2012)
Phase 3 costs USD million (for 5 years)
BLA cost USD million
DKK
USD
USD
7,90%
25%
5,62
150,00 DKK
3,00 DKK
t=time
Year
Phase
0
2012
843,73
16,87
1
2013
2
2014
3
3
2015
4
2016
BLA
5
2017
6
2018
7
2019
8
2020
9
2021
10
11
2022
2023
MARKET
12
2024
13
2025
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
22
2033
2034
MARKET (no patent)
23
2035
24
2036
25
2037
26
2038
Probability of succes
Culmulative probability
100,00%
100,00%
100%
100,00%
100%
100,00%
64,20%
64,20%
81,60%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
Yearly number of people diagnosed with prostate cancer
Growth (2%)
People suitable for treatment (13,97%)
780.000
2%
14%
795.600
2%
14%
811.512
2%
14%
827.742
2%
14%
844.297
2%
14%
861.183
2%
14%
878.407
2%
14%
895.975
2%
14%
913.894
2%
14%
932.172
2%
14%
950.816
2%
14%
969.832
2%
14%
989.229
2%
14%
1.009.013
2%
14%
1.029.193
2%
14%
1.049.777
2%
14%
1.070.773
2%
14%
1.092.188
2%
14%
1.114.032
2%
14%
1.136.313
2%
14%
1.159.039
2%
14%
1.182.220
2%
14%
1.205.864
2%
14%
1.229.981
2%
14%
1.254.581
2%
14%
1.279.673
2%
14%
0
0
0
0
35%
5%
35%
19%
35%
36%
35%
51%
35%
64%
35%
75%
35%
84%
35%
91%
35%
96%
35%
99%
35%
100%
35%
100%
35%
99%
35%
97%
35%
95%
35%
72%
35%
53%
35%
37%
35%
24%
35%
13%
35%
6%
35%
1%
0,08
2%
0,08
2%
0,08
2%
0,08
2%
0,08
2%
0,09
2%
0,09
2%
0,09
2%
0,09
2%
0,09
2%
0,10
2%
0,10
2%
0,10
2%
0,10
2%
0,10
2%
0,11
2%
0,11
2%
0,11
2%
0,11
2%
0,11
2%
0,12
2%
0,12
2%
BAVA market share
Penetration
Price (DKK million)
Price inflation (%)
Revenue (DKK million)
161
638
1.257
1.853
2.420
2.950
3.438
3.875
4.253
4.563
4.795
4.989
5.138
5.238
5.337
4.208
3.223
2.341
1.580
890
427
74
Royalty share % of revenue
Royalty (DKK million)
Cost (phase 3 and BLA) (DKK million)
15%
24
15%
96
15%
189
15%
278
15%
363
15%
443
15%
516
15%
581
15%
638
15%
684
15%
719
15%
748
15%
771
15%
786
15%
801
15%
631
15%
483
15%
351
15%
237
15%
134
15%
64
15%
11
0
202
202
17
EBIT (DKK million)
0
-202
-202
-17
24
96
189
278
363
443
516
581
638
684
719
748
771
786
801
631
483
351
237
134
64
11
Tax (25%) (DKK million)
0
-51
-51
-4
6
24
47
69
91
111
129
145
159
171
180
187
193
196
200
158
121
88
59
33
16
3
NOPLAT (DKK million)
NOPLAT probability weighted (DKK million)
0
0
-152
-152
-152
-152
-13
-8
18
10
72
38
141
74
208
109
272
143
332
174
387
203
436
228
478
251
513
269
539
283
561
294
578
303
589
309
600
315
473
248
363
190
263
138
178
93
100
52
48
25
8
4
0
-130
-121
-6
7
24
44
59
72
81
88
92
93
93
90
87
83
79
74
54
38
26
16
8
4
1
Present value probability weigthed (DKK million)
Probability weigthed NPV p.31/12-2012 (DKK million)
956
Appendix 4: PROSTVAC – NPV no tech. risk and R&D cost
Input variables
WACC
Tax rate
