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.

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.

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.

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?

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.

DCF and NPV Methods and the effect of initial sales and sales growth

Before moving forward with subject of this article you may download the excel model from the link below:
Valuing start-up and early stage biotechnology companies is particularly difficult. In particular, early stage biotech and pharma companies have high sunk costs (i.e. fixed costs that cannot be recovered) and at the same time few or no sources of revenue at all. As a result most or all their Profit & Loss (P&L) items such as EBIT and Net Income have a negative sign. This restricts the ability to value these types of companies through a Comparable Multiples Method (CMM) or Comparable Transactions Method (CTM). Therefore, DCF and Venture Capital Method (see: A Simple VC Investment Model: What every Biotech Entrepreneur should know) of major importance. This article will focus on how DCF and NPV can be applied to value an early-stage biotech company.
In order to value a company using the Discounted Cash Flow (DCF) method the following variables shall be taken into account:
  • R&D Cost by Phase: This can be provided by the Management of the company (as estimates). For the purpose of this analysis the figures provided by Bogdan and Villiger.
  • Attrition Rates: Probability of approval by phase – Assumed based on past studies/cases
  • Discount Rate: Discount rate of the project can be assumed to be the same as the discount rate of the company, if the company has one project or very few similar ones (i.e. same therapeutic area – same risk etc.) Discount rate (and more specifically, beta) decreases each time a drug passes to the next phase of clinical trials because the project becomes less riskier as the product gets closer to the market. The discount rate is estimated through the Capital Asset Pricing Model (CAPM).
  • Post-approval revenues and costs: In order to value the company sales forecasts are needed. That is particularly hard and risky to do because of the uncertainty of the market, the economy, the regulation or even tax policies in general in 6-7 years from now. However, revenues and costs are necessary to estimate future free cash flows of the firm or the project.
  • P&L and Balance Sheet items: Items such as Cost of Goods Sold (COGS), Selling, General and Administrative (SGA) costs, EBIT margin, CAPEX and Working Capital will be assumed as a % of sales based on comparable companies (high growth, medium growth and maturity companies).
  • Free Cash Flow calculation (1/2): If revenue projections have already been obtained (from the company’s management) the next step is to estimate operating expenses that lead to EBIT. By assuming an appropriate tax rate, estimating CAPEX (capital expenditure on fixed assets), change in Working Capital and Depreciation & Amortization (using the relevant method, e.g. straight line) Free Cash Flow to the Firm (FCFF) can be calculated by using the following formula: FCFF = EBIT*(1-T) + (Depr’n & Amortisation) – CAPEX – Change in Working Capital
  • Free Cash Flow calculation (2/2): If revenue projections have not been provided by the management of the company then there are two alternatives. The first one is the market method and the second is the comparable method. The former suggests that the market forecasts and statistics should be found  (e.g. if the product is a cancer drug then forecasts for the oncology market need to be found – it would be even more relevant if forecasts of the subsector can be reproduced i.e. if the product is monoclonal antibody cancer drug, then research the monoclonal antibody cancer market). Then estimate the therapeutic area’s statistics (potential number of patients targeted for the treatment based on disease prevalence) estimate pricing (search for comparable products to see prices and look for social insurance reimbursement percentages) and of course examine market access and penetration issues that may arise and perform quantitative (by looking at past products) and qualitative analysis (ask doctors whether they would prescribe that drug or not, do questionnaires, focus groups etc.) based on this information.
Using the assumptions outlined and those discussed above, the following steps were taken to come out with the results:
STEP 1: Comparable Companies (COGS, SG&A, EBIT Margin, WACC)
Comparable Companies

Figure 1: Comparable Companies

STEP 2: R&D Costs by Phase
R&D Costs by Phase

Figure 2: R&D Costs by Phase

STEP 3: Discount Rate by Phase
Discount Rate by Phase

Figure 3: Discount Rate by Phase

STEP 4: Discounted Cash Flow Results
Initial Sales that result in an NPV = 0 have been used (i.e. USD 132 mn.). Sensitivity analysis has been applied to observe how initial sales shape NPV of the project (see Step 5).
Discounted Cash Flow Methodology

