Biotech Values

[TastyTheElf]

unduly negative toward the claims of various small biotech companies

DewD, I think I should probably qualify my complaint better, as I'm the one who generated this sidetrack with my bile.

Small bios tend to hype their results/plans because their survival depends on their ability to raise money largely through private offerings of equity. So they need a higher stock price to control dilution. That alone, for me, makes me a skeptic.

I guess what bothered me was the more specific issue of working hard to create bear scenarios to refute analysis that isn't being provided by those companies, but is the result of taking publicly available information and extrapolating trial outcomes.

For instance, you have a small biotech that had what appear to be good Phase II results -- which are hardly conclusive but certainly encouraging -- and then you have enrollment data, Phase III trial parameters, and a good (if not great) sense of likely survival for the control arm. Then you assume that the drug is performing consistent with its Phase II performance, and you get modeling outcomes that are consistent with the trial progress to date (e.g. with guidance from the company on when data should be available or when an interim trigger will be met or simply vis-a-vis how much time has gone by).

In such a case, I think you have reasons to become bullish -- perhaps cautiously bullish -- on that outcome. One should still have concerns about many things, including the accuracy of the data and any guidance, the quality of the Phase II trial and its results, and the possibility of unknown parameters/factors that could be causing the modeling outcome other than efficacy (e.g. lags in endpoint measurement, the possibility of unusual interim parameters, high LTFU rates, etc).

I would encourage no one to run a model and plunge in to something. But there seems to be a pat attitude on this board that this particular DD tool is flatly invalid -- "the numbers game never works" -- and some think that if you can construct a defensible modeling outcome (regardless of likelihood), that example invalidates the tool. I think that's a mistake.

Suppose I ran a trial with two healthy guys, age 50, gave guy one a sugar pill every day, and gave the other guy some other pill every day -- there is no disclosure regarding what it is -- and the trial goes on like this until both guys are dead. Then I come back to you 100 years later and tell you that the trial is still going because one guy is alive and healthy, and that's all I tell you.

Are you really going to tell me I know literally nothing about the mystery substance? Are you really going to tell me that it is not likely that the mystery substance extended this guy's life? That's what iwfal would tell me, I think.

Regards,
TGW