Is the Celgene / Amgen deal for Otezla fair?

Celgene recently disposed Otezla indicated for the treatment of psoriasis and psoriatic arthritis to Amgen in $13.4bn deal. Therefore, the question that is raised at this point is whether the deal was good for both companies strategically and financially.

From a strategic perspective it will provide Amgen with rights of a blockbuster drug with growing revenues and with a patent expiry date between 2024 and 2028. Amgen will also gain future tax benefits valued at $2.2bn the company said (Source: Company press release).

On the other hand, for Celgene, it will pave the way to it’s merger with Bristol Myers Squibb as regulators. Initially, regulators had expressed that the deal might raise anti-trust concerns between Celgene and Bristol in relation to the companies’ anti-inflammatory pipeline (Source: WSJ).

To determine whether the deal is fair financially, one would need to derive the value of the asset. This would allows us to conclude whether Amgen overpaid or underpaid for the deal to happen. An intangible valuation method is appropriate, namely the multi-period excess earnings approach (‘MEEM’). The MEEM approach is very much similar to the DCF approach except for the addition of contributory asset charges (‘CACs’). CACs reflect the contribution of other assets to the cash flow generated by the intangible that is valued. Otezla is an intangible asset which generates cash flows through contribution of other assets such as fixed assets, working capital and workforce. Under the MEEM approach one would deduct the charges from these assets to arrive at the residual value i.e. the value of Otezla. For example, fixed asset CAC is calculated based on the proportion of fixed assets that are attributed to Otezla and the return on a return on fixed assets that one would require if he were to borrow those assets (typically 5% for fixed assets).

The key inputs in the valuation model are future revenues, profitability of the drug, patent expiry, the discount rate and CACs:

– Patent expiry: due to uncertainty on patent expiry two scenarios were developed. Scenario 1 reflects US patent expiry of Otezla in 2024 and scenario 2 a US patent expiry in 2028. Bernstein analyst Ronny Gal suggested a probability of 33% that the patent will be expired in 2028 and 67% for 2024 (see relevant article here). Scenario 3 was also developed for taking into account Otezla approval for the treatment of Behcet disease.

– Future revenues: Otezla revenues up to 2024 were obtained from EvaluatePharma. For the scenario where patent expires in 2028 a stable revenue growth rate was applied (EvaluatePharma assumes revenue growth rate in 2023 at 7% which was decreased to 6% in 2025, 5% in 2026, 4% in 2027 and 3% in 2028). For both patent expiry scenarios, post-patent expiry revenue decline was applied using comparable products (in psoriatic arthritis / psoriasis) that have already expired. In addition, Otezla has also been approved for the treatment of Behcet’s disease, which is highly prevalent in Turkey population (~80 per 100,000) while in the US prevalence is lower (~5 per 100,000). Four scenaria were built for Behcet’s disease indication (no launch – probability at 10%, peak market share of 10% – probability at 40%, peak market share of 25% – probability at 40% and, peak market share of 50% – probability at 10%).

– Profitability: given that Otezla is a relatively large share of the company’s revenue it was assumed that Celgene’s overall profitability is similar to that of Otezla, excluding R&D expense, as Otezla is already on the market. This translates to an EBITDA of ~75% going forward.

– Discount rate: Celgene’s (and Amgen’s) weighted average cost of capital (WACC) is estimated at around 9%. WACC reflect’s the weighted average risk of the company’s cash flows, which includes both pipeline and marketed drugs. It is reasonable to assume that a higher discount rate is driven by pipeline drugs which are inherently riskier from a commercial perspective (note that the discount rate does not consider clinical success rate as this is taken into account when risk-adjusting the cash flows of pipeline drugs using industry benchmarks of clinical trial success rates). As a result, a WACC of 6.5% (a discount of ~30% to the overall WACC of ~9%) was considered as Otezla is a commercial drug.

– CACs: Based on the proportion of Otezla revenue to total revenue fixed assets and working capital items were calculated. A typical return on asset of 5% and 3% were used for fixed assets and working capital, respectively. Working capital CAC was calculated at 0.4% for all scenarios. Fixed asset CAC was 1% for scenario 1, 0.8% for scenario 2 and 0.4% for Behcet disease indication.

Using the assumptions above the outputs from the MEEM valuation model are presented below:



Valuation results are as follows:

MEEM results in a value of $13.3bn which is well aligned with the actual deal value of $13.4bn and therefore, the deal was fair in terms of valuation. In addition, the impact on the stock prices of both companies was minimal which implies that the market also perceives the deal to be fair.

Now Amgen’s tax amortization benefit (‘TAB’) on Otezla will be examined. TAB refers to the net present value of income tax savings resulting from the amortization of intangible assets.

The step-up factor of 1.20 implies that the tax benefit is 16% on the value of Otezla i.e. 16% of the $13.3bn calculated in the MEEM model which translates to $2.1bn. This is in-line to the company’s estimates as indicated in its press release here.

In conclusion, based on the author’s valuation analysis the Amgen / Celgene deal is considered fair for both sides and Amgen’s estimated future tax benefits also appear to be realistic.

Biotech rNPV Valuation using Monte Carlo simulation – A simple approach

The methodology for valuing biotech products using the risk-adjusted NPV (‘rNPV’) approach has been well established. The concept behind the rNPV method is taking into account the risk of success / failure in clinical trials for clinical development products. In this way, companies can prioritise their portfolio based on the expected value of each product.

However, clinical success rates are well documented (e.g. see Nature and BIO papers) and therefore the risk lies in the market performance of the product. This is further discussed below.

There are three key revenue and cost parameters that need to be modeled to arrive at the rNPV of a biotech product. These are the following:

Revenue parameters

  1. Effective addressable number of patients (i.e. after diagnosis rate, treatment rate and patient compliance has been accounted for)
  2. Peak market share
  3. Annual price per patient on an ex-factory basis

Cost parameters

  1. Cost of goods sold (COGS): typically 10% for biologics
  2. Selling, General and administrative expenses: ranging from 25% to 35% for biotech companies
  3. R&D costs: these may be post-marketing / Phase IV studies – usually these costs are minimal upon product commercialisation.

As we may see may revenue parameters 1. and 3. can easily be defined. A company that is developing a lung cancer product, can use incidence, survival and treatment rates to determine the effective addressable number of patients. In addition, the annual price to be charged can be based on similar products in the market, for example using the price of another product that is prescribed under the same line of treatment (as prices usually differ for drugs indicated for different treatment lines under the same disease).

Cost parameters can also be determined using industry benchmarks. For example, for a CNS or an oncology product one could check Biogen’s and Celgene’s COGS and SG&A margin, respectively.

Consequently, the most uncertain parameter is peak market share as it is linked with the product’s safety and efficacy results in clinical trials. However, for a drug that is in Phase I safety and efficacy outcomes are highly unknown. As a result the valuation model should provide sufficient sensitivity and stress testing on peak market share.

The purpose of this article is to provide a user-friendly Monte Carlo simulation model that can help a company make an informed decision on whether a biotech project is worth undertaking.

In the model that I have developed, the following assumptions are made:

Indication: Non-small Cell Lung (‘NSCL’) Cancer

Company location: US

Addressable market: 500,000 reflecting 10-year prevalence of 554,000 of which 90% is treatable (i.e. not at terminal stage or at very early stage)

Peak market share: 20%

Market share uptake: starting at 10% and increasing by 10% every year. Once uptake reaches 100% it stays at 100% for another year. Due to patent expiration and generic erosion it falls down to 50% the following year, then down to 20% the year after, then down to 10% the year after and finally down to 5% in the last year of the forecasting period.

Price at launch: $150,000, which is a typical annual price for an NSCL cancer product in the US.

COGS margin: 10%

SG&A margin: 35%

Probability of success in Oncology (source BIO):  Phase I – 63%, Phase II – 25%, Phase III – 40%, Approval – 82%

R&D costs: Phase I – $30m, Phase II – $40m, Phase III – $100m, Approval – $2m

R&D period: Phase I – 2 years, Phase II – 3 years, Phase III – 4 years, Approval – 1 year

Tax rate: 26% (21% + state tax at 5%)

Working Capital: 15% of revenue

Discount rate: 25%

The assumptions above produce a risk adjusted value of $36m.

The important question is whether a peak market share of 20% is feasible or not. As mentioned previously the commercial outcome is a function of efficacy and safety results in clinical trials, which at the start of Phase I is highly uncertain.

This is where the Monte Carlo approach comes into play.

Assume in all possible scenaria the mean peak market share is 20% and the standard deviation is 10% (50% of mean). Now lets randomize the probability by using the RAND() excel function and dragging this formula down in 3,000 rows (3,000 randomised probabilities). By applying the NORM.INV function, where the mean is 20% the standard deviation is 10% and the probability is the Randomised probability calculated by the RAND function, the randomised peak market share can be obtained.