Figure 4: Discounted Cash Flow Methodology

STEP 5: NPV of the Project
NPV of the Project

Figure 5: NPV of the Project

STEP 6: Sensitivity Analysis – Effect of Initial Sales and CAGR on DCF and NPV
Sensitivity Analysis - Initial Sales and CAGR effect on NPV

Figure 6: Sensitivity Analysis – Initial Sales and CAGR effect on DCF and NPV

Figure 6 depicts the exponential effect of sales CAGR on DCF Valuation for different initial sales values while initial sales follow a linear relationship with DCF valuation for different CAGR. For a minimum initial sales of USD 25 mn. the product needs a CAGR of 35% for a positive NPV, while for the minimum CAGR of 15% initial sales should be at least USD 200 mn. in order for NPV to be positive.
There are various financial modelling difficulties (subjectivity, unreliable forecasts, risk) in DCF but these can be reduced if the company to be valued has already secured a licensing agreement of its product(s) with a big pharma company. Then a Comparable Licensing Deals Valuation can be applied, in which the appraisal is based on licensing and royalties revenue development and how costs are distributed between the licensor and the licensee, what is the risk and value shared etc.
For VC-backed early-stage biotech/pharma companies there is also the Venture Capital Method which can be more accurate as it is based on investors’ requirements (return, exit strategy etc.). If the investment fails the company is in trouble while the investors moves on to another company and expect that their return on investments to the next company will cover the cost of the failure (+ profit) from the previous investment.
Of course there can be a combination of the methods outlined above, i.e. a VC firm will probably invest in a company that has already proven its ability to potentially develop successful products, i.e. a company that has already out-licensed one of its products. Such company will probably have less strict terms by the VCs as opposed to a company that has not secured any deal. In that case, model-wise, a valuation model should be considered that will incorporate VC investments as well as licensing deals.

Viropharma Acquisition by Shire Pharmaceuticals: Was the price right?

Shire Pharmaceuticals acquired Viropharma for USD 4.2 bn. Was the price right? What does Comparable Multiples Method say?

In order to determine whether the price was right, a sample of comparable (publicly listed) companies was collected together with their multiples (Figure 1). Values marked with red colour represent outliers.

Viropharma Multiples

Figure 1: Viropharma Comparable Companies Multiples (Source: FY 2012 Financial Statements)

In Figure 2, the market value of equity of Viropharma was estimated based on the multiples presented above.

Figure 2: Implied Market Value of Equity of Viropharma

Figure 2: Implied Market Value of Equity of Viropharma

It should be noted that equal weights were given to all multiples which resulted in a weighted average market value of equity of USD 1,658 mn. From January 2012 to September 2013 (i.e. until Shire Pharmaceuticals showed interest which could have effect on share price), market capitalisation of Viropharma was ranging between USD 1,342 to USD 2,309 mn. with average market capitalisation (over the same period) being ~ USD 1,785 mn., converging highly to the market value derived through the Comparable Multiples Method (difference of the order of 7%). Therefore, it can be implied that the market valued Viropharma “realistically”.

On November 7th 2013 the market capitalisation of Viropharma reached ~USD 3,300 mn. The acquisition price is usually implied as follows:

Acquisition Price = Market Value of Equity + Control Premium + Synergies Premium

Control Premium is approximately 20% of the market value of equity. Since market value of equity and acquisition price are known, synergies premium should be of the order of USD 300 mn. This amount may also incorporate the Net Present Value of Viropharma’s pipeline (1 pre-clinical, 2 phase I and 5 phase II products). Indeed, according to the Financial Times through this acquisition, Shire Pharmaceuticals may achieve synergies of USD 150 mn. by 2015.

From a valuation perspective, it can be concluded that Shire Pharmaceutical’s offer converged to market reality, mainly arising from the reasonable total premium offered.

5 Ways to Boost your Company’s Stock Price

Stock Prices is the result of demand and supply forces in the capital markets. It is not necessarily linked with financial performance of the company, especially in the biotechnology sector. In fact, a significant amount of the biotech companies being acquired or after raising equity through an IPO (two of the main exit strategies) have negative Net Income. The reason is the huge amounts of capital required to push a product into the market as well as market access and reimbursement issues after the product has been approved. The capital markets and the investors are well aware of these issues and therefore they focus on companies that could bring great returns in the medium to long-term either in the form of dividends (which implies that the company needs to have positive net income) or stock price increase.