1US$ equals (exchange rate 31/12-2012)
Phase 3 costs USD million (for 5 years)
BLA cost USD million
t=time
Year
Phase
7,90%
25%
DKK
5,62
USD 150,00 DKK 843,73
USD
3,00 DKK 16,87
0
2012
Yearly number of people diagnosed with prostate cancer
Growth (2%)
People suitable for treatment (10%)
BAVA market share
Penetration
1
2013
2
2014
3
3
2015
4
2016
BLA
5
2017
EBIT (DKK million)
Tax (25%) (DKK million)
NOPLAT (DKK million)
Present value (DKK million)
NPV 31/12-2012 (DKK million)
2.666
8
2020
9
2021
10
2022
11
2023
MARKET
12
2024
13
2025
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
22
2033
2034
MARKET (no patent)
23
2035
24
2036
25
2037
26
2038
795.600
2%
14%
811.512
2%
14%
827.742
2%
14%
844.297
2%
14%
861.183
2%
14%
878.407
2%
14%
895.975
2%
14%
913.894
2%
14%
932.172
2%
14%
950.816
2%
14%
969.832
2%
14%
989.229
2%
14%
1.009.013
2%
14%
1.029.193
2%
14%
1.049.777
2%
14%
1.070.773
2%
14%
1.092.188
2%
14%
1.114.032
2%
14%
1.136.313
2%
14%
1.159.039
2%
14%
1.182.220
2%
14%
1.205.864
2%
14%
1.229.981
2%
14%
1.254.581
2%
14%
1.279.673
2%
14%
0
0
0
0
35%
5%
35%
19%
35%
36%
35%
51%
35%
64%
35%
75%
35%
84%
35%
91%
35%
96%
35%
99%
35%
100%
35%
100%
35%
99%
35%
97%
35%
95%
35%
72%
35%
53%
35%
37%
35%
24%
35%
13%
35%
6%
35%
1%
0,09
2%
0,09
2%
0,09
2%
0,10
2%
0,10
2%
0,10
2%
0,10
2%
0,10
2%
0,11
2%
0,11
2%
0,11
2%
0,11
2%
0,11
2%
0,12
2%
0,12
2%
0,12
2%
0,12
2%
0,13
2%
0,13
2%
0,13
2%
0,13
2%
0,14
2%
0
Royalty share % of revenue
Royalty (DKK million)
7
2019
780.000
2%
14%
Price per treatment (DKK million)
Price inflation (%)
Revenue (DKK million)
6
2018
0
0
0
186
734
1.448
2.134
2.786
3.397
3.958
4.461
4.896
5.253
5.521
5.744
5.916
6.031
6.145
4.846
3.711
2.695
1.819
1.025
492
85
15%
28
15%
110
15%
217
15%
320
15%
418
15%
510
15%
594
15%
669
15%
734
15%
788
15%
828
15%
862
15%
887
15%
905
15%
922
15%
727
15%
557
15%
404
15%
273
15%
154
15%
74
15%
13
28
110
217
320
418
510
594
669
734
788
828
862
887
905
922
727
557
404
273
154
74
13
7
28
54
80
104
127
148
167
184
197
207
215
222
226
230
182
139
101
68
38
18
3
21
83
163
240
313
382
445
502
551
591
621
646
666
678
691
545
417
303
205
115
55
10
14
52
96
131
158
179
193
202
205
204
199
191
183
173
163
119
85
57
36
19
8
1
Appendix 5: PROSTVAC – Tornado diagram
PROSTVAC; TORNADO DIAGRAM - UNCERTAIN VARIABLES
Input
PV -25% Base case PV 25%
Growth
880
956
1.036
BAVA Market Share
652
956
1.259
Price
652
956
1.259
Royalty
652
956
1.259
People Suitable for Treatment
652
956
1.259
Appendix 6: PROSTVAC – Management Estimates
0
2012
MANAGEMENT ESTIMATES FOR UNCERTAIN VARIABLES
1
2013
2
2014
3
2015
4
2016
5
2017
6
2018
7
2019
8
2020
9
2021
10
2022
11
2023
12
2024
13
2025
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
