Thanks again. I don't want to throw a cliché at you here, but it seems incredibly complex to estimate the value of even 1 product in the pipeline. So many uncertainties: is it effective in phase 3, what does the competition do, what is the expected compensation to name a few. This then times 10-20 to evaluate all phase 3 IMPs. Let alone pre-clinical to phase 2. Not a investor but the current PE ratio doesn't seem to factor in much growth. Most 'standard' metrics are quite conservative compared to other biotechnology companies. Seems like the market sees Regeneron like a potential Moderna/BioNTech?
Yes, I would agree. I make next to no attempt to model REGN's pipeline - I don't think I'd be able to add any value that way. Others do, of course, do it, but as I argue in my deep dive, the sell-side are almost always too bearish on REGN's long-term prospects. Biopharma investing is a somewhat niche/specialist industry and it brings with it the valuation tools that you're 'supposed' to use, but I suspect REGN is better off being treated as a 'compounder' such as you find in other sectors. No doubt some would call me eccentric, but I don't think REGN was expensive even when it was >$1000, looking at it though this lens.
Yes, I can imagine it is hard to 'predict'. My current work is related to chronic kidney disease (CKD). Here a couple of drug classes have been approved the last decade (SGLT2, MRA, GLP-1 agonists among others). Even professors spending 20 years in clinical pharmacology find it challenging to exactly decipher the mechanisms behind these drugs now, let alone predict there effects before they entered phase 2 and 3 clinical trials. Also many phase 3 trials are probably related: similar compounds and indications so you can't just multiply the number of trials by the approval rate for phase 3 trials for a certain disease field or indication (just guessing here:)).
Thanks for sharing David. I don’t know the CKD space well at all, other than GSK’s largely failed efforts with daprodustat. I’m no expert but I wonder if there’s cause for optimism around using machine learning for better understanding mechanisms, targets and the like - in fact GSK is also doing a lot of work in that direction. And for any company that can increase its probability of success, valuation perhaps becomes a bit less of a shot in the dark (or warrants a higher P/E in any case)
Hi David. I believe the FDA typically requires two adequate and well controlled studies to show efficacy and safety. In practice this often means two identical trials to satisfy the requirement.
Thanks. I didn't know. I remember the approval of sparsentan by the FDA which was not according to the two-trial paradigm. Would be interesting to see whether any methodological aspects may have cause the different findings. I understood the recent results were related to an IL-33 antibody.
Thanks again. I don't want to throw a cliché at you here, but it seems incredibly complex to estimate the value of even 1 product in the pipeline. So many uncertainties: is it effective in phase 3, what does the competition do, what is the expected compensation to name a few. This then times 10-20 to evaluate all phase 3 IMPs. Let alone pre-clinical to phase 2. Not a investor but the current PE ratio doesn't seem to factor in much growth. Most 'standard' metrics are quite conservative compared to other biotechnology companies. Seems like the market sees Regeneron like a potential Moderna/BioNTech?
Yes, I would agree. I make next to no attempt to model REGN's pipeline - I don't think I'd be able to add any value that way. Others do, of course, do it, but as I argue in my deep dive, the sell-side are almost always too bearish on REGN's long-term prospects. Biopharma investing is a somewhat niche/specialist industry and it brings with it the valuation tools that you're 'supposed' to use, but I suspect REGN is better off being treated as a 'compounder' such as you find in other sectors. No doubt some would call me eccentric, but I don't think REGN was expensive even when it was >$1000, looking at it though this lens.
Yes, I can imagine it is hard to 'predict'. My current work is related to chronic kidney disease (CKD). Here a couple of drug classes have been approved the last decade (SGLT2, MRA, GLP-1 agonists among others). Even professors spending 20 years in clinical pharmacology find it challenging to exactly decipher the mechanisms behind these drugs now, let alone predict there effects before they entered phase 2 and 3 clinical trials. Also many phase 3 trials are probably related: similar compounds and indications so you can't just multiply the number of trials by the approval rate for phase 3 trials for a certain disease field or indication (just guessing here:)).
Thanks for sharing David. I don’t know the CKD space well at all, other than GSK’s largely failed efforts with daprodustat. I’m no expert but I wonder if there’s cause for optimism around using machine learning for better understanding mechanisms, targets and the like - in fact GSK is also doing a lot of work in that direction. And for any company that can increase its probability of success, valuation perhaps becomes a bit less of a shot in the dark (or warrants a higher P/E in any case)
Well I hope the combination of new drugs will give companies like DaVita a run for their money by reducing the number of CKD patients on dialysis :)
Recommend to read this short column if you don't know it by Derek Lowe:
https://www.science.org/content/blog-post/end-disease
Although it might indeed make make pre-clinical work more efficient, he thinks it is far from replacing the current process.
Interesting day today. Any idea why REGN initiated two phase 3 trials for COPD? Also, I can't find the publications yet.
Hi David. I believe the FDA typically requires two adequate and well controlled studies to show efficacy and safety. In practice this often means two identical trials to satisfy the requirement.
Headline results were published yesterday but won’t be presented in detail until later: https://investor.regeneron.com/news-releases/news-release-details/itepekimab-met-primary-endpoint-one-two-chronic-obstructive
Just in case you don’t follow closely, I should also note this is completely separate to Dupixent’s existing approval in COPD - different drug.
Thanks. I didn't know. I remember the approval of sparsentan by the FDA which was not according to the two-trial paradigm. Would be interesting to see whether any methodological aspects may have cause the different findings. I understood the recent results were related to an IL-33 antibody.
*their