This article focuses on how a pharmaceutical company can boost its stock price. It should be noted that the suggested means are not definite and there are certain risks and pitfalls when using these methods. Hence, the disadvantages of these methods are also discussed.

Stock Repurchase (or Stock Buy-Back)

Stock repurchase has been a common method to boost share price. The reason is that in a stock buy-back the demand for the stock increases and hence its price. It is a way to convince the markets that the stock is reliable and that the company believes that its future performance will improve. A selected number of major stock repurchases of large pharma and biotech companies is shown below:

Pfizer: $10 billion Stock Repurchase Program (Announced in 2013)

Johnson & Johnson: $12.9 billion Accelerated Share Repurchase (Announced in 2012)

Amgen: $10 billion Share Repurchase Program (Announced in 2012)

Biogen: $3 billion Share Repurchase Program (Announced in 2007)

So how has these companies performed since the stock repurchase programs were announced? The following graphs show the stock price variation since the stock repurchase programs were announced.

Pfizer Stock Price since Stock Repurchase Program Announcement

Figure 1: Pfizer Stock Price since Stock Repurchase Program Announcement

Johnson & Johnson Stock Price since Stock Repurchase Program Announcement

Figure 2: Johnson & Johnson Stock Price since Stock Repurchase Program Announcement

Amgen Stock Price since Stock Repurchase Program Announcement

Figure 3: Amgen Stock Price since Stock Repurchase Program Announcement

Biogen Stock Price since Stock Repurchase Program Announcement

Figure 4: Biogen Stock Price since Stock Repurchase Program Announcement

It can be seen that in all cases there was a minor to major increase in stock price of these companies. However, there are large discrepancies; Pfizer shows a $1 increase in stock price while Biogen has experienced a 4-fold increase in its stock price. This indicates that there are numerous factors affecting the stock price such as M&A, regulatory & legal issues, company expectations and investor expectations. Therefore, one cannot simply draw conclusions from stock fluctuations but it can be, in some cases indicative of the impact of stock repurchase programs. A comprehensive and interesting analysis on this subject has been provided by Life Sci VC.

Raising Debt

Financial Theory supports that capital structure does not have an effect on firm value; However, in the real world capital markets are largely based on psychology and every move can have an impact. Raising debt can lower the overall risk of the firm provided that the firm has not reached the point of financial distress yet (i.e. the firm is unreliable and unable to pay short-term debts). In addition, depending on the amount of debt raised and how it will be used it may have a positive effect on the stock price. An example is that of Pfizer that raised $13.5 bn. in debt (in the form of corporate bonds) in March 2009 and since then its stock price has been higher than the debt offering announcement.

The types of debt raised may also affect -indirectly- the stock price of the firm based on debtor’s timely returns and flexibility.  The different types of debt are described below (As described by Bender and Ward, “Corporate Financial Strategy”, 2008):

  • Secured Debt: Backed by a collateral, low interest rate and low risk (e.g. corporate bonds).
  • Unsecured Debt: Partial covenants, medium interest rate and risk (e.g. debenture).
  • Mezzanine Debt: Covenants may exist, high interest rate and risk, convertible to equity.
  • Subordinated Debt: No collateral, very high interest rate and risk.

Selling preferred shares can also be considered as a way to finance a company. Although it is an equity measure, it features some characteristics of debt securities and is more directed to the financial performance of the company. Main characteristics of preferred shares (Miller, “Valuing a Preferred Stock”, 2007):

How Preferred Shares Characteristics May Affect Value

Figure 5:How Characteristics of Preferred Shares May Affect Value

Convertible, cumulative preferred shares with fixed and adjustable dividend rates and voting rights are more likely to attract investors and increase the demand of the preferred stock which may allow the company to further improve the terms of the preferred stock thus leading to an improved enterprise value. This in the long-term may prove beneficial to the common stock as well.