The final step is to create a data table where the row input is the randomised peak market share and the data table input is the risk adjusted value of $36m. Using the data table, a histogram can be plotted which shows in ranges of rNPV values and the count of these value ranges, including those that produce negative values. The distribution of value ranges is presented below:

The histogram shows that there are 417 possible zero or negative outcomes i.e. there is a probability of 14% that the project becomes worthless (zero or negative rNPVs).

By applying the Monte Carlo method, biotech companies are able to prioritise drug candidates that combine low probability of making a loss and high weighted average rNPV across all scenaria. Such prioritization is effective for generating high returns to investors, especially for public listed biotechs.

You may find the model with the assumptions and results discussed above in this link.

Is Novartis leading the way in pharma R&D restructuring?

Big pharma companies have undoubtedly been suffering from low R&D productivity pushing them to revise their business strategy. Although inorganic R&D strategies through M&A and in-licensing deals have boosted big pharma’s late stage pipeline, a viable organic R&D model to secure long-term survival is paramount. Novartis is a bright example of a big pharma company that tries to revisit its R&D model. The company recently announced that is abandoning 20% of its pipeline as an attempt to refocus on its innovative medicines division (see here).

Other moves include the company’s intention to spin-off its eye care devices business unit of Alcon (see here), as well as its divestment of its consumer healthcare business, which was sold to GlaxoSmithKline in a $13bn deal (see here). In addition, Novartis recently teamed up with Pfizer to develop an innovative portfolio of medicines treating nonalcoholic steatohepatitis (‘NASH’), a sub-type of fatty liver disease (see here). Both Pfizer and Novartis have a good track record within cardiovascular indications; Novartis cardiovascular franchise includes three key marketed products (Exforge indicated for hypertension, Diovan indicated for high blood pressure / congestive heart failure, and Entresto indicated for heart failure, which is expected to reach c.$4bn in sales by 2024), while Pfizer generates c.$1bn from Norvasc (indicated for high blood pressure and coronary artery disease) as well as c.$2bn from Lipitor, a product which was expired on November 2011. Therefore, this strategic collaboration aims at utilising the companies’ complimentary capabilities in the cardiovascular space. In particular, through this deal both companies expect to leverage Novartis’s existing proprietary non-bile acid product (tropifexor) in order to gain the first mover’s advantage in a segment that has huge revenue potential (fatty liver space has a global prevalence of c.3%) and is expected. Although the anti-hyperlipidaemics segment had been dominated by Lipitor (c.30% market share) and Crestor (c.15% market share) and the market size of this category has been declining since 2011 (due to the higher availability of generics products), there are a few potential blockbuster products that have already been launched (Sanofi’s Praulent, Amgen’s Repatha and Amarin’s Vascepa). NASH is a specialty indication and there are no products in the market for treating this diseases. There are high hopes for many drug development candidates such as Ocaliva (Intercept pharmaceuticals), Elafribranor (GENFIT), MGL-3196 (Madrigal pharmaceuticals), and GR-MD-02 (Galectin therapeutics). These products are estimated to reach c.$4bn in combined revenue. As a result, it is highly probable to see higher deal activity within this space in the future.

But what do the R&D refocus and specialisation into certain indications mean to the industry as a whole? Novartis is not alone in this restructuring journey aiming at building a sustainable, high-return internal R&D model; Other examples are Shire, which is attempting to follow similar path (the company recently divested its oncology business to Servier in a $2.4bn deal) as well as Merck KGaA (which sold off its consumer healthcare unit as well as its biosimilars portfolio to Fresenius and Procter & Gamble, respectively).

Will such moves lead to a more effective drug development in the future? Formulating a hypothesis as to how the industry will look like in 10 or 20 years from now would be a speculation at best. However, recent events in the sector indicate that big pharma companies tend to focus on core therapeutic areas leveraging established internal capabilities. This is a fascinating trend demonstrating that big pharma companies are trying to adopt big biotechs’s model in order to not only enable themselves to build a strong internal product pipeline but also to become more effective in picking the right acquisition or licensing targets (big biotechs are highly successful in this area). There is no doubt that biotechs’ success is mostly attributed to their specialisation on key therapeutic areas; Biogen dominates the multiple sclerosis market, Celgene generates 75% of its revenue through its haematology / oncology division and Gilead holds c.50% market share in the global anti-virals market.

Agility is a key factor for pharma and biotech companies to ensure their survival. R&D restructuring and specialisation are necessary for successful drug development. However, in order to become more effective at the earlier stages of drug discovery, combined strategic efforts with the adoption of emerging technologies (e.g. artificial intelligence) is necessary. If such strategies become fruitful it we may become witnesses of a transformed pharma space, which will also shape patient lives, most probably to the better.

In conclusion, it is highly likely that we will see more moves from other pharma companies following Novartis’s lead. Although such efforts is a good sign for the industry as a whole, these efforts are premature and there is a long way to go for a visible impact in healthcare overall.

Can U.S. Drug Prices be Justified? A U.S. vs. E.U. Comparison

Regulators and payers have raised major concerns over recent spikes in drug prices. Unjustified high drug prices (see Valeant case) have triggered not only political comments from U.S. presidential candidates in the previous U.S. elections (see Hillary Clinton’s statement) but also a broader discussion on how drug prices can be regulated and whether the European drug pricing model (reference pricing) should be adopted.

In this article, I will discuss the differences between U.S. and E.U. drug prices based on the case of CNS drugs. Prices have been drawn from various sources including reported Wholesale Acquisition (WAC) prices as well as from a number of journal articles.

The following indications will be analysed: Multiple Sclerosis, Neuropathic Pain and Parkinson’s Disease. These disorders account for ~50% of the global CNS market (excl. psychiatric disorders such as depression, schizophrenia anxiety or eating disorders).


Multiple Sclerosis (MS)

Disease Description: MS is a neurodegenerative disorder in which the insulating covers of the nerve cells in the brain and spinal cord are damaged causing a range of symptoms (mental, muscle, ophthalmic).

MS market: is highly crowded by various drugs that are prescribed based on disease progression. First line therapies include beta interferons (Avonex, Rebif, Extavia and Betaseron) which are injectables, Copaxone which is also an injectable and finally Aubagio, Tecfidera and Gilenya (Gilenya has been approved as first-line therapy in the U.S. but as second-line therapy in the E.U.) which are oral therapies. First-line therapies account for approx. 80% of the USD 22 bn. MS market.


Neuropathic Pain

Disease Description: Neuropathic pain is a chronic pain disorder in which nerve fibers have been damaged sending the wrong signals to the somatosensory system. There are 3 types of neuropathic pain: painful diabetic neuropathy, postherpetic neuralgia and trigeminal neuralgia.

Neuropathic Pain Market: Painful diabetic neuropathy accounts for 90% of the overall neuropathic pain market which is estimated at USD 2.5 bn.


Parkinson’s Disease

Disease Description: PD is neurological disorder that affects the region of the brain responsible for movement. PD slowly progresses from Stage I  (mild symptoms) to Stage V (aggressive symptoms), which are generally broken down to two major patient categories: early stage patients and advanced stage patients.

Parkinson’s Disease Market: The global PD market is estimated at USD 3.5 bn. with the advanced stage segment holding a share of ~70%.


Across all 3 CNS indications, U.S. pharmaceutical prices are approximately x 4.4 greater than EU5 prices. This is one of the main reasons that most pharmaceutical and biotech companies target FDA approval first; A company can argue to European authorities that this is the drug price approved in the U.S. and thus it should be considered as a basis for receiving a high price in European countries as well.

Are such high prices in the U.S. justified? It depends on what the U.S. market economy is trying to achieve. High drug prices is one of the incentives for U.S. biotech companies to continue innovate and for VCs to continue invest in U.S. biotech companies. In fact, the amount of VC funding that U.S. biotech firms receive is triple compared to what European biotech companies receive.

Therefore, the question is shaped as follows: how can U.S. drug prices be regulated without causing a VC funding crisis but also without resulting in a disruption of the biotech stock market?

A Simple Licensing Deal Model for your Biotech Start-Up

You can find my simple model for your use below:


Drawing on past licensing deals in the biotech space, one can see a major shift in licensing deals strategy. Big pharma is placing large bets on early-stage assets that could potentially provide pharma with long-term growth. A major challenge that licensors and licensees face is valuation of such assets. How do you ensure a “fair” value sharing?

