Hey Richard, this is an amazing video. How accurate do you think that past reports are, especially ones that are considering data before 2016? Do you think it is still useful for the new technologies of 2022 and how maybe the success rate is higher because of these technologies? Should we make any higher adjustments to past data?
The short answer is that a lot of investors do assume higher POS due to improved technology, but there isn't a lot of evidence to support that assumption, and in reality they just end up overvaluing companies. We can see the consequences of overvaluing stocks playing out in the bear market of the last year and also the increase in negative stock reactions to news (implying that investors had overly optimistic expectations of study success): lifescivc.com/2022/03/biotech-bears-jumping-a-lower-bar-or-a-higher-one/ there are some studies of more recent trends in clinical trial success rates, but the issue with analyzing more recent clinical studies is that there are a lot of studies that haven't finished yet, so you don't know if they succeed or fail. Thus estimates using more recent studies are prone to high inaccuracy (see FAQ 23 here: projectalpha.mit.edu/faq/, where they originally estimated prob of success for a recent cohort at 13.8% but new data showed it was actually 6.6% -- half the level that they originally estimated). It's also important to note that historically, improvements in drug discovery technology have not correlated with improved R&D productivity -- Eroom's Law states that R&D productivity is on a cyclical decline even despite massive improvements in technology. There is an argument to be made that some of the observed stabilization / modest improvement in R&D productivity is due to a friendlier FDA, better / more focused clinical trial design, or other factors rather than just improving tech. Overall as Frank said you can't rely on any general dataset for POS -- recent or historical -- you have to look in detail at the drug in question, the target, the development plan, trial design etc. And you'll never be able to accurately predict the POS of any novel target or technology. For practical purposes I find it easier to try to figure out what POS the market prices in and then see whether I disagree or agree strongly with that. If I have to squint to see if my POS differs from consensus then I usually move on to an idea where I have a more differentiated view. If you like an investment but your conviction isn't super high (maybe you have a lot of uncertainty about the POS), you can account for that uncertainty in the size of your position (if you aren't super confident in an investment, but think it's still worth doing, just make it a smaller investment and vice versa -- ie bet your edge).
Anything specific about the development of it? I touched on pricing of Zolgensma at the end of this blog post: www.baybridgebio.com/blog/most_expensive_drug.html Let me know if there are other questions on pricing
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Thank you so much for these amazing series! Happily subscribed.
Great work, Richard! Very useful content for someone exploring a move into portfolio / BD work
Hey Richard, this is an amazing video. How accurate do you think that past reports are, especially ones that are considering data before 2016? Do you think it is still useful for the new technologies of 2022 and how maybe the success rate is higher because of these technologies? Should we make any higher adjustments to past data?
The short answer is that a lot of investors do assume higher POS due to improved technology, but there isn't a lot of evidence to support that assumption, and in reality they just end up overvaluing companies. We can see the consequences of overvaluing stocks playing out in the bear market of the last year and also the increase in negative stock reactions to news (implying that investors had overly optimistic expectations of study success): lifescivc.com/2022/03/biotech-bears-jumping-a-lower-bar-or-a-higher-one/
there are some studies of more recent trends in clinical trial success rates, but the issue with analyzing more recent clinical studies is that there are a lot of studies that haven't finished yet, so you don't know if they succeed or fail. Thus estimates using more recent studies are prone to high inaccuracy (see FAQ 23 here: projectalpha.mit.edu/faq/, where they originally estimated prob of success for a recent cohort at 13.8% but new data showed it was actually 6.6% -- half the level that they originally estimated).
It's also important to note that historically, improvements in drug discovery technology have not correlated with improved R&D productivity -- Eroom's Law states that R&D productivity is on a cyclical decline even despite massive improvements in technology. There is an argument to be made that some of the observed stabilization / modest improvement in R&D productivity is due to a friendlier FDA, better / more focused clinical trial design, or other factors rather than just improving tech.
Overall as Frank said you can't rely on any general dataset for POS -- recent or historical -- you have to look in detail at the drug in question, the target, the development plan, trial design etc. And you'll never be able to accurately predict the POS of any novel target or technology. For practical purposes I find it easier to try to figure out what POS the market prices in and then see whether I disagree or agree strongly with that. If I have to squint to see if my POS differs from consensus then I usually move on to an idea where I have a more differentiated view. If you like an investment but your conviction isn't super high (maybe you have a lot of uncertainty about the POS), you can account for that uncertainty in the size of your position (if you aren't super confident in an investment, but think it's still worth doing, just make it a smaller investment and vice versa -- ie bet your edge).
Hey Richard thank you so much for the amazing content! Could you please do a video on the development and pricing of zolgensma?
Anything specific about the development of it? I touched on pricing of Zolgensma at the end of this blog post: www.baybridgebio.com/blog/most_expensive_drug.html
Let me know if there are other questions on pricing
@@baybridgebio2576 Thank you richard you're the best
Goat 🐐 Thanks for the informational video!!!
Very awesome video and great contents in your Channel ! thanks for sharing , a fellow creator ! subbed ! )