Organisational Restructuring

Organisation Restructuring requires evaluating, valuing and prioritising the main assets of the company. For example, if your company has multiple business divisions and business units can have “subunits”. As an example, considering a fully integrated pharmaceutical company which its operations lie on two main therapeutic : oncology and cardiovascular in which they are both split in mature products and early-stage products. Valuing the projects or the business units based on financial performance (e.g. sales growth, EBIT margins) is crucial for the firm (see figure below).

Organisational Restructuring

Figure 6: Organisational Restructuring

If a business unit or a subunit performs well below than the overall performance of the firm then the firm may consider to either raise funds for that unit to organically grow or sell that business to another firm. This will show investors a willingness to grow, improve financial performance that could potentially (in the long-term) be rewarder through a higher demand for equity.

Mergers & Acquisitions (M&A)

Consolidation is a major trend in the pharmaceutical industry due to the high M&A activity in the sector. There is an extensive literature in the field of M&A and particularly its effect on shareholder value and stock price. The table below shows a number of studies that have examined this effect:

Literature - Effect of M&A on Stock Return

Figure 7: Literature – Effect of M&A on Stock Return

It can be seen that the majority of these studies conclude that the effect of M&A on stock return is positive.

It should be noted though that due to the fact that most of these studies have used econometric analyses (regression) as their methodology, a large time-series data is required for the effect of time-lags to be smaller in order for the model to show significant results. In other words, small time-lags are used thus implying that these positive effects are short-term while long-term effects of M&A on stock price is not completely visible.

Diversifying Portfolio

If a company is profitable, a certain % or absolute amount of net income is usually reinvested to the company. The rest can be distributed to shareholders as dividends which can have a positive effect on stock price depending on the consistency and the (relative, i.e. compared to previous year) amount of dividends distributed.

An additional strategy can be using a small percentage of net income as capital investments to other companies. The figure below shows the types of investments (public equity, public debt and private) that can be made assessed by their level of risk and return (click on the figure to see graphs more clearly):

Level of Risk and Return of Different Types of Investments

Figure 8: Level of Risk and Return of Different Types of Investments

A portfolio of investments can be optimised by using as a benchmark: (i) average market return, or (ii) 6 month or 1-year average stock return of your company, (iii) Weighted Average Capital Cost (WACC) of your company, or (iv) Industry-specific index average return (e.g. NASDAQ Biotechnology Index – BTK) depending on the (expected) return that a company needs. In order to do that, a historical benchmarking of each type of investment should be performed. The next step is to model different combinations of investments (portfolios) to achieve the required return. Although different combinations may lead to the same required return, adjustments should be made based on the needs and preferences of the company. A sensitivity analysis is crucial as well, as some of the modelled portfolios might be highly sensitive to very few investments which makes the perceived risk high.

Overall, diversifying portfolio is a strategy that may be appreciated by capital markets, as the company will show its intention to diversify its risks and returns from different operations.


In this article 5 ways to boost your company’s stock price have been suggested: (i) Stock Repurchase, (ii) Raising Debt, (iii) Organisational Restructuring, (iv) Mergers and Acquisitions (M&A) and (v) Diversifying Portfolio. The pros and cons of each strategy have also been discussed. A combination of these strategies is more likely to have an impact on the stock price of your company. For example, a company can go through an organisational restructuring through which a certain amount of capital can be saved. Thereafter, the company can raise debt and use the “saved capital” and some of the debt to perform M&A, repurchase stock and diversify its portfolio, or a combination of the three.

A Simple VC Investment Model: What every Biotech Entrepreneur should know

Before reading this article, you can download the Excel version of the model from the link below:

VC Financing Model – Revised

All Entrepreneurs know that Venture Capitalists (VCs) want is two main things: (i) Return and (ii) Control. They want return because they have invested in a company that operates in one of the riskiest industries of the world and they want control to participate in the decision-making that may affect the future returns on their investments. What are the elements affecting their return on investment? How do these reflect to the valuation of the company after a series of investments?