The main challenges in developing a licensing deal model for early-stage products are:

  • Clinical Development Costs and Time-frame: to estimate the time needed for completion of the clinical trials is difficult. You would need to be clear on the time needed for: recruiting patients, completing the trial, evaluating and interpreting results. In terms of costs, you would need to estimate the number of patients to be participate in clinical trials as well as any labour costs and overheads.
  • Sales Forecast Profile: it is very difficult to develop sales forecasts for a product that is currently at the research or pre-clinical stage for various reasons including: uncertainty of the status of the market (competitors, disease status etc.) when the product is approved, pricing of the product upon approval and estimating the exact target patient population.

As a result, a flexible licensing model is needed that can incorporate different scenaria based on the assumptions above. In the deal model, three scenaria have been developed: base case, best case and worst case.

In the sample deal model I developed, the following assumptions have been made (which can be changed in the inputs tab):

  • Sales forecasts: Blockbuster sales forecast profile (peak at ~$3 b.) in the base case scenario.
  • Success rates: based on past attrition rates of oncology products
  • Discount Rate: ~10% for the licensee and ~20% for the licensor, given the high risk involved.
  • R&D expenses (Licensee): Phase I – $10 m., Phase II – 30 $m., Phase III – $75 m.
  • Operating expenses (Licensee): COGS – 15% of sales, SG&A – 20% of sales.
  • Upfront payment: $25 m. in line with average upfront payments in early-stage licensing deals
  • Milestones (development) payments: Phase I – $20 m., Phase II – 35 $m., Phase III – $70 m. (no sales milestones have been assumed), in line with average milestone payments in early-stage licensing deals
  • Tiered Royalty rates: 3% – 7%

Based on the scenario selected value sharing changes. In the best case scenario the licensee receives 72% of the value, in the base case he receives 60% and in the worst case he receives 21%. The value that is shared to the licensee drops as the scenario gets worse. The reason is that missing sales forecasts mainly harms the licensee, as it is the licensee that usually incurs the R&D expenses but receives nothing back (milestone and royalty payments) until the product is commercialised. Even upon commercialisation, the sales forecasts are risk adjusted based on probability of success rates. Therefore, if actual sales do not meet expectations licensee’s value in the deal is minimised.

In opposite, the licensor should be worried about meeting the milestones rather than future sales. More than 90% of the value to licensor comes from upfront and milestone payments, while royalty payments account to less than 10% of the value attributed to the licensor. That is because, royalty payments are too far in the forecast period and therefore, their risk-adjusted present value is really low.

In conclusion, a simple but flexible model is a key tool for understanding the value of your products as a biotech start-up. Using a multiple-scenario deal model allows companies to track the changes in the NPV sharing structure, which can be leveraged during deal negotiations with big pharma.

Modern Portfolio Theory: Does it Work for Biotech?

Modern Portfolio Theory suggests that every portfolio has its risk and its corresponding rate of return. Markowitz (1952) showed that there is no “best investment” but rather a “best” trade-off between risk and return, called efficient frontier theory.

This theory is based on a critical assumption: the risk and return profile of an asset or portfolio when constructed, is based on historical prices of the assets within the portfolio. As a result, a trader should not fully rely on Markowitz’s theory when making an investment decision; future returns / risk will not necessarily lie on the efficient frontier curve (which is discussed below).

The following formulas need to be considered to understand how the efficient frontier graph is built.

Return Formulas


Risk Formulas


Now, lets take the following example: Say you have an X amount to invest in two assets – stocks and bonds – with equal split. Therefore, you decide to invest in Apple and in the U.S. 10Y Treasury Bill (U.S. government bond). What is the risk and return of your portfolio? What is the optimal split?

Step 1: You can download historical stock prices of Apple, Inc. here and historical Treasury Bill yields here

Step 2: Apply the ln formula. Take ln of the ratio of Price at day i divided by Price at day i-1 applied to the whole sample (in this example the time period is 11 months, 6.1.2016 – 6.12.2016).

Step 3: Calculate the average return and risk of Apple’s stock and TBill’s yield (for average see formula 1 and for risk see formula 4).

Step 4: Calculate excess returns. This is the daily ln return minus the average return applied to the whole sample (formula 2)

Step 5: Construct the covariance Matrix. In this case, since there are 2 assets, it is a 2×2 matrix.

Step 6: Calculate the return and risk of the portfolio using formulas 3 and 5, respectively.

Applying these steps to the example, the portfolio’s average expected return is 8.5% and 1.5%, respectively, based on 50 / 50 split. What would be very interesting to see is how the risk / return relationship changes when using different splits. These are my results using a scenario analysis:


As you can see the inflection point is at a 70/30 split. Take the 60/40 split (1 point below the 70/30 split in the graph). You receive a return of ~8.7% and a risk of 1.4%. However, that would not be a wise investment decision. That is because, in the 90/10 split (2 points above) you can receive a higher return (~9.4%) with the same risk of 1.4%. As a result, in theory you shouldn’t construct this portfolio with a weighting less than 70% of Apple’s stock.

Considering the example above, I will now examine the application of the efficient frontier theory to Biotech. The analysis is done for midcap and largecap firms based on 5-year historical data of stock prices (June 2011 to December 2016). The following 6 portfolio sets analyzed: Mid cap, Mid cap with Treasury Bill, Large cap, Large cap with Treasury Bill and finally, Large cap with Mid cap and Treasury Bill. Two scenarios have been constructed under the latter portfolio: starting with Mid cap weight of 100% and moving down to 0% with a 10% step and by keeping Large Cap weight equal to that of Treasury bill, and the second scenario starting with Large cap weight of 100% and moving down to 0% by keeping Mid cap weight equal to that of Treasury bill.

Mid cap: in this analysis, I have included companies with market capitalisation between USD 1 bn. and USD 10 bn, while large cap are firms with market cap larger than USD 10 bn.

Therefore, the Mid cap sample includes: Alkermes, Jazz Pharmaceuticals, OPKO Health, United Therapeutics, Exelixis, Neurocrine Biosciences, Alnylam Pharmaceuticals, ACADIA Pharmaceuticals, ARIAD Pharmaceuticals, The Medicines Company, Sarepta Therapeutics, Lexicon Pharmaceuticals, Depomed and Emergent Biosolutions.

Large cap: this includes big biotech companies such as Amgen, Gilead, Celgene, Biogen, Regeneron Pharmaceuticals, Alexion Pharmaceuticals and BioMarin Pharmaceutical.

It should be noted that in both the Mid cap and the Large cap samples the weighting is split equally between the different companies.

Applying the same process as described in the initial example, the following results are obtained:


The first observation from these results is that, surprisingly, the Mid cap with Tbill portfolio does not follow the risk return profile according to Markowitz. In fact, the Mid cap graph exhibits a linear risk / return relationship (the actual formula derived from this sample is Return = 13.8*Risk – 0.2).

From a financial aspect, the linear midcap line and the Mid cap with Large cap = TBill graph (purple line) would not be wise investment decisions, as you can get the same risk with a much higher return. Similarly, the Large cap with TBill is a better investment rather than the Mid cap with Tbill rather which is slightly shifted away, exhibiting a higher risk.

Therefore, we are left with the following 2 “optimal” portfolios to choose from:


The shaded red area is a bad investment. Instead, if you decide to invest between the two blue lines the Large cap with TBill portfolio is a clear winner. Above these lines it is an area of personal taste i.e whether you want to invest in a riskier portfolio (Mid cap with Large cap) with higher return a less risky portfolio (Large cap with TBill) with lower return. However, by looking at the actual numbers, at a 100% Large cap portfolio you get the highest return of 18.4% for a risk of 1.4%. If you want to minimize your risk you would need to go down to a return of 11.3% at 1.1% risk (red line, 80% Large cap, 20% TBill). That means sacrificing 7.1% return for reducing the risk by merely 0.3%.

In conclusion, a good investment decision based on the results above, is the Large cap / Mid cap portfolio with the Large cap’s weighting higher than 75%.

Winners and Losers in Pharma / Biotech Mergers and Acquisitions: Biogen Shines Again

Pharma / Biotech is one of the most M&A intensive industries. Over a period of approximately 20 years, the industry has spent over USD 1.4 trillion in pharma / biotech acquisitions (excl. generics, OTC, Animal Health, CROs and CMOs acquisitions).

The aim of this analysis is to assess which of the acquirers have really gained from those deals based on a simplified DCF analysis of the acquired R&D and marketed products (i.e. this excludes acquisitions of technology platforms that can enhance future drug discovery efforts, as this is extremely hard to assess).

I have outlined below the steps and criteria in my analysis:

– Identified M&A deals performed by big Pharma and Biotech between 1994 and 2012. Brought forward (future value) of M&A expenditure prior to 2015 to 2015 (Valuation was done as of 31/12/2015) using an estimated WACC on a firm-by-firm basis. M&A deals post-2012 were excluded from the analysis because it was assumed that those deals cannot have an immediate or visible effect 3 years later.

– Identified the marketed products acquired as well as the products that were still under the R&D phase at the time of acquisition.

