The following post appeared over at Motley Fools' biotechnology board. I felt it could be of interest also to SI biotechies.
As the MF boards are now subscription only, I have asked the author's permission to re-post it here. He accepted, noting that he follows quite a few of the boards over here at SI, but that he doesn't have any writing privileges.
Any comments would be welcome. I feel for example that one would have to account for the expected market size one way or another.
Erik
For my 3 star 500th post on the Fool I thought I should try to do something a little different. So I thought that I would lay out a proposal for developing a pipeline valuation metric. When I am through I will leave it open ended to gather comments from the board. Warning! This is very long!
There are several valuation metrics that are relative measures such as Price/Earnings (P/E), Price/Sales (P/S), Price/Cash Flow, etc. Their use is to provide a context in which to place how much we are paying for a company. This can be amongst peers w/i an industry in the same timeframe or to compare the current valuation w/ how the company has been valued in its past.
Such metrics do not apply to the majority of biotech companies as they do not have earnings or even sales. We could assume that much of their value lies in their pipeline. For the purposes of making industry wide comparisons, perhaps it is useful to have a relative valuation metric that could be used to determine how much we are paying for a company's pipeline. And perhaps it is also useful if we could determine how much value the market places on a pipeline today as compared to the past history of the industry. Maybe such a metric would allow for the identification of bubbles and depressions as the metric would clearly indicate aberrantly high or low valuations.
I will state the goal as developing the price to pipeline ratio which I will denote as P/P. P/E is typically share price over earnings per share but it is also market capitalization over net income. As there is not a per share value of pipeline that is easy to determine, P/P will be in terms of market capitalization over pipeline. Thus we have the starting equation:
Price/Pipeline = Market Capitalization/Pipeline
Now what we need to determine is a quantitative measurement for pipeline to plug into the equation. One way is to simply add up the number of drugs at each stage:
P/P = MC/ #Phase 1 + #P2 drugs + #P3 drugs + # BLA/NDA drugs
We should all realize this is somewhat inappropriate as it gives equal weighting to all of the drugs at various stages of clinical trials. This is not true at all as experience tells us that late-stage drugs are given much more value than early stage drugs. So we need to revise the equation to reflect these weightings, where A,B,C, and D are the appropriate relative weights for each stage. So now the equation becomes:
P/P = MC/(A)(P1)+(B)(P2)+(C)(P3)+(D)(P4)
Now we need to derive the values of the relative weightings for each stage of clinical trials. Essentially the question becomes how much more value does the average phase 3 drug have over the average phase 1 drug? What we are looking for is the differences in value between the different stages on average.
To simplify the process, I will make the assumption that there is such a thing as an "average" drug. We don't want to worry about high potential vs. low potential. This is because we are looking across hundreds of drugs throughout the industry. And over all these drugs the differences will average out. That is the assumption.
So that means we can ignore variables such as potential market size, competition, per patient drug costs, etc. This simplifies down to two variables: different development risk per stage and the length of time before the drug gets approved.
I will start with development risk. Late stage drugs have more value simply because they have higher odds of approval. We have a better chance of getting a payoff by investing in these drugs. In this case, the relative values of each stage is easy to determine. We can say that the relative values of the clinical trial stages is based on the odds of success at the particular stage. So if I fill in the values for A,B,C, and D with the historical success rates the P/P equation becomes:
P/P = MC/(0.1)(P1)+(0.3)(P2)+(0.67)(P3)+(0.81)(BLA/NDA)
This is based on the industry averages that drugs in phase 1 have 10% odds of eventual approval, phase 2 drugs have 30% odds, etc. This is essentially the Core Clinical Index (I think that's right) that Greg Carlin (ElricSeven) developed a few years back. If anyone else was involved and I didn't credit you I sincerely apologize.
What the equation essentially says is that since, for example, a phase 2 drug has a 30% chance of eventual approval and a phase 1 drug has 10% chance of eventual approval, that makes the phase 2 drug worth 3X the phase 1 drug. On average, of course.
So the process of developing a pipeline score is to add up the # of drugs at each stage, adjust w/ the multiplier, and then sum up the values.
I want to step away from the relative development risks and mention the importance of time. A late stage drug has more value because approval is closer, making the cash payoff for the R&D expenditure closer. With a drug that has had a BLA filed, it may be on the market within a year earning revenues for the company and its shareholders. In contrast, a Phase 1 drug is probably 7 or 8 years away from the market, making the future cash payoff far away and therefore much less valuable in today's dollars.
I would propose that there is a time value factor making late stage drugs more valuable than early stage drugs. Using figures based on industry averages, phase 1 drugs are 7 years from the market, phase 2 drugs are 6 years from the market, phase 3 drugs are 4 years from the market, and BLA/NDA drugs are 1 year from the market. Maybe specific times are debatable, but the important point is that there are different lengths of time to approval for drugs at each stage.
Now what needs to be done is to discount the cash payoff for approval back over these time periods to determine their relative values due to the time factor. I do not want to bias anyone who may have a better way to do this so I will use my result without showing my work. I will be willing to go over this later though. Using the relative time values I derived for each stage and entering them in for A,B,C, and D, the P/P equation becomes:
P/P = MC/(0.28)(P1)+(0.34)(P2)+(0.48)(P3)+(0.83)(BLA/NDA)
According to the time weightings I derived, a drug at the BLA stage is worth about 2X a drug at phase 3. Maybe this makes sense because I assumed it will be on the market generating sales 3 years earlier than the drug in phase 3.
In this case, to arrive at the numeric value for the pipeline denominator, just add up the drugs and multiply as appropriate. Then sum up. Then dividing market cap by the pipeline score gives the P/P ratio.
I am going to finish with a few comments and not complete the work. That is all open for discussion. And the validity of the assumptions is all up for discussion as well.
Maybe we can all agree that development risk and time value are important variables contributing to the fact that on average a Phase 3 drug is worth more than a Phase 1 drug. However, notice that the relative weightings by trial phase is different in each case. What to do? What to do?
So, can the board reconcile the two equations for development risk and time value? Perhaps the final equation should look something like this:
P/P=MC/(A)(A')(P1)+(B)(B')(P2)+(C)(C')(P3)+(D)(D')(BLA/NDA)
Where the ABCD are the weights for development risk and the primes are time value?
Or maybe that's the wrong way to express it? Perhaps. I'd love to see what others think because I'm not a mathemetician, I'm just an impostor that's had a little too much time in school.
So I wrap up with these questions:
Can we express the relative importances of R&D risk and time on the values of drugs in different stages? How do we reconcile the two equations? (Sorry, this isn't developing a Grand Unifying Theory for quantum mechanics and relativity so you won't win the Nobel Prize if you're right.)
If we could develop such a P/P metric does it have any real value to an investor? Do you want to know how much you are paying for Millennium's pipeline over Vertex's? Or how much more you are paying for it now than in the past?
Are today's pipelines cheaper than the historical average for the industry? Would a P/P metric help us answer that question?
Is there a better way to make fast and easy industry wide pipeline valuation comparisons?
Or should we ignore such academic nonsense because we live in the real world?
I have thoughts on this, but I'll wait to see what the board has to say.
Enjoy,
Charly |