2033
22
2034
23
2035
24
2036
25
2037
26
2038
780.000
795.600
408.000
811.512
416.160
827.742
424.483
844.297
432.973
861.183
441.632
878.407
450.465
895.975
459.474
913.894
468.664
932.172
478.037
950.816
487.598
969.832
497.350
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
13,97%
5,00%
15%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
15%
5%
0,09
0,09
0,05
0,09
0,05
0,10
0,05
0,10
0,05
0,10
0,05
0,10
0,05
0,10
0,05
0,11
0,05
0,11
0,05
0,11
0,05
0,11
0,06
0,11
0,06
0,12
0,06
0,12
0,06
0,12
0,06
0,12
0,06
0,13
0,06
0,13
0,06
0,13
0,07
0,13
0,07
0,14
0,07
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
# of people with prostate cancer
Input
Growth (%)
Base Case
Lower estimate (95% confidence)
2%
780.000
400.000
Data
Base case
Lower estimate
Result
Volatility based on lower estimate (%)
Absolute volatility
989.229 1.009.013 1.029.193 1.049.777 1.070.773 1.092.188 1.114.032 1.136.313 1.159.039 1.182.220 1.205.864 1.229.981 1.254.581 1.279.673
507.297
517.443
527.792
538.347
549.114
560.097
571.298
582.724
594.379
606.267
618.392
630.760
643.375
656.242
8,73%
68.132
People suitable for treatment
Input
Growth (%)
Base case
Lower estimate
0%
13,97%
5,00%
Data
Base case
Lower estimate
13,97%
Result
Volatility based on lower estimate (%)
Absolute volatility
10,08%
1,41%
Royalty
Input
Growth (%)
Base case
Lower estimate
0,00%
15%
5%
Data
Base case
Lower estimate
15%
5%
Result
Volatility based on lower estimate (%)
Absolute volatility
54,93%
8,24%
Price
Input
Growth (%)
Base case
Lower estimate
2%
0,09
0,045
Data
Base Case
Lower estimate
Result
Volatility based on lower estimate (%)
Absolute volatility
9,77%
0,0088
Market share
Input
Growth (%)
Base case
Lower estimate
Data
Base case
Lower estimate
Result
Volatility based on lower estimate
Absolute volatility
0
35%
5%
35%
19,08%
0,0668
35%
5%
35%
5%
35%
5%
Appendix 7: PROSTVAC – Spreadsheet for Monte Carlo Simulation and Project Volatility
Input variables
WACC
Tax rate
1US$ equals (exchange rate 31/12-2012)
Phase 3 costs USD million (for 5 years)
BLA cost USD million
t=time
Year
Phase
DKK
USD
USD
7,90%
25%
5,62
150,00 DKK
3,00 DKK
0
2012
Probability of succes
Culmulative probability
Yearly number of people diagnosed with prostate cancer
Growth (2%)
People suitable for treatment (13,97%)
BAVA market share
Penetration
843,73
16,87
1
2013
2
2014
3
3
2015
4
2016
BLA
5
2017
6
2018
7
2019
8
2020
9
2021
10
2022
11
2023
MARKET
12
2024
13
2025
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
22
2033
2034
MARKET (no patent)
23
2035
24
2036
25
2037
26
2038
100%
100%
100%
100%
100%
100%
64,20%
64,20%
81,60%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
100%