– Found the historical sales of marketed products (as well as forecasts if they are still under patent protection).

– In regards to R&D products, if those products entered the market the historical and forecasted sales of these products were used.

– Multiplied the 6-year (2010 – 2015) average Free Cash Flow (FCF) to Sales ratio of each firm by the sales of products to find FCF of each product. It should be noted that the R&D expenditure was added back prior to calculating each firm’s FCF to Sales ratio. The assumption is that, in the future, there will be no R&D expense on acquired marketed products (unless the acquirer decides to spend cash on R&D to assess if these marketed products can benefit other patient populations or be used in other indications). In the calculation of FCF for acquired R&D products, R&D expense was again added back to FCF. R&D expenses of an acquired R&D product were estimated based on three parameters: therapeutic category of each product, probability of success by phase, risk of the R&D project and time. Then the value of R&D expense was subtracted from the overall DCF value of each product.

– Brought forward (future value) the calculated FCF of the products prior to 2015 to 2015 and discounted the calculated FCF sales post-2015 to 2015 (this was done by multiplying the forecasted sales by the FCF to Sales ratio using the same WACC used to bring forward the M&A expenditure).

– Divided the total DCF value (acquired marketed + acquired R&D) by the total M&A Expenditure (by firm) resulting in the M&A ROI ratio.

The acquirers included in the analysis were: Pfizer, Roche, Sanofi, Merck & Co, Gilead Sciences, Amgen, Bristol Myers Squibb, Shire, Biogen, Takeda, Merck KGaA, Eli Lilly, Celgene, Novartis, AstraZeneca, GlaxoSmithKline and Abbott Laboratories.

The results of these analyses are presented below:


Figure 1: DCF Value of Acquired R&D and Marketed Products by Company (As of 31/12/2015)



Figure 2: Total, Time-Adjusted M&A Expenditure by Company (As of 31/12/2015)



Figure 3: Ratio of DCF Value to Total, Time-Adjusted M&A Expenditure by Company (As of 31/12/2015)


The clear winner is Biogen. Biogen is the lowest spender (USD 2.8 bn.) and the value generated by its acquired product is USD 26.2 bn. resulting in an M&A Effectiveness Ratio of 9.28. What is really impressive is the fact that 98% of that value is attributed to acquired R&D products. This implies that Biogen has the ability to spot the “hottest” products that fit to the company’s existing R&D strategy and product portfolio. It also means that Biogen acquires biotech companies with potentially successful R&D projects in their pipelines ensuring the company’s long-term growth.

Gilead and BMS have a much lower M&A effectiveness ratio than Biogen, but still relativey high considering the huge risk of R&D focused acquisitions. Both Gilead’s and BMS’s high ratio are attributed to the DCF value of acquired R&D products.

Instead, Merck and Roche have generated value mostly through targeting companies with marketed products. These buyers will potentially face pipeline gaps in the future when the patents of the marketed products acquired expire. As a result, they would need either to keep making acquisitions of firms with established products in the market or focus on building a stronger internal R&D capabilities.

Eli Lilly and Sanofi are breakeven, which means (at least in theory), M&A does not make any difference for them in terms of generating value.

The clear loser is Pfizer, which is the biggest spender (over USD 500 bn.) while the value of its M&A product portfolio is close to USD 300 bn., meaning it has “lost” USD 200 bn.

It should be noted that the analysis above has the following limitations:

– WACC of the acquirer at the time of acquisition and after the acquisition changes. Also, the discount rate used in discounting FCF of a specific product (project) might differ from the discount rate of the business. In this case, WACC has been assumed constant and equal to the discount rate used to discount the FCF of each product.

– A similar reasoning applies to the FCF / Sales ratio (which might differ between the products and companies), but for the purpose of this analysis it has been assumed that the ratio is the same across all products (under the same firm).

– Sales were projected up to patent expiry. After the patent expiry, sales were assumed to be equal to zero, which might not be the case in real life. Usually there is a sharp drop due to pressure from generics / biosimilars, however the present value of the FCF during that period is likely to be very low.

– R&D expenses of R&D products were estimated based on documented success rates by therapeutic category (see here) and out-of-pocket R&D expenditure as well as clinical development time frames (see here). The discount rate (or forward rate) used to account for time value of money was the firm-specific WACC except that the beta was changed each time a product entered to the next phase. It has been assumed that a beta of 2.5 is relevant for a research project, which was reduced by 0.25 for each of the next phases, reaching a beta of 1.25 when the product hits the market.

Brand Valuation of OTC Pharmaceutical Businesses

Brand valuation is a major part of business valuation in certain industries such as food & beverage and consumer home products. For example, Coca-Cola’s brand value is estimated at USD 73 bn. (see here), accounting for 40% of Coca-Cola’s current market capitalization.

But how does brand valuation apply in the context of pharmaceuticals? In theory, a pharmaceutical company’s brand has minimal value when it comes to generating revenue. That is because (again, in theory) doctors seek to prescribe drugs with high efficacy, safety and cost-effectiveness and thus, brand name does not (or at least, should not) affect doctors’ decisions.

Therefore, it is interesting to investigate brand value in the context of OTC (i.e. drugs that can be bought without a prescription from a doctor, e.g. aspirin).

Through my analysis I will attempt to value Bayer’s consumer care division and estimate the amount of value that is attributed to “brand name”. The reason I chose Bayer is that it generates significant OTC revenues and financial information on its OTC business unit is publicly available.

The following steps will be followed to estimate the brand value of Bayer’s OTC business:

Step 1: Estimate Market Value of OTC business.

This will be achieved by using the EV / EBITDA and EV / EBIT multiples of Bayer and apply them to OTC business’s financials.

  • Cash for the OTC business will be estimated by using an analogy of OTC EBITDA or EBIT to Total EBITDA or Total EBIT (depending on the multiple used to estimate market value of equity).
  • Debt for the OTC business will be calculated based on the cash estimated as described in the bullet point above.

A brief DCF model will be also used to validate the estimate market value of equity using the multiple approach.

  • EBIT*(1-T) of OTC business will be assumed equal to Free Cash Flow (i.e. change in working capital is assumed negligible and capex is assumed to be equal to D&A.)This assumption is completely rational. When calculating terminal value in perpetuity Capex is equal to D&A in all DCF models. Terminal value is ~60% of the overall DCF value. Therefore, the potential effect of D&A not being equal to CAPEX (during the forecast period) on the DCF-derived market value of equity will be very small. The second assumption that can obviously be challenged is that change in working capital is assumed to be 0 which may not be the case. But since this is a “brief” DCF model, change in WC will be indeed assumed to be 0.
  • Tax rate = 25%
  • Forecast period growth rate = compound annual growth rate in previous years (2007 – 2014) = 6.7%, a rational assumption for the sales forecast part of a simple DCF model.
  • Growth to perpetuity = 2%
  • WACC of OTC business = WACC of Bayer = 9.29% This assumption can indeed be challenged since the risk profile of the OTC business is possibly lower than, for example, Bayer’s pharmaceutical business (OTC business’s WACC could be in the range between 6% – 8%). But again, for the sake of this exercise, it is assumed that OTC WACC is equal to overall WACC.

Step 2: Estimate Brand Value as % of Total Vale

The royalty relief method will be used to estimate the brand value of the Bayer’s OTC business. Across 26 comparable out-licensing deals that took place during the period 2000 – 2015, the average royalty rate for pharmaceuticals was close to 10%. It should be noted that due to lack of data available (or lack of deal-making) on OTC products, the sample of deals includes mainly prescription drugs.

Based on the forecast period growth rate, the WACC and the growth rate to perpetuity, the brand value of the OTC business was estimated using the DCF method.


  1. Estimating Market Value of Equity of OTC Business

A/ Multiples Approach

Bayer’s breakdown of financials by business unit for FY 2015 is presented below:


Based on the 2015 average market capitalization, the Enterprise Value of Bayer was calculated:


The Market value of equity of the consumer care (OTC) business was estimated using both the EV / EBITDA and EV / EBIT method. EV that was estimated to stand at USD 100.6 bn. was divided by the company’s EBITDA and EBIT, arriving at an EV / EBITDA multiple of 9.8 and EV / EBIT multiple of 14.2. By applying those multiples on OTC business EBITDA and EBIT, we arrive at an EV of the OTC business of USD 14.3 bn.

As mentioned previously, cash was calculated using the % of EBITDA of Bayer that is attributed to the OTC business (i.e. 14.2%) multiplied by Bayer’s total cash (USD 1,859 mn.). Instead, debt was calculated based on the % of cash that is attributed to the OTC business multiplied by Total debt. Both methods result in the same value, i.e. USD 11.7 bn.