Before contacting a VC (and you need to have a strategy even for that) you must make sure that you know what you need from them and if it is just capital, how much (a reasonable range) would you need and how would you allocate it (R&D and Marketing, or only R&D and then secure a marketing and distribution agreement with a large pharmaceutical company?). In brief, VCs want:

  • Initial Ownership: Percentage of stock owned by VCs based on their initial investment.
  • Dividend Provision: Future dividends model (no dividends, flat or cumulative?)
  • Exit Strategy: M&A or IPO
  • Liquidation Preferences: Return multiple (i.e. times their initial investment)
  • Type of Stock received: Usually investors required a convertible preferred stock. That is because, initially, they receive all their stock as preferred stock which means that in the case of bankruptcy the investors get paid first and then the rest of shareholders. This is a “shield” to make sure that in case their investment fails they will get back some money back. Therefore, convertible preferred stock reduces the overall risk of the investment. In case where their investment is successful, they have the right to convert all the preferred stock into common stock which can be sold to collect their investment returns.
  • Participation: If the company is sold (or if the equity raised through an IPO) more than its post-money valuation (i.e. premium) then the VCs can “participate” in that premium too.
  • Protective Covenants: usually a  non-competition covenant is applied – an employee is not allowed to work for a competitor for a specified period of time.
  • Board of Directors (BoD) Control: In order for VCs to have actual control on importance decisions made in the company they will certainly ask for board sits.
  • Rights of First Refusal: Rights of first refusal allows the VCs to prevent dilution of ownership in case of additional series of investments from other VCs. Full rights of first refusal means that VCs will maintain exactly the same ownership until exit.
  • Stock Repurchase Agreement: Restriction on stock repurchases from existing shareholders (mainly founders) to avoid concentration of shares in a single or very few shareholders.


Biostrategy Analytics Corp. is a biotechnology company that with its own funds and Angel investors has succeeded in bringing a drug from research to phase I and seeks VC funding for testing the drug in clinical trials. On average an early-stage biotech company needs needs € 60 mn. in total (nominal value) throughout the clinical development period (6 – 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.

Table 1 presents the Series A model of investment:

Series A Financing

Table 1: Series A Financing

Highlighted in blue are the assumptions of the model, while in green are calculated values. Assuming the initial investment is € 10 mn. and the required ownership is 20%, this gives a post-money valuation of € 50 mn. and a pre-money valuation of € 40 mn. If there are 10 mn. outstanding shares then 2.5 mn. of convertible preferred stock resulting in 12.5 mn. of total shares. The price per share, assuming that all preferred stocks are converted to common stocks is:

Price (€) per Share: pre-money valuation / outstanding shares = € 40 mn. / 10 mn. = € 4

Since this is an investment in an early stage company the risk is very high and the VCs will ask for increased liquidation preferences (4x initial investment) and a participation of 40%. Therefore the required investment return (nominal, i.e. at exit) is:

Required Investment Return at Exit = (Liquidation Preferences)*(Initial Investment) + 40%*(Value at Exit – Post-money Valuation)

In Table 1, the required Investment Return is 4 € 10 mn. = € 40 mn. (participation not taken into account since there is no exit yet at series A).

An additional assumption is that the conversion ratio (if the preferred stock is converted into common stock) will be 1 in all series of investments.

Table 2 below presents the valuation of the company assuming there are three series of investments: A, B and C. As it can be seen the valuation of the company changes depending on the ownership the investors require and the amount of investment dedicated by each VC. Outstanding shares are cumulative (initial shares + shares issued in each Series of investments).

Table2: Series A - C

Table 2: Series A – C

Cells highlighted in red point to the factors that mostly affect the investment return to the VCs and what is left for the founders of the company. The post-money valuation of the company after series C has been estimated to be € 87.5 mn. It should be noted that full rights of first refusal have not been applied in this model.

In table 3, the ownership structure of the company (post-series C) is shown:

Ownership Structure

Table 3: Ownership Structure

The majority of the company’s equity (69%) has passed into the hands of the VCs while only 31% has remained to the founders. In case where full rights of first refusal were applied the company would dilute further. In addition, summing up the investors’ required return gives € 170 mn. (€ 70 mn. + € 60 mn. + € 40 mn.) which is approximately 2 times the post-money valuation of the company. Therefore, only in case where the company raises equity (through an IPO or sold to another company) at least double of its post-money valuation the VCs will get the required return. Entrepreneurs will receive return only if the company raises equity or sold more than double its post-money valuation, and they will only have a 10% participation of that (see Table 4, click on the figure to see numbers more clearly). That is the only pure profit for the Entrepreneur.