52,39%
780.000
2%
14%
795.600
2%
14%
811.512
2%
14%
827.742
2%
14%
944.297
2%
14%
861.183
2%
14%
878.407
2%
14%
895.975
2%
14%
913.894
2%
14%
932.172
2%
14%
950.816
2%
14%
969.832
2%
14%
989.229
2%
14%
1.009.013
2%
14%
1.029.193
2%
14%
1.049.777
2%
14%
1.070.773
2%
14%
1.092.188
2%
14%
1.114.032
2%
14%
1.136.313
2%
14%
1.159.039
2%
14%
1.182.220
2%
14%
1.205.864
2%
14%
1.229.981
2%
14%
1.254.581
2%
14%
1.279.673
2%
14%
0
0
0
0
35%
5%
35%
19%
35%
36%
35%
51%
35%
64%
35%
75%
35%
84%
35%
91%
35%
96%
35%
99%
35%
100%
35%
100%
35%
99%
35%
97%
35%
95%
35%
72%
35%
53%
35%
37%
35%
24%
35%
13%
35%
6%
35%
1%
0,1185
2%
Price (DKK million)
Price inflation (%)
0,0782
2%
0,0797
2%
0,0813
2%
0,0829
2%
0,0846
2%
0,0863
2%
0,088
2%
0,0898
2%
0,0916
2%
0,0934
2%
0,0953
2%
0,0972
2%
0,0991
2%
0,1011
2%
0,1031
2%
0,1052
2%
0,1073
2%
0,1094
2%
0,116
2%
0,1139
2%
0,1161
2%
Revenue (DKK million)
161
713
1.257
1.852
2.419
2.950
3.437
3.875
4.253
4.562
4.796
4.989
5.137
5.237
5.335
4.208
3.223
2.340
1.641
890
427
74
Royalty share % of revenue
Royalty (DKK million)
Cost (phase 3 and BLA) (DKK million)
15%
24
15%
107
15%
189
15%
278
15%
363
15%
443
15%
515
15%
581
15%
638
15%
684
15%
719
15%
748
15%
770
15%
786
15%
800
15%
631
15%
483
15%
351
15%
246
15%
134
15%
64
15%
11
0
202
202
17
EBIT (DKK million)
0
-202
-202
-17
24
107
189
278
363
443
515
581
638
684
719
748
770
786
800
631
483
351
246
134
64
11
Tax (25%) (DKK million)
0
-51
-51
-4
6
27
47
69
91
111
129
145
159
171
180
187
193
196
200
158
121
88
62
33
16
3
NOPLAT (DKK million)
NOPLAT probability weighted (DKK million)
0
0
0
0
0
0
0
0
18
10
80
42
141
74
208
109
272
143
332
174
387
203
436
228
478
251
513
269
540
283
561
294
578
303
589
309
600
314
473
248
363
190
263
138
185
97
100
52
48
25
8
4
7
7
27
29
44
47
59
64
72
78
81
88
88
95
92
99
93
101
93
100
90
97
87
94
83
90
79
85
74
80
54
58
38
42
26
28
17
18
8
9
4
4
1
1
PV t=0
PV t=1
NPV 31/12-2012
NPV 31/12-2013
1.216
1.312
z (return)
7,60%
Appendix 8: PROSTVAC – Tornado Diagram and Sensitivity Analysis
Tornado Diagram over RO Input Variables
RO Value
-25% Base
S_0
0
0
Volatility
0
0
Risk free rate
0
0
Tech risk phase 3
0
0
Tech risk BLA
0
0
25%
0
0
0
0
0
Two-factor model: Volatility & Strike price (percentage change)
-25%
-20%
-15%
-10%
Volatility/S_0
41,85%
44,64%
47,43%
50,22%
-25%
2000
0
0
0
0
-20%
2133
0
0
0
0
-15%
2266
0
0
0
0
-10%
2399
0
0
0
0
-5%
2533
0
0
0
0
0%
2666
0
0
0
0
5%
2799
0
0
0
0
10%
2933
0
0
0
0
15%
3066
0
0
0
0
20%
3199
0
0
0
0
25%
3333
0
0
0
0
-5%
53,01%
0
0
0
0
0
0
0
0
0
0
0
0
55,80%
0
0
0
0
0
0
0
0
0
0
0
5%
58,59%
0
0
0
0
0
0
0
0
0
0
0
10%
61,38%
0
0
0
0
0
0
0
0
0
0
0
15%
64,17%
0
0
0
0
0
0
0
0
0
0
0
20%
66,96%
0
0
0
0
0
0
0
0