B / DCF Approach

WACC was calculated as follows (bond values and coupon rates were taken from Bayer’s 2015 financial statements). Cost of equity was calculated using the Capital Asset Pricing Model: risk free rate + beta*market risk premium, where risk free rate = 10 year U.S. government bond as of 31.12.2015 = 2.2%, Bayer’s beta = 1.34 (as referenced in NASDAQ) and market risk premium = 6.7% (Ibbotson).


Free cash flow was calculated as follows: EBIT*(1-T)*(1+CAGR)^n + (EBITDA – EBIT), where n = year 1, 2, 3… and EBITDA less EBIT = D&A (added back since it is a non-cash item). Also, CAGR = 6.68% and T = 25% as indicated in Step 1.


Using the DCF approach, the Market value of equity of the OTC business is estimated at USD 10.0 bn.

C / Final Market Value of Equity of OTC business

A 25% weight was assigned to the EV / EBITDA and EV / EBIT method (i.e. a total weight of 50% for the multiples approach) and a 50% to the DCF method. The weighted average market value of equity of the OTC business was calculated as USD 10.9 bn.


2. Estimating Brand Value using the Royalty Relief Method

Using a royalty rate of 9.72% and the same CAGR and WACC as in previous steps, the brand value of the OTC business is estimated at USD 7.5 bn.:



The results show that the market value of equity of Bayer’s consumer care business is approximately USD 10.9 bn. and its brand value is USD 7.5 bn. This implies that close to 70% of the value of Bayer’s consumer care business is attributed to its brand.

The key takeaway from this analysis is that brand value of pharmaceutical firms strongly correlates with OTC revenue and hence total value. Investing in marketing and brand promotion can boost the value of an OTC business and as a result, increase cash gained in deal-making. Companies that operate in various healthcare related sectors can be strongly benefited from their brand , since consumer awareness of those firms is amplified (e.g. Johnson & Johnson).  As a result, the price premium put on a potential sale of the business can also be higher.

A Simple VC Investment Model: What Every Biotech Entrepreneur Should Know (Revised)

In my previous post (see here) I developed a static financial model that incorporated all the necessary parameters to evaluate the potential investment return gain for entrepreneurs and VCs after a successful exit (through M&A).

The model incorporated what VCs usually ask from entrepreneurs: a percentage of the firm’s equity in the form of convertible preferred stock, liquidation preferences, control over the BoD and full rights of refusal.

However, after some thought and further readings I have refined the model. The assumptions are more accurate and realistic so that the model can be applicable in the real world.

The case is built as follows:

NewCo is a biotechnology company that with its own funds and Angel investors has succeeded in bringing a drug from research to phase I and is currently seeking VC funding to progress its lead drug candidate into late phases. On average an early-stage biotech company needs $70m in total (nominal value) throughout the clinical development period (6 to 9 years). Due to the huge amount of investment required, the company plans to receive three series of investments: Series A, Series B and Series C. The company has 10m of outstanding shares at the moment.

The assumptions of the model are the following:

  1. Series A investment of $5m with a 20% ownership of Newco’s equity shares and liquidation preferences requirement of x3
  2. Series Β investment of $10m with a 35% ownership of Newco’s equity shares. and liquidation preferences requirement of x2
  3. Series C investment of $55m with a 40% ownership of Newco’s equity shares. and liquidation preferences requirement of x1.5
  4. Exit strategy is M&A with an exit multiple of x6 (based on evaluatepharma data).

The initial assumptions and calculations are summarized in the table below:

Table 1: Model Assumptions

Based on these calculations, the ownership structure at exit (without any rights of first refusal for series A and B investors) can be built: Shares to be issued in each series divided by the total number of shares post-series C (i.e. series A gets = 2.5m of outstanding shares / 32.0m shares post-series C = 7.8%):


In a successful exit scenario (M&A or IPO) a promising biotech firm can be acquired for x6 its total initial investment (i.e. $420m) in this case. Looking at these returns number, it might seem impossible for a pre-revenue firm to be valued at that level. However, if the firm has developed a highly innovative therapy that addresses an unmet medical need (especially in the orphan disease space) and has showed promissing phase II or phase III trial results, it is highly likely to attract big biotech / pharma for an M&A move. This is usually the case when a biotech firm has developed a fully-integrated technology platform enabling the potential acquirer to generate multiple drugs from the platform (i.e. not a one-off product company), which is where all the “future value” comes from. However, if the acquirer is a troubled, cash-cow, big pharma company that is unable to innovate and therefore looks for a short-term pipeline refill, the target company might very well be a single-product business. In short, this example demonstrates the value that can be generated from a very successful mid-stage biotech firm.

Below, is the M&A exit scenario (optimistic scenario as series A and B investors get diluted in each series) that calculates entrepreneurs’ return:


As you can see in a successful exit of the NewCo, an incredible amount of wealth is created for both VCs and entrepreneurs. But what happens if series A and B investors exercise rights of first refusal?


In that case entrepreneurs get 1/7th of what they would normally get without first refusal rights (which is the case in most VC deals).

There are a few assumptions made to develop the model:

1) Time value of money has been ignored for simplicity: This is a static model examining the relationship between the value and the early-stage investing at discrete time points (pre-money and post-money). The model does not take into account the changing risk profile of the company as it gets closer to the market.

2) All VC investments are assumed to be allocated for R&D, personnel and other operating or capital expenses. Any potential net income is assumed to be reinvested in the company.

The key takeaway from this analysis is that VC deals always dilute entrepreneurs and, in exchange, entrepreneurs can achieve a value-adding exit that can help them become wealthy and fund future start-up ideas. As they say in the VC world “its better having 5% of something than 100% of nothing”.

You can download the model here.

Sales Forecasting in the Pharmaceutical Industry

One of the main challenges Sales & Marketing teams face is how to forecast the revenue of new products. There exist two principal strategies to estimate the sales of new products hitting the market:

  1. Primary research: communicating to KOLs and physicians how a new medicine can add value to patients and its potential side effects. Hence, based on their views and on current competition an estimation can be established for the peak sales of the product.
  2. Developing a patient flow: a purely financial estimation based on potential market share to be captured and on drug pricing.

In this article I will discuss about the second method for developing drug sales forecasts. In particular, I will establish an estimation of the U.S. and EU5 sales of Nusinersen (expected launch in 2017), an orphan drug co-developed by Biogen and Ionis Pharmaceuticals for the treatment of Spinal Muscular Atrophy (SMA). SMA is an ultra-orphan neurodegenerative and autosomal recessive disorder with a prevalence of approximately 1/10,000 live births.

SMN1 and SMN2 genes are responsible for producing the SMN protein, the protein which is crucial for the survival of motor neurons (neurons that exist in the spinal cord). In SMA, a defect in the SMN1 and SMN2 genes causes disruption in SMN protein expression.

There exist four types of SMA categorized based on age of onset, disease progression and prevalence (1,2):

Table 1: Description of SMA types

Using prevalence estimates the % breakdown of SMA patients can be derived.

Table 2: Breakdown of SMA patients by type.

SMA Patients - Breakdown

At this point, some important assumptions need to be made in order to develop the sales model for Nusinersen. Nusinersen will be the only pharmacological solution for the treatment of SMA and therefore, it can be assumed that a company with global reach such as Biogen can easily capture 40% of type 1 and type 2 patients and 10% of type 3 and type 4 at peak (since symptoms and disease progression for these types are much less serious and paying a high-cost product might not be justified in these cases). In addition, patent expiry is assumed 10 years post-launch (2027). Diagnosis and compliance rates are assumed 95% for type I and type II and 85% for type III and IV (late age of onset, less visible symptoms).

For the purpose of this analysis, the average annual cost of treatment of Duchenne Muscular Dystrophy (DMD) therapies has been assumed as the standard annual cost for SMA. That is because, both DMD and SMA are orphan, genetic disorders causing defects in the musculoskeletal system due to deletion mutations. Therefore, cost of treatment for DMD is the closest approximation to that of SMA. Since Nusinersen is an ultra-orphan product, it is normal to expect the annual cost of treatment to range between US$ 200,000 – 400,000 in the U.S. and a 60% discount on that price for EU5 (this discount accounts both for price reductions and for clawbacks / rebates that are present in some EU countries). EU prices are in most cases significantly lower than those in the U.S. Recent example in DMD: big price cuts for Translarna in Germany. (In indications where there are many treatments available, price estimations and discounts can be estimated with more accuracy by analysing prices of competitive products (number of dosages, mg/dosage, $/mg etc.) or by using reference pricing for EU).

Table 3: Estimated Annual Cost for Therapy for SMA (US).

Annual Cost of DMD Therapies

The assumptions made above can be summarized into an input sheet of the financial model:

Table 4: Inputs for Nusarnesen Sales Forecast


Using these assumptions the sales forecast is developed as follows:

Table 5: Nusanersen Sales Forecast


By 2023 the product is expected to hit the billion dollar mark driven by strong market penetration and high annual cost of treatment.