Exit Scenario

Table 4: Exit Scenario

In the IPO scenario it is assumed that the company raises € 200 mn. Together with participation, investors receive € 197 mn. and € 3 mn. are left for the entrepreneur. If the company raises € 3 mn. less, then the entrepreneur gets nothing.

In the M&A Scenario, it is assumed that the company is sold twice its post-money valuation. In that case the return for the entrepreneur is much lower, i.e. € 0.5 mn.

Assumptions and Limiting Factors of the Model

1) Time value of money has not been taken into account. This is mainly a static model rather than a dynamic one as it does not take into account the risk profile of the Company, how it changes and how it develops through times. It is rather a model examining the relationship between the value of the company and the investments to it at discrete time points (pre-money and post-money).

2) Full rights of first refusal were assumed non-existent.

3) All VC investments are assumed to be allocated for R&D, Personnel Costs and Other company operating or capital expenditures. Any potential net income is to be reinvested in the company.

In conclusion, every entrepreneur should know that when seeking investments, going the VC way it is like a long journey with many obstacles and when the destination is reached you might not be rewarded.

Valuation of Pharmaceutical and Biotechnology Companies: Comparable Transactions Method (Part 3)

In this article the Comparable Transactions Method (CTM) is discussed. In CTM the valuation of the company is based on the answering the following question: If the company was sold are there any similar transactions have taken place under similar conditions? Could these transactions be used in a comparative manner in the valuation of the company? The following steps can be followed to accurately value the target company using CTM:

Step 1: Analysis of the Target Company

As in CMM (see here) the data needed to be collected for the target company are:

  • Location: headquarters, countries of operation, location of subsidiaries.
  • Quoted Status: Publicly Listed or Private.
  • Product Pipeline: Number of products, breakdown of products’ type.
  • Revenue structure: breakdown of revenues by area.

Step 2: Characteristics of Comparable Transactions

The CT sample should fulfill the following criteria:

  • The target company shall have a similar business description if available.
  • When researching for acquisitions (comparable transactions) the SIC code should be the same or close to our company.
  • Comparable transactions should have been completed at most 3-4 years prior to the valuation date.

Step 3: Collection of Comparable Transactions Data

Two types of data need to be collected for CT valuation. These are:

  • Transaction Financials: Price to Sales, Enterprise Value to Sales, Price to Earnings After Tax (EAT), Enterprise Value to EBIT.
  • Financials of the Company to be Valued: Sales, EAT, EBIT, Net Debt (Debt – Cash).
  • Other: Target Ownership (Public or Private), Announcement Date of Transaction, Percentage bought by bidder in each comparable transaction.

Step 4: Analysis

Before estimating the average and the median of the transaction multiples a two-fold adjustment has to be made in the equity value of the target company in each comparable transaction:

  • Discount for Lack of Marketability: If the target company in the CT sample is a private company and the company to be valued is public (or vice versa) then the equity value of the target company has to be adjusted. This occurs because a private company does not have a comparable equity value with that of a public company and that is because a public company has better liquidity and better access to the capital markets.
  • Control Premium: For each transaction in the CT sample it must be known whether the bidder has acquired a majority or a minority of the target’s equity. If it is a majority stake then the bidder paid a control premium which should be subtracted to find a realistic transaction multiple.

Since, it is almost impossible to find the discount due to lack of marketability and the control premium for each transaction an industry average can be applied (based on the industry classification code named SIC Code).

Control premiums for past transactions can be found here. For example, the SIC Code for the pharmaceutical industry is 2834. In the link attached, 14 transactions took place in the pharmaceutical industry in the first quarter of 2012. Taking the average of the control premiums of the above sample (excluding outliers) a representative control premium can be found if you are valuing a pharmaceutical company in 2013 or 2012. Typical control premiums can range between 15% – 45%.

Marketability discount can be found by looking at recent Initial Public Offerings (IPO) of companies in the relevant industry and comparing the company’s equity value pre-IPO with the market value of equity in the post-IPO period. Marketability discount varies by industry and company size but it is typically between 20% – 40%.