0
0
0
25%
69,75%
0
0
0
0
0
0
0
0
0
0
0
Appendix 9: RSV – Static NPV
STEP 3: FORECAST FOR RSV
Phases
Preclinical
phase 1
phase 2
phase 3
BLA
Cost (mill USD)
Cost (DKK mill)
Exchange rate
59,9
336,93
5,62
32,2
181,12 Tax rate
37,7
212,06
25%
96,1
540,55 WACC
3
16,87
7,90%
Time
Year
phase
tech risk
Cul. Probability
0
2012
RSV market (DKK mill)
Market growth (%)
Market share (%)
Penetration
Revenue
Royalty (%)
Royalty (DKK mill)
1
100%
100%
2
83,7%
83,7%
100%
83,7%
56,3%
47,1%
100%
47,1%
100%
47,1%
7
2019
BLA
64,20%
30,3%
4.935
3,30%
0%
5.098
3,30%
0%
5.266
3,30%
0%
5.440
3,30%
0%
5.620
3,30%
0%
5.805
3,30%
0%
5.997
3,30%
0%
2013
1
2
2014
3
2015
4
2016
5
2017
3
6
2018
8
2020
9
2021
10
2022
11
2023
12
13
2024
2025
MARKET
100%
100%
23,3%
23,3%
76,90%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
6.399
3,30%
35%
19%
426
6.610
3,30%
35%
36%
833
6.828
3,30%
35%
51%
1219
7.054
3,30%
35%
64%
1580
14
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
22
23
2034
2035
Market (no patent)
100%
100%
100%
23,3%
23,3%
23,3%
7.287
3,30%
35%
75%
1913
7.527
3,30%
35%
84%
2213
7.775
3,30%
35%
91%
2476
8.032
3,30%
35%
96%
2699
8.297
3,30%
35%
99%
2875
8.571
3,30%
35%
99%
2970
8.854
3,30%
35%
97%
3006
9.146
3,30%
35%
95%
3041
9.448
3,30%
35%
72%
2381
9.759
3,30%
35%
53%
1810
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
2033
24
2036
25
2037
26
2038
27
2039
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
10.081
3,30%
35%
37%
1306
10.414
3,30%
35%
24%
875
10.758
3,30%
35%
13%
489
11.113
3,30%
35%
6%
233
11.480
3,30%
35%
1%
40
0
0
0
0
0
0
0
6.195
3,30%
35%
5%
108
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
15%
16
15%
64
15%
125
15%
183
15%
237
15%
287
15%
332
15%
371
15%
405
15%
431
15%
445
15%
451
15%
456
15%
357
15%
272
15%
196
15%
131
15%
73
15%
35
15%
6
6
Milestone payments
R&D Cost
0
106
106
180
180
180
17
EBIT (DKK mill)
0
-106
-106
-180
-180
-180
-17
16
64
125
183
237
287
332
371
405
431
445
451
456
357
272
196
131
73
35
Tax 25% (DKK mill)
0
-27
-27
-45
-45
-45
-4
4
16
31
46
59
72
83
93
101
108
111
113
114
89
68
49
33
18
9
2
NOPLAT (DKK mill)
NOPLAT with tech risk (DKK mill)
0
0
-80
-67
-80
-67
-135
-64
-135
-64
-135
-64
-13
-4
12
3
48
11
94
22
137
32
178
41
215
50
249
58
279
65
304
71
323
75
334
78
338
79
342
80
268
62
204
47
147
34
98
23
55
13
26
6
5
1
0
-57
-53
-47
-44
-40
-2
2
6
10
14
17
19
20
21
21
21
20
19
17
13
9
6
4
2
1
0
Pressent value probability weighted
NPV 31/12-2012
-4,81
Appendix 10: RSV – NPV no tech. risk and R&D cost
Phases
Preclinical phase
phase 1
phase 2
phase 3
BLA
Time
Year
phase
RSV market (DKK mill)
Market growth (%)
Market share (%)
Penetration
Revenue
Cost (mill USD) Cost (DKK mill) Exchange rate