Table 5: Summary of Results


This is a bright example of a blockbuster orphan drug. Although the blockbuster model has become obsolete, there are still blockbuster opportunities for big pharma / biotech in indications where no pharmacological treatments are available, especially in the orphan space. In these markets, high prices can be charged, market shares can be maximized in little time and sales & marketing expenses are smaller leading to huge ROI. The challenge however is that regulators are stricter when it comes to high drug prices and therefore such prices must be justified by the value (in terms of efficacy and safety) added to patients.


(1) D’Amico, A. and Mercuri E. Spinal Muscular Atrophy (2011). Orphanet Journal of Rare Diseases 6, 71.


(3) Eurostat

(4) U.S. Census bureau (

10 Things I learned from “Shark Tank”

“Shark Tank” is one of my favourite TV Shows. Not only because it is related to the early-stage investment field that is the main driver of major economies but also because it is fun to watch. The way that all interesting (or not) ideas are presented and pitched to high-net worth investors stimulates your mind and makes you think “how did that folk come up with this?”.

Some of the inventions do receive funding, some do not. Before an investor says “I am out” or “I will make you an offer”, he/she explains the reasoning behind the final decision and that is where all the learning process is centered. Watching numerous pitches I noted some key challenges entrepreneurs face as well as the reasons their ideas are rejected, sometimes harshly.

  • Timing: Coming up with a novel invention that is marketable and has significant potential to generate profits and return on investment is great. However, entering the Shark Tank as a pre-revenue firm will not help you survive in the tank. Investors want some kind of track record that will attract their interest and eventually persuade them to invest in the target firm. Going too early will not necessarilly kill you but going too late certainly will; Asking for funding for an idea that started 7 years ago, has generated very few sales and has burned all the cash invested by the entrepreneur (or other investors) is certainly not appealing to the sharks.
  • Getting Distribution: A potentially money making business will attract the interest of investors but what usually troubles entrepreneurs is when they are asked “how do you get distribution?” Many entrepreneurs make the mistake to assume that they can do everything on their own. That is a no-go for the sharks especially when founders are not open-minded to suggestions and insist on the idea of going alone.
  • Asking for too much: I have seen so many ideas that have a great potential but are killed because entrepreneurs ask for so much cash for so little equity that makes investors not even think about making a counter-offer. These sky-high valuations proposed by entrepreneurs would make the investment prohibitive for any investor around the world.
  • Character: Commitment and ability are the main personal characteristics that the sharks want to see in an entrepreneur. Having a full-time job while trying to go forward with an idea shows no commitment and of course, no willingness to take risks. In such case the idea will be, most of the times, considered a hobby rather than an actual business. Demonstrating the ability to sell and to take initiatives are skills that are always needed to have. Being hesitant to pick up the phone to call potential customers will make the sharks thing that they have to do all the work and that is not possible as they have their own business to run.
  • I.P. protection: being copied by a large retailer that can manufacture the exact same item in a matter of days will not get you any market share, ever. Having a patented or at least patent pending invention is a pre-requisite before even talking about numbers.
  • Margins / Pricing: If the product is too expensive or has very low gross profit margins will be considered as a threat to receiving a return on investment. Provided that the sharks decide to invest in the business, this will be a drawback. Entrepreneurs may overcome this challenge if they use investors’ cash to place orders of their products from manufacturers in large batches so that the cost of goods sold can go down.
  • Ethics: Presenting a controversial idea might make investors re-consider to invest in the target business. But it is not only about ethics. It is also about a potential distortion of investors’ image. And that is something the sharks want to avoid.
  • Deal Structure: Being open to accept various deal structures is crucial. It is unpleasant to see a businesses not receiving funding because a specific deal structure is not preferred by entrepreneurs, even though the shark’s overall offer is very close to entrepreneurs’ initial offer.
  • Honesty: Showing honesty and integrity is vital. Presenting a product that is a part of the business and hiding the real “juice” will make sharks hesitant to invest in that person and think that a mutually beneficial relationship cannot be established.
  • Marketability: As mentioned previously an idea or product must be marketable and appealing to customers. If not so, it will be a low revenue business that will not succeed in the long-term. Investors certainly want to avoid that.

In summary, entrepreneurs should avoid making these mistakes in order to maximise their chances of receiving funding. An innovative idea must be complemented by positive investment prospects as well as good personality traits.

Venture Financing Trends in Biotech: A Decade of Healthy Investment Returns

Biotech stocks have demonstrated enormous growth during the past few years (see: The U.S. Small and Mid-Cap Biotech Shines: Stocks on the Rise). The average stock return for biotechs was found to be over 40%, depending on the date of reference during the post-IPO period (see: Post-IPO performance of U.S. Biotechnology Companies).

Biotech firms can generate huge stock returns since their IPO offer price. But what about actual returns to investors?

VC investment deal value for companies that successfully achieved an IPO exit, hit a 10-year high in 2014 (USD 8.0 bn.). It seems that biotech has recovered fully since the global financial crisis (Figure 1). Average VC investment deal per financing is also the second-highest during the same 10-year period. One major observation is while the number of financing rounds has remained almost flat since 2006 at 400 – 480 financings, the amount of funding has been increasing at a 3% CAGR.

Figure 1: Total VC Investment Deal Value by Year - Average VC Investment per Deal

Figure 1: Total VC Investment Deal Value by Year – Average VC Investment per Deal

Despite the VC investment hype for biotech, the same cannot be said for the total amount of money raised through IPO, as well as for the average IPO raised per company (Figure 2).

Figure 2: Total Amount of IPO Raise by Year - Average IPO Raise per IPO

Figure 2: Total Amount of IPO Raise by Year – Average IPO Raise per IPO

From the previous graphs, IPO Raise to Average Deal Value can be inferred. It seems that the markets hype to pay significant premiums compared to VC investments, peaked in 2011 when the corresponding multiple reached 7.2 x. Since 2011 however, the multiple has dropped to the levels of 2006 – 2007. (Figure 3).

IPO Raise

Figure 3: IPO Raise to Average Deal Value

It would be interest to see how VC investments are distributed by phase and by therapeutic area. Approximately 70% of the investments are made to biotech companies 20% to specialty pharma, while the rest of the investment to miscellaneous technologies (generics, OTC etc.). The following two graphs present the pipeline profile of the companies targeted by VC Investors (Figure 4 and Figure 5). It is clear that VC investors target companies whose pipeline is mostly at an early stage (62% pre-clinical and drug discovery), as investors understand that innovation comes at early stage and the value added of these medicines is strongly correlated with scientific expertise and money invested during those stages.

Investment by Phase

Figure 4: Pipeline of Target Companies by Phase at the time of Investment

A similar trend is observed when looking at pipeline of target companies by therapeutic areas. Approximately half of the pipeline of firms targeted by investors is in CNS and Oncology which are the most challenging areas both in terms of finding treatments and in terms of chance of success during clinical trials.

Figure 4: Pipeline by Therapeutic Area at the time of Investment

Figure 5: Pipeline of Target Companies by Therapeutic Area at the time of Investment

From these trends the are two major observations and 1 key takeaway:

Observation 1: The typical profile of a firm receiving investment from VCs, is a firm with CNS and Oncology drugs still at the drug discovery and pre-clinical stages. Investors are targeting these high risk biotech firms as they have a huge potential of bringing more than satisfactory returns through successful exit.

Observation 2: Total VC investment experienced a growth during the last 4 years, while the annual average deal size has been constantly declining from 2006 to 2013 demonstrating an upward trend only in 2014. Average IPO raise per year has been ranging from USD 65 mn. to USD 80 mn. Although in 2014 a decreased multiple of IPO raise to VC investments (4.5 x) is observed compared to previous years, it still demonstrates a strong appetite by capital markets to invest in those companies.

Key Takeaway:  VC investors believe in high-risk early stage biotech firms with promising pipeline in challenging areas that will bring high returns through exit. At a market level, market investors continue to invest in biotechs that have successfully exited and have huge potential for realising stock returns far exceeding market-average.

Do Scientists accept Management Processes?

Scientists’ acceptance or rejection of management processes has been historically a controversial issue not only at a corporate level but also at a research level. The method used by a researcher reveals the underlying theory associated with this method and determines to a certain extent the results obtained and hence, their interpretation. In order to frame this issue sufficiently defining “scientist”, “technical processes”, “management processes” as well as explaining what it means to reject or accept such processes, is important.