Adjusted Equity Value When Valuing a Public Company = Equity Value * (1 + a*CP + b*MD) (i)

Adjusted Equity Value When Valuing a Private Company = Equity Value * (1 + a*CP – b*MD) (ii)

  • a = 0 if the bidder buys a minority stake
  • a = 1 if the bidder buys a majority stake
  • b = 0 if the target company is public
  • b = 1 if the target company is private

If net debt is also known for each target company in the CT sample the Adjusted Enterprise Value can be estimated by adding the Adjusted Equity Value with net debt. If net debt cannot be obtained then reported (e.g. annual report) EV measures can be used.

As a final step, the transaction multiples are calculated by dividing  Adjusted Enterprise Value and adjusted equity value with the target company’s sales and EBIT and EAT. By finding the average of these ratios (excluding outliers) and multiplying by the company’s parameters the final value of the company can be obtained.

Example: CT Valuation of Sanofi (As of 31.12.2005)

Sanofi is publicly listed therefore equation (i) applies in regards to adjusted equity value.

The following CT sample 13 comparable transactions were identified (click on the picture to see numbers more clearly). A control premium of 25% and a 25% marketability discount have been applied.

Comparable Transactions Sample

Comparable Transactions Sample

The CT sample above produced the following multiples:

Comparable Transactions Multiples

Comparable Transactions Multiples

Using the CT multiples above and the Sanofi-Aventis’ financial parameters as of 31.12.2005 the market value of equity of Sanofi-Aventis is derived as follows:

Market Value of Equity Estimation - CT Approach

Market Value of Equity Estimation – CT Approach

The last step to complete the valuation process is to provide a weight for each valuation approach. DCF approach resulted in € 91,925 mn. CMM resulted in € 92,954 mn. and CT in € 100,999 mn. (press here for previous articles on DCF and CMM)

The final step of valuation is to give weights to each valuation method in order to determine the central value of the company.

CMM and CT approach will both receive equal weight of 25% while DCF will receive a weight of 50%. Therefore, the weighted market value of equity is calculated as follows:

Valuation Synthesis

Valuation Synthesis

It can be seen that the total weighted value of € 94,451 mn. diverges 10% from the actual market capitalisation of Sanofi (€ 103,656 mn.). As mentioned in Part 1 & Part 2 there are various reasons for the difference in derived values from various valuation approaches and the actual market capitalisation of a company (including: potential investors’ speculation, M&A rumors, imperfect information, short-term investments on companies’ stocks as opposed to DCF which is based on long-term free cash flows etc.)

It should be noted that the value derived is the central value. This means that sensitivity analysis was not performed to provide with a range of values. In DCF one could slightly alter the growth to perpetuity and WACC to see the potential effects on Enterprise Values. That would provide a range of values and in fact the actual market capitalisation value would lie in that range. Therefore, the derived value can be considered close to the actual market capitalisation meaning that the stock as of 31.12.2005 was not overvalued or undervalued and investors’ expectations about Sanofi-Aventis were realistic with respect to Sanofi-Aventis actual financial performance.

Valuation of Pharmaceutical and Biotechnology Companies: Comparable Multiples Method (Part 2)

In this article the Comparable Multiples Method (CMM) is discussed and analysed. CMM is based on a relatively basic principle; that the value of the target company (the company to be valued) can be derived through certain multiples (financial ratios) of similar (comparable) companies.

Step 1: Analysis of the Target Company

There are certain data that should be collected for the target. These are both financial and non-financial:

  • Non-Financial Data
    • Location: headquarters, countries of operation, location of subsidiaries.
    • Quoted Status: Publicly Listed or Private
    • Subsidiaries: number of subsidiaries, subsidiaries’ sector of operation.
    • Global Strategy: M&A, organic growth, future potential.
    • Product Pipeline: Number of products, breakdown of products’ type.
    • Number of competitors and potentially perform a SWOT and Porter’s 5 forces analysis as well as create a BCG matrix.
    • Market drivers and challenges.
  • Financial Data
    • Revenue structure: breakdown of revenues by area. For example, a company active in the Oil & Gas industry could segment its sales by type of product sold Natural Gas sales, Petroleum Sales, Bioethanol etc.
    • Cost structure: Where does the company spends its cash on compared to the industry? R&D, Marketing or Manufacturing?
    • Bench-marking of competitors and the target.