WACC
59,9
336,93
5,62
7,90%
32,2
181,12
37,7
212,06
96,1
540,55
3
16,87
0
2012
4777,05
1
2013
1
2
2014
2
5.098
3,30%
0%
4
2016
5.266
3,30%
0%
5
2017
3
5.440
3,30%
0%
6
2018
5.619
3,30%
0%
7
2019
BLA
5.804
3,30%
0%
8
2020
5.996
3,30%
0%
9
2021
10
2022
11
2023
12
13
2024
2025
MARKET
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
2033
22
23
2034
2035
Market (no patent)
24
25
26
27
2036
2037
2038
2039
0
0
0
0
0
0
0
6.194
3,30%
35%
5%
108
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
15%
16,26
15%
63,82
15%
124,92
15%
182,81
15%
236,98
15%
286,87
15%
331,90
15%
371,42
15%
404,76
15%
431,18
15%
445,41
15%
450,81
15%
456,09
15%
357,07
15%
271,52
15%
195,81
15%
131,20
15%
73,41
15%
35,00
15%
6,03
EBIT (DKK mill)
0
0
0
0
0
0
0
16
64
125
183
237
287
332
371
405
431
445
451
456
357
272
196
131
73
35
6
Tax 25% (DKK mill)
0
0
0
0
0
0
0
4
16
31
46
59
72
83
93
101
108
111
113
114
89
68
49
33
18
9
2
NOPLAT (DKK mill)
0
0
0
0
0
0
0
12
48
94
137
178
215
249
279
304
323
334
338
342
268
204
147
98
55
26
5
Pressent value
0
0
0
0
0
0
0
7
24
44
59
71
80
86
89
90
89
85
80
75
54
38
26
16
8
4
1
Royalty (%)
Royalty (DKK mill)
4.935
3,30%
0%
3
2015
6.398
3,30%
35%
19%
425
6.609
3,30%
35%
36%
833
6.828
3,30%
35%
51%
1219
7.053
3,30%
35%
64%
1580
7.286
3,30%
35%
75%
1912
7.526
3,30%
35%
84%
2213
7.774
3,30%
35%
91%
2476
8.031
3,30%
35%
96%
2698
8.296
3,30%
35%
99%
2875
8.570
3,30%
35%
99%
2969
8.852
3,30%
35%
97%
3005
9.145
3,30%
35%
95%
3041
9.446
3,30%
35%
72%
2380
9.758
3,30%
35%
53%
1810
10.080
3,30%
35%
37%
1305
10.413
3,30%
35%
24%
875
10.756
3,30%
35%
13%
489
11.111
3,30%
35%
6%
233
11.478
3,30%
35%
1%
40
Milestone payments
NPV 31/12-2012
1025
Appendix 11: RSV – Tornado diagram
Input
PV -25% Base
PV +25%
Market growth
-31,99
-4,81
25,85
Royalty
-64,43
-4,81
54,80
Market share
-64,43
-4,81
54,80
Appendix 12: RSV – Management Estimates
MANAGEMENT ESTIMATES FOR UNCERTAIN VARIABLES
0
2012
1
2013
2
2014
3
2015
4
2016
5
2017
6
2018
7
2019
8
2020
9
2021
10
2022
11
2023
12
2024
13
2025
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
2033
22
2034
23
2035
35%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
35%
5%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
15%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
15%
3%
MARKET SHARE
Input
Growth
Base case
Lower estimate (95% confidence)
0%
35%
5%
Data
Base case
Lower estimate
Result
Volatility based on lower estimate (%)
Absolute volatility
24,32%
8,51%
MARKET GROWTH
Input
Growth
Base Case
Lower estimate
0
3,30%
0,10%
Data
Base Case
Lower estimate (95% confidence)
3,30%
Result
Volatility based on lower estimate (%)
Absolute volatility
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