From a research-based view, Science can be defined as the process in which a researcher (Scientist) collects and redefines data and uses a qualitative/quantitative or mixed methodologies to achieve certain results from which specific conclusions can be drawn. Performing scientific processes at a macro-level (e.g. societies and businesses) or at a micro-level (groups with similar characteristics, e.g. engineers, managers) stems from the need to understand the various dynamics of our environments. This tendency towards identifying the stimuli of such environments is well incorporated in human nature. Scientists performing research originating from interest, dedication or passion for inventing or discovering novel results for the benefit of the community will be referred as basic researchers.

In practice, scientific research is to an extent restricted. Scientists working in a corporate environment need to carry out specific research projects that are aligned with the strategy of the company. In other words, a “corporate scientist” (also referred as applied researchers) does not have the free will to choose his subject of research. In theory, corporate scientists may not accept management processes because such processes directly affect their day-to-day work and restrict their research spectrum. Conversely, technical processes are accepted since these are compatible with scientists’ academic and research background. However, this is not always the case.

Consider that many corporate scientists work for contract research organisations (CRO) or fully integrated pharmaceutical companies (FIPCO) that perform clinical trials on their own. Corporate scientists in such organisations are very commonly involved in completing protocols: a set of actions that must be completed, as required by the company or regulatory authorities, in order to achieve certain targets. A concrete example is the involvement of scientists in clinical development process (phase I, II and III). Scientists work together to collect and validate data on patients based on the protocols provided by the regulatory authorities (FDA, EMA etc.). Such protocols are not rejected by corporate scientists but they are not fully endorsed either; because in a way protocols restrict them in a typical process that does not require the use of skills and expertise that scientists have developed throughout their lives. Hence, scientists may not accept all technical processes just because their academic and research backgrounds are considered “compatible” with certain research subjects.

Based on the discussion above, a fundamental difference can be observed; in general terms, a corporate scientist is less autonomous than a basic researcher. To situate this distinction within a philosophical framework, basic researchers have more power of self-government in their work life and are more able to exercise this power than corporate scientists. Having the ability and the opportunity to make a decision are prerequisites of having the power of self-government. The two factors determining the degree of autonomy of a scientist are the existence of realistic alternatives and the provision of sufficient information. However, there are very few or no alternatives for corporate scientists, since they tasks they have to complete are pre-determined. Instead, basic researchers have sufficient information to decide on the topic to dedicate time and effort on.

The problem for corporate scientists lies in the fact that in most large corporations there is a top-down approach, which hampers the ability of scientists to understand management processes in the same way managers do. This constraint however, can be removed if the company is open to new ideas and allows its scientists to articulate their research ideas to the upper management which will then review them and decide if these are aligned with the overall strategy of the company. In such process, an entrepreneurial spirit is developed and it can have a huge positive effect on the company’s potential to innovate in the long-term. Establishing this culture, is very common in early and mid-stage biotech firms where the company is mostly focused on R&D.

In my view, one of the reasons big pharma suffers from lack of innovation is that big pharma corporations, due to their size, have adopted the top-down approach that does not leave much room for ideas to be generated from bottom-up. And that is way, pharma’s way out of this challenge is to acquire biotech firms with promising products in their pipeline.

Structuring and Developing an Effective Business Plan

Developing a Business Plan (BP) is a very frequent action when companies expect a shift in their strategic direction or desire to have a clearer path in the future. The hardest part in developing a BP is to form a realistic plan in terms of expectations. In addition, a BP shall be understandable and easy to explain to both internal and external stakeholders in order to be implemented effectively and not just stay on paper. In this article, some insights are provided with respect to structuring and developing a BP.

Business Plan Pre-Development

1) Why a BP: before getting into writing a BP think of why you need to develop a BP, how a BP will benefit your organisation and within what time-frame (short-term / long-term) you expect that it will bear fruit.

2) Stakeholders: A company needs to identify the stakeholders that need to be involved in developing the BP as well as the frequency of their involvement. For example, internal stakeholders could be the CEO on a semi-regular basis, the Business Development Manager on a regular basis and possibly financial analysts on a regular basis as well. It is wise to consult external stakeholders such as a strategic / financial advisory firm. However, your advisor shall be a well-respected firm with significant experience in assisting its clients to develop a BP in similar sectors with proven positive results.

3) Preparation: Based on 1) and 2) the company may start to discuss internally the depth of the BP in order for the senior management together with the day-to-day stakeholders involved in the BP to budget their time prior to the development of the BP. It is crucial for the company to minimize destruction of day-to-day business during the development of the BP.

Business Plan Development

1) Availability of Historical Data: The Company shall have historical financial and operational data prepared or at least at an easily editable level. Practically the company should have 2-3 years of historical data of the following:

  • Financials: financial data should be available as analytically as possible. This does not mean just using financial statements as a benchmark but preparing detailed analysis of individual balance sheet and income statement items.
  • Detailed Analysis of the Company’s Operations: Assume that a company is a produces a range of products and sells them to a certain number of buyers. You need a basic analysis of the production process, a description of the end-products, analysis of terms (if any) of licensing / commercial agreements between the producer and the buyers and finally, a breakdown of the Company’s sales revenues and operational / capital expenses. For instance, with respect to revenue data: imports / exports, % of revenue coming from top 5-10 customers, revenue share of the different product categories. For costs / expenses: cost of goods sold (COGS) by product category and breakdown of operational expenses (payroll, advertising, insurance, utility, repair & maintenance expenses and third party expenses). It is very crucial to understand the relationship between these cost / expenses and revenues and not just report it on paper. Do these costs / expenses scale with revenues? If so, how? Will this relationship remain the same in the near future? If not, are these costs / expenses linked in another way with Profit & Loss (P&L) or Balance Sheet (BS) items?
  • Reporting figures: The way you report revenues and expenses is the way you will manage your company, so effective reporting is crucial. Does the volume of products you sell in general and their average price matter? Or is it the number of customers that matter? Which of the two makes more sense? Are most of your expenses direct (cost of production, payroll of scientists & salesmen, etc.) or indirect (management, accounting department etc.)?

2) Projections: Projections need to be as analytic and presentable as historical data. However, it is of crucial importance to make solid hypotheses and justifiable assumptions in terms of:

  • P&L items: What are the revenue drivers of the Company? Do these scale a lot with the economy at large (e.g. construction industry)?  Can you analyse easily the profitability of each of your products separately? Is it worth to utilise fully your product portfolio? Or is it hurting your profitability?
  • Balance Sheet Items: Are you getting paid fast? Or your suppliers / debtors manage their cash by delaying their payments? Do you have too much inventory in risk of losing some of your cash? Do your creditors demand payments in a timely manner? Or do they have a flexibility on the payment schedule?

All these questions should be answered carefully when writing the business plan. A business plan makes sense when there are suggestions on how to overcome the problems identified and assess how realistic the solutions are on paper compared to real life. In other words, an effective and pragmatic business plan should always be tied with an “action plan” for the company, especially if the company is an early or mid-stage company and not a mature company that is highly inflexible in implementing organisational changes and changes in its strategic directions.

3) Monitoring: the final step is to monitor the progress of the financial projections and the performance of the company. Is the company performing as projected? If not why? Is it something recurring or is it a one-off effect?

These “qualitative” issues should be reflected within the financial model that complements the business plan. Not everything can be modelled but it can be close enough to reality.

A Primer on Determining the Appropriate Type of Investor for your Company

Investments are the principal growth driver of our global economy. The motive behind every investment shapes the investment deal structure and therefore plays a significant role on the outcome of every investment. This article highlights the main differences between strategic and financial buyers.

Buyers can be classified as investment and corporate buyers. There exist general investment firms who acquire both private and public companies. In addition, there are Investment buyers focused on the private market such as Private Equity (PE) & Venture Capital (VC) firms and capital markets investors such as investment banks and funds (mutual funds, closed-end funds and unit investment trusts). It should be noted that investment banks and funds usually do not acquire entire companies but acquire certain amount of securities from different companies (“baskets”).

Corporate buyers are companies performing acquisitions for various reasons. Buy-outs is inherent in some companies’ strategy as opposed to companies who aim at growing organically. For instance, Pfizer has performed numerous acquisitions over the past few years while companies such as Merck and GlaxoSmithKline are more focused on internal growth and are much more selective when it comes to M&A.

Hybrid models of the above main categories have also been developed, for example, corporate investment arms which are “arms” of large corporations that target firms in relevant sectors and segments. They also aim at bringing high return on investments as well as identifying potential interesting targets for the larger corporation.

What are the main differences between strategic and financial buyers?

In terms of motives, financial buyers are more interested at maximizing return on investment (through a successful exit) by providing access to additional capital and leverage for the target company, if necessary. Instead, strategic buyers aim at acquiring companies that will benefit the existing establishments (by for example, product or technological complementarity, access to new geographical areas, boosting product pipeline, enhancing product discovery and design, acquiring successful marketed products and expanding manufacturing or distribution capabilities) whether this is an add-on acquisition by a PE firm or a corporate buy-out. This is achieved through synergies which is particularly difficult to achieve especially when multinationals are involved due to post-merger integration issues.

