How closely do you model your biotech names
Working in a small generalist team where I am also in charge of healthcare investments. I have in the past tried to model things very granularly but my team has no appreciation for this, which is fine. Overtime I have therefore reduced my process to something like this for pharma/biotech names:
- Review their pipeline if they have a dedicated deck (which is the case 95% of the time), otherwise see if anyone in sellside has a current overview
- Find peak sales for each asset and determine the most important ones (usually only looking at phase 2b and beyond). Sometimes the company will have calculated this. If not available, I will try to see whether there are comparable drugs or otherwise try to approximate patients in the US, guess the price and then 2x that value for global sales. It is all pretty rudimentary, I am not here trying to split hairs. General idea being that if being off by 15-20% kills the investment thesis (specifically the upside) then I was not interested anyway to begin with.
- At this point I will round up the assets that I am most interested in after having reviewed the clinical data. Time for the model which becomes even more rudimentarily. E.g. ok this asset has peak sales of $5bn. Maybe it is phase 2 going into phase 3. Perhaps chance of success is 30% and then FDA approval is 80%, with commercial execution at 75% (this is not binary, essentially me saying the remaining 25% is released as the drug starts selling and eventually reaches peak sales). So my risk adjusted value is $0.9bn. Looking around it seems the market only has this at $0.6bn, but anyway this is kinda irrelevant to me. The point here is to get past phase 3 and erase the associated 70% discount. So then my Target Sales would be X + $0.9bn/0.3 = X + $ 3bn. I expect this to trade at 4x EV/Sales. So then I can calculate target EV and from there I can get the target share price.
So in short I don't even model out the revenue curve. Sure I have some assumptions of my own more or less in terms of what figures would be good enough, I typically will have a number written down in preparation for quarterly results, but I rarely if ever model launches beyond the quarter in question, seems so futile. Really and truly I mostly read sellside reports and twitter to gauge whether the market is happy or not and then if it is not happy I will do some thinking of my own to decide whether it can ramp up to a place where the market will be happy and if not then consider selling it (case in point being UCB, where I expected a certain figure for the previous quarter). Crucially I work as a stockpicker so our strategy allows us to be thoughtful and we rarely try to dump a position immediately.
FYI I do check the basic stuff like warrants and thus dilution, revenue split with partners, etc.
Anyway I never received any formal training on the buyside regarding biotech, though I have studied this stuff. And sure I can do pharmacokinetic and pharmacodynamic modelling (though again I keep this very rudimentary) to get an idea of whether the clinical data is decent enough. But it just feels like I am just stumbling my way through biotech as my work is extremely undetailed and primarily focused on the big picture. How bad is my process?
My PM, who used to work with a more detailed biotech guy maybe a decade ago when he was an analyst, jokes about how futile his models were. That the analyst would change a simple input and the stock would crater by 40% etc. Point being that he does not put much weight into the model and is more focused on me telling him what the upside is and the likelihood of success. That's it really.
Not to show off but for the most part my process has worked. Obviously I don't get them all right. What surprises me is that it does work which makes me wonder whether I am just getting lucky, because my process for non pharma/biotech names is completely different, with models that are easily over 1k lines. whilst you would be lucky to get more than a 100 lines from any of my biotech models, let alone having more than 20 columns.
It just makes me feel like a fraud. And yet here I am in charge of our healthcare investments. Life is so weird...
It’s a generalist fund. Your efforts in biotech seem as like “better than nothing”. Also the PM seems to have more of a betting approach for these names like what is upside and chance of getting there. If upside is $100 a share and it’s 50% of getting there, then fair value of that bet is $50. If stock is at $40 he would buy in theory.
Yes compared to dedicated biotech analysts you are probably much weaker and less in depth than modeling but seems like good enough for your current seat. Generally the better modeling you can do the better but there’s a trade off and figuring out the right balance and cost/benefit for you.
GL
I think a lot of dedicated biotech analysts have valuation processes just as simple as yours. Modeling is not generally going to be a source of alpha in biotech and that discourages a lot of people from spending time on it.
The benefit of getting more granular however, is it forces you as as the investor to really think about what clinical data scenarios support which commercial outcomes. Alot of the time, simply succeeding in clinical trials is not enough. If you're haphazardly crediting achievement of peak sales regardless of clinical outcome as long as the drug doesn't fail, you're understanding of the risk/reward of the bet is flawed. This is a good way to lose alot of money in the cases that you end up being wrong.
Can second that I have experience seeing a great stock in the clinic fall and ultimately delay and out on hold it’s strong clinical expertise because it couldn’t figure out a good commercial model for the drug (specifically producing a particular treatment at scale and fast enough) to justify investing in pushing the drug through to FDA approval and having a patent cliff and exclusivity period wait out
Explicabo nemo recusandae voluptatum nihil voluptate repellat. Autem sequi quisquam sed. Vel aut nihil voluptatem ratione.
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