Henrik Ekman BioTech Equity Analyst
How to look at valuation of Biotech and Life Science companies?
In our last BioSnack we concluded valuation as being one of the most important things to consider if you are a long-term investor in Biotech and Life Science companies. We acknowledge, that if you are a short-term investor and think the high volatility in Biotech and Life Science stocks is positive because it constantly provides you with trading opportunities, it is often more important to assess how risk appetite will develop in financial markets. Factors affecting risk appetite in financial markets can be macroeconomic and geopolitical uncertainties, and in particular how central banks conduct monetary policy. However important, these factors are difficult to forecast – as short-term movements in financial markets always are – and the objective of the BioSnack is not to add value in forecasting changes in market sentiment and risk appetite. Instead, we will try and give you some valuation perspectives on the Biotech and Life Science stocks from a long-term perspective.
Biotech and Life Science requires different valuation approach
Compared to most other sectors, Biotech and Life Science companies typically only have little, or no revenue and income when they are in their developing phase. Therefore, some of the widely used stock market valuation metrics like P/E (Price Earnings), EV/EBITDA or P/S (Price/Sales) is difficult to use as they all require a realistic revenue and earnings number to make meaningful calculations.
Instead, we use a DCF (Discounted Cash Flow) model to get a picture of how much value the market has currently discounted in the share price.
The DCF-model is widely used by analyst in the stock market across sectors, but it is especially relevant to use with Biotech and Life Science companies because it does not require revenue or positive earnings estimates on a short-term basis. Instead, the model calculates the accumulated present value of all the individual likely future net cash flows from the company on a long-term basis, whether they are 5 or 10 years out – or longer. In practice, however, although DCF-modelling being the theoretical correct framework for evaluating companies, the approach still relies on several assumptions and cash flow inputs to be correct and relevant.
How to use the DCF model
Some of the key assumptions to consider before using the DCF model and calculating the individual cash flows are the following:
- Which part of the pipeline should be included?
- Market size and growth rate (according to the company)
- Pricing structure, gross margins, and royalty rates
- Market share, peak level, and market share penetration curve
- EBIT or EBITDA margins
- Operating expenses, and reinvestment rate requirements
- Capital increase and share count
- Discount rate
The first point in question relates to the pipeline, as many Biotech or Life Science companies have a huge pipeline of projects of which some are still only in early pre-clinical phases or phase 1. To be conservative, we would typically only include the more advanced products, i.e., those in phase 3 or late stage 2. The products in early phases do have potential value, but it would be considered more of an ‘optional’ type of value. The same goes for those Biotech or Life Science companies that has a technology platform that can potentially be used within many therapeutic areas, some of which is not even being tested in pre-clinical trials yet. The platform has value, but it is also an ‘optional’ type of value. That optionality can have huge value, as we have repeatedly been reminded, when Big Pharma acquire biotech companies with the primary purpose of getting access to the technology platform.
We also want to highlight, that the model uses the public available estimates from the company regarding market size and growth, when available. This way estimate risk is limited to one source.
The DCF model comes with limitations
Generally, it is important to remember that the detailed individual cash flows are still only estimates based on a list of assumptions with huge, implied uncertainties, which ultimately does not necessarily make it a better guiding tool whether a stock is attractively or expensively valued compared to the beforementioned simple P/E or EV/EBITDA. According to critics, DCF-models are famous for being ‘perfectly wrong’ as the model is only as good – or bad – as the estimates that are being put into the model.
Therefore, the often more relevant use of the DCF-model is to do sensitivity analysis by changing one or more assumptions positively or negatively thereby getting a sense of what is the primary drivers of the valuation of the company in question. For instance, if we change the peak market share assumption for a new pipeline product from 10 to 15 percent versus changing the EBITDA margin from 25 to 35 percent, which is most important driver of value?
For all the relevant shortcomings, the use of the DCF-model is still considered a relevant valuation model for assessing valuation dynamics of Biotech and Life Science companies.
Low valuation compared to history
After the calculations in the model has been made, the value is compared to the market value of the company to get a picture of how much of the potential future value is implicitly discounted by the market. This can be measured by the Probability of Success (PoS) which – according to the market and based on the beforementioned assumptions – reflects how likely it is for the individual company to get its phase 3 project approved and successfully commercialized.
As our calculations show – and exemplified in the two One-pagers included in this BioSnack – it is not uncommon that current implied market valuations reflect 20-25 percent likelihood for the products in phase 3 to become successful.
This compares to a historical industry average level of success (PoS) of approximately 55 percent for phase 3 studies across indications according to Biostatistics. In other words – and as exemplified – the market currently thinks there is less than half the chance for many Biotech and Life Science companies to be as successful as the industry has been historically.
Another way to interpret the low number, is that the markets implicitly think there is a risk that the companies in question would need to raise capital and dilute its shareholders by more than doubling the share count. That generally seem to be a relatively harsh assumption. And also, if products in less developed phases are included, the PoS is even lower, suggesting that even less of the potential future value is discounted.
Valuation is important and very supportive
In theory the DCF model accumulates all future potential cash flows and calculate a present value of the estimated accumulated earning (‘E’) from the Biotech or Life Science company. In most other sectors, the estimated E constantly changes due to macroeconomic and geopolitical uncertainties, so assessing when the P/E multiple is attractive can be difficult. The E in Biotech and Life Science is subject to far less change as it primarily reflects the estimated financial effect of a potential future medical advancement based on science that is not affected by changed macroeconomic development etc. This way the Biotech and Life Science E could be interpret as a constant or fixed value, while the valuation P becomes much more important as it is the only moving factor.
As described, when using the DCF model on many Biotech and Life Science companies you get a clear impression that the market currently discounts far less of the potential future value upside compared to historical averages. As we have seen in the beginning of the year, Big Pharma has realized this and started buying. Experts expects this to continue, and if correct, it will be a welcoming new determining factor for the market for Biotech and Life Science stocks that could potentially result in a very promising 2023 for Biotech and Life Science investors.