Financial buyers are more flexible in proposing alternative deal structures due to their expertise in Finance and investments as well as due to their flexible model of receiving returns which can be achieved in various ways. Instead, strategic buyers want to acquire an entire Company in order to expand and the alternatives are very few.

At a theoretical level, strategic bidders value targets higher than financial bidders due to the potential financial gain from synergies. In practice, the uncertainty and difficulty of achieving synergies as well as the higher due diligence costs involved in strategic acquisitions, strategic bidders offer price is highly volatile. Instead, financial bidders are more tolerant to higher deal values due to the better financial position.

Let’s consider the following scenario:

Company A seeks an investor that will provide access and the ability to expand in new markets but keep its employees and the key management unaffected from the acquisition.

Company B wants to cash out and wants the highest price possible.

Company C seeks an investment because of its high leverage and is negative profitability.

Company D seeks funding to use it in its research and development in order to bring its product in the marketplace.

The financials of these companies are presented in the table below (Table 1).

Company Financials

Table 1: Company Financials

Using the information above in combination with the financial information provided, we may determine the appropriate type of investor for each company. Company D is an early-stage company with no marketed products yet and therefore it has not produced any financial statements.

Company A wants to keep its employees and therefore a financial investor is more appropriate. That is because, strategic investors usually integrate the acquired company in their operations which implies employee layoffs and general organizational restructuring. However, the financial investor must be specialised and have the expertise in the relevant sector in order to provide Company A with new opportunities of expansion.

Company B wants to cash-out and maximize selling price and therefore it shall mainly a strategic investor.

Company C is highly leveraged and needs a debt restructuring which can be provided by a distress fund.

Company D is still at the research level and seeks early-stage funding. Therefore, a Venture Capital or Private Equity investor is most appropriate.

Table 2 summarizes these results.

Relevant Investor by Company

Table 2: Relevant Investor by Company




Common Mistakes in Valuation (Discounted Cash Flow)

Financial Modelling is both an art and science as it is not only based on Corporate Finance Theory but also on the ability of the Analyst to put theory in practice. This articles describes some common mistakes in Discounted Cash Flow (DCF) valuation, the principal method for valuing a business. Suggestions have been made to deal with these errors in three levels of DCF valuation: WACC calculation, Free Cash Flow calculation in previous periods as well as in the projected period and other common financial modelling mistakes.

These are presented in the following figures (click on to see the figures more clearly):

WACC Calculation

WACC Calculation

Free Cash Flow (Current & Previous Periods) Calculation

Free Cash Flow (Current & Previous Periods) Calculation

Free Cash Flow (Projected Period) Calculation

Free Cash Flow (Projected Period) Calculation

Common Financial Modelling Mistakes

Common Financial Modelling Mistakes

In conclusion, these are the most frequent mistakes involved in DCF modelling and valuation. In practice, the valuation of the Company might not very much differ if you do not correct these errors, however it is particularly crucial to acknowledge such errors and correct them before being challenged by a potential strategic or financial investor.

Pfizer AstraZeneca M&A Rumors – Is US$ 101 bn. the Right Price?

It is rumored that Pfizer will strike a US$ 101 bn. deal for acquiring AstraZeneca. AstraZeneca’s market capitalization prior to these rumors (17.04.2014) was US$ 80 bn. If these rumours are true it means that Pfizer is offering 25% premium over the market capitalization of AstraZeneca. Is this a fair price?

Normally, the price offered for acquiring 100% of a Company’s ownership should include: the current market value of equity of the target, the control premium over and above the market value of equity and a part of the present value of the expected synergies that will benefit the acquirer in the future.

A very rough Discounted Cash Flow model to estimate AstraZeneca’s market value of equity is presented in the Figure 1. According to various sources (including the Financial Times) AstraZeneca’s revenues will decline in the future as a result of major patent expirations including that of Nexium, Symbicort and Crestor during the period 2014 – 2016. By assuming a Compound Annual Growth Rate (CAGR) of -1% and a stable EBIT margin the free cash flow to the firm has been estimated.

Additional assumptions include:

Current Assets / Sales: Constant (equal to 2013 value)

Cash / Sales: Constant (equal to 2013 value)

Current liabilities / Sales: Constant (equal to 2013 value)

Depreciation & Amortisation (D&A): Constant (equal to 2013 value)

Capital Expenditure (CAPEX): Constant (equal to 2013 value)

Disposals/Purchases: 0 and Constant

Terminal Value: replacement CAPEX (i.e. CAPEX = D&A, capital investments will be used to offset the negative effect of D&A on Assets)

Free Cash Flow Calculation

Figure 1: Free Cash Flow Calculation

As a next step the discount rate (WACC) is calculated by estimating the cost of equity (using the Capital Asset Pricing Model) and the cost of debt defined as interest expense over total debt (Figure 2)

WACC Calculation

Figure 2: WACC Calculation

The market value of equity is the sum of the discounted free cash flows and the discounted terminal value. This is presented clearly in Figure 3.

Estimation of AstraZeneca's Market Value of Equity

Figure 3: Estimation of AstraZeneca’s Market Value of Equity

The amount estimated through DCF incorporates already the control premium but excludes expected value gained from synergies for the acquirer. Based on the analysis presented above the market value of AstraZeneca is US$ 101 bn., exactly the amount Pfizer is offering according to rumors. The price is right. But will AstraZeneca accept such deal?

How to challenge your Company’s forecasts

Forecasting is a major challenge when it comes to budgeting, business planning or even valuation. In order for a Company to make future projections it has to have a good grasp of the market, its competitors as well as its own strengths and weaknesses. I have identified the following factors that a company executive can challenge when it comes to forecasting:

  • Look at competition: what is their strategy? How can their strategy affect your future performance?
  • What is the situation of your commercial agreements (commercial contracts)? In other words, to what extent are your revenues secured? (especially important for retail companies)
  • Has your company performed well at forecasting Profit & Loss (P&L) and Balance Sheet items in the past? What were the major reasons for divergence from actual performance? Were the factors causing this divergence systematic or one-off (extraordinary in accounting terms)
  • Look at industry reports: Global and national (where your company operates) – What do they say about the sector and its future? Are there any extreme differences between projected performance of the sector and your company? And why?
  • Macroeconomic and regulatory factors: Is the economy booming or in a recession? How elastic is the demand of your products/services and will the demand of your products/services be satisfied under these conditions? Are there any laws/regulations that may greatly affect your company in the future?
  • Investment community: What is the stock market telling you about the sector you operate in (even if you are not publicly listed)? What is the level of consolidation (M&A activity) that may shape the future of the sector? Are there any rumours for future deals?
  • Keep internal record: What about your working capital days? Are they expected to be stable in the future? (this is particularly important when projecting balance sheet items). Are you expecting major changes in your operating expenses, cost of goods sold (COGS) and selling & administrative expenses (SG&A) in the future?
  • What is the ability of your company to pay interests on short-term and long-term loans (if any) that may affect your company’s profitability?

These are the main questions yourself and discuss with your colleagues when it comes to forecasting the future performance of your company.

The U.S. Small and Mid-Cap Biotech Shines: Stocks on the Rise

Biotech equities have sky-rocketed during 2013. As it is evident from the graph presented below, on Friday 3rd of January 2014, the NASDAQ Biotechnology Index closed at 2,373 a 58% rise compared to 1st of January 2013.
NASDAQ Biotechnology Index

NASDAQ Biotechnology Index

Such growth was largely driven by companies that were listed in the stock market post-2007 that have no filed / marketed products, but only clinical trial products. Such stocks also have dramatic potential in stock price growth in case of market entry of their clinical trial products. These companies are shown in the table below (click on the picture to see the numbers clearly):
Shiny Biotech Stocks

Shiny Biotech Stocks

In terms of past trends for those companies, the IPO offered stock price and the current stock price have been included as well as the stock price growth since IPO. It can be inferred that the majority of these equities have already sky-rocketed, before even any of the products of these companies enter the market (highlighted in green). This is a signal of “trust” of investors in these companies, as potential return on investment in case products enter the market, is huge.
In my view, the companies with slightly negative stock growth with very few late stage products are those to be watched as their future cash flows depend on the status of these products and everybody waits to see if they demonstrate positive clinical trial results (highlighted in yellow).
It should be noted that the analysis above purely depends on the financial performance of these stocks and the number of clinical trial products. It does not say anything about the quality of the companies’ products and the operational performance these companies. Hence, this analysis should, at no circumstance be used as an investment advice.
Disclaimer: The author does not hold stocks of the companies presented in the article or has not any direct / indirect financial interest with these companies.