Step 2: Characteristics of Comparable Companies

The comparable companies should have similar Financial and Non-Financial Data (as in Step 1) with the target. At a later stage CMM will be applied on Sanofi, the meaning of “similar data” will be clearer and more specific.

Step 3: Collection of Financial Data and Multiples of Comparable Companies

There exist two different types of multiples. These are Enterprise Value multiples and Equity multiples.

  • Enterprise Value multiples: enterprise value (EV) is defined as Market Capitalisation + Net Debt (i.e. Debt – Cash). It is partially market-dependent (due to the market capitalisation component) but it has a significant enterprise specific element (net debt). The most commonly used EV multiples are EV/Sales, EV/EBIT, EV/EBITDA and EV/Free Cash Flow.
  • Equity multiples: these are multiples which are based on the market value of equity of the comparable company. PE ratio, P/Sales, P/Book Value and P/Operating Cash Flow are mostly used.

Step 4: Analysis

Before estimating the average and the median of the multiples above a careful consideration shall be given when ruling out outliers. Outliers are numerical values diverging from most of the sample. It should be noted that the median is estimated for ensuring that the sample is uniform (i.e. all outliers have been excluded, sample is converging). After analysing and deciding on the final multiples the market value of Equity and the Enterprise Value can be estimated based on the corresponding multiples and financial data of the target company (e.g. if  the average of P/Sales of the comparable companies has been estimated, then it should me multiplied by the sales of the target company to measure what its P is i.e. its market value of equity).

Example: CMM Valuation of Sanofi-Aventis (As of 31.12.2005)

In 2005, Sanofi-Aventis was particularly active in 3 main therapeutic areas: Cardiovascular (~10% of total sales), CNS (~20% of total sales), Blood (~15% of total sales) and Oncology (~10% of total sales). Using appropriate country filtering (U.S., Northern European and Japanese companies were included) and by searching through financials the following companies with similar revenue breakdown were identified:

 Baxter International
 Johnson & Johnson
 King Pharmaceuticals
 Mitsubishi Pharma
 Torii Pharmaceutical

By assessing the characteristics of the sample one could observe a number of problems. Firstly, comparable companies in terms of market size are missing apart from Johnson & Johnson, which however, has a large medical devices segment and could be considered non-comparable. For the purpose of this valuation, Johnson & Johnson will be included. The second problem is the size of the sample. The sample contains 6 companies which is sufficient only if it contains highly comparable companies.

In the table below the multiples of the comparable companies are shown. Highlighted in red are the outliers which have been excluded in the calculation of the average and the median (click on the picture to see the actual numbers more clearly).

Comparables Companies - Average Multiples

Comparables Companies – Average Multiples

The table below presents the process of estimating the total market value of Sanofi Aventis’ equity based on the derived transaction multiples. Net Debt has only been subtracted from Enterprise Value to determine the market capitalisation of the company as figures derived from equity multiples are market values of equity.

Market Value of Equity Estimation - CMM Approach

Market Value of Equity Estimation – CMM Approach

Using the CMM approach the market value of equity of Sanofi-Aventis as of 31.12.2005 was estimated at € 92,954 mn. The market capitalisation of Sanofi-Aventis was € 103,656 mn. (31.12.2005).


In CMM one collects a sample of comparable companies based on both financial and non-financial criteria. Equity and enterprise multiples are collected for the comparable companies and the average and median are calculated for the comparable companies and outliers are excluded. Thereafter, the average multiples are applied to the target company. Net debt has to be subtracted from the enterprise value derived from the comparable multiples, as equity multiples estimate the market value of equity and the aim is to compare these values to the actual market capitalisation of the target company.

Although a 10% deviation between the derived value and the actual market capitalisation of Sanofi-Aventis can be considered as huge when considering share price performance, CMM is highly sensitive to the selection of the sample and the average multiples. A difference in a decimal point in a high-weight multiple can have a large impact on the final value of the company.

The next article will focus on the Comparable Transactions (CT) methodology and provide an overall summary of the valuation results from the 3 methodologies (CMM, CT and DCF) on Sanofi.