3,30%
0,10%
36,45%
1,20%
ROYALTY
Input
Growth
Base case
Lower estimate (95% confidence)
0%
15%
3%
Data
Base case
Lower estimate
Result
Volatility based on lower estimate
Absolute volatility
80,47%
12,07%
Appendix 13: RSV – Spreadsheet for Monte Carlo Simulation and Project Volatility
Phases
Preclinical
phase 1
phase 2
phase 3
BLA
Cost (mill USD) Cost (DKK mill) Exchange rate WACC
59,9
336,93
5,62
7,90%
32,2
181,12
37,7
212,06
96,1
540,55
3
16,87
Time
Year
phase
tech risk
Cul. Probability
0
2012
RSV market (DKK mill)
Market growth (%)
Market share (%)
Penetration
Revenue
Royalty (%)
Royalty (DKK mill)
1
2013
1
2
2014
100%
100%
2
83,7%
83,7%
3
2015
4
2016
100%
83,7%
56,3%
47,1%
5
2017
3
100%
47,1%
4.935
3,30%
0%
5.098
3,30%
0%
5.266
3,30%
0%
5.440
3,30%
0%
5.620
3,30%
0%
6
2018
100%
47,1%
7
2019
BLA
64,20%
30,3%
5.805
3,30%
0%
5.997
3,30%
0%
8
2020
9
2021
10
2022
11
2023
12
13
2024
2025
MARKET
100%
100%
23,3%
23,3%
76,90%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
6.399
3,30%
35%
19%
426
6.610
3,30%
35%
36%
833
6.828
3,30%
35%
51%
1219
7.054
3,30%
35%
64%
1580
14
2026
15
2027
16
2028
17
2029
18
2030
19
2031
20
2032
21
2033
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
22
23
2034
2035
MARKET(no patent)
100%
100%
100%
23,3%
23,3%
23,3%
24
2036
25
2037
26
2038
27
2039
100%
23,3%
100%
23,3%
100%
23,3%
100%
23,3%
7.287
3,30%
35%
75%
1913
7.527
3,30%
35%
84%
2213
7.775
3,30%
35%
91%
2476
8.032
3,30%
35%
96%
2699
8.297
3,30%
35%
99%
2875
8.571
3,30%
35%
99%
2970
8.854
3,30%
35%
97%
3006
9.146
3,30%
35%
95%
3041
9.448
3,30%
35%
72%
2381
9.759
3,30%
35%
53%
1810
10.081
3,30%
35%
37%
1306
10.414
3,30%
35%
24%
875
10.758
3,30%
35%
13%
489
11.113
3,30%
35%
6%
233
11.480
3,30%
35%
1%
40
0
0
0
0
0
0
0
6.195
3,30%
35%
5%
108
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
0%
0
15%
4
15%
64
15%
125
15%
183
15%
237
15%
287
15%
332
15%
371
15%
405
15%
431
15%
445
15%
451
15%
456
15%
357
15%
272
15%
196
15%
131
15%
73
15%
35
15%
6
Milestone payments
R&D Cost
0
106
106
180
180
180
17
EBIT (DKK mill)
0
-106
-106
-180
-180
-180
-17
4
64
125
183
237
287
332
371
405
431
445
451
456
357
272
196
131
73
35
6
Tax 25% (DKK mill)
0
-27
-27
-45
-45
-45
-4
1
16
31
46
59
72
83
93
101
108
111
113
114
89
68
49
33
18
9
2
NOPLAT (DKK mill)
NOPLAT with tech risk (DKK mill)
0
0
-80
-67
-80
-67
-135
-64
-135
-64
-135
-64
-13
-4
3
1
48
11
94
22
137
32
178
41
215
50
249
58
279
65
304
71
323
75
334
78
338
79
342
80
268
62
204
47
147
34
98
23
55
13
26
6
5
1
0
0
6
6
10
11
14
15
17
18
19
20
20
22
21
22
21
23
21
22
20
21
19
20
17
19
13
14
9
10
6
6
4
4
2
2
1
1
0
0
PV t = 0
PV t = 1
NPV 31/12-2012
NPV 31/12-2013
237
256
z (return)
7,60%