Posted by storybored
https://www.metafilter.com/210242/Where-are-the-Trillion-Dollar-Biotechs
The Dismal Economics of Bio-Tech Research. A long, detailed analysis of why biotech research is still hard. "Human genetics, drug repurposing, and AI are the most common levers [cited to improve things], and each promises to cut costs or derisk pipelines. But the more you look into specific companies and their stories, the more you notice that these strategies rarely work. This is especially true once you turn to age-related diseases, the only market large enough to rescue pharma's economics, yet the one where our best heuristics work the least."
"There are also plenty of examples of selecting a genetically validated target, often outside of oncology or CNS, and failing over and over again to deliver on the promise. CETP variant was enriched in centenarian cohorts and showed coronary heart disease reduction in people with the variant, yet 4 different drugs failed in early-stage trials (likely asset-specific failure). MSTN inhibition leads to obvious muscle mass gains, yet there were 4 failed MSTN antibodies before Scholar Rock got apitegromab approved earlier this year (indication/trial design failure). The list goes on and on. "
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"One number that is worth appreciating is that 80% of all costs associated with bringing a drug to market come from clinical-stage work. That is, if we ever get to molecules designed and preclinically validated in under 1 year, we'll be impacting only a small fraction of what makes drug discovery hard. This productivity gain cap is especially striking given that the majority of the data we can use to train models today is still preclinical, and, in most cases, even pre-animal. A perfect model predictive of in vitro tox saves you time on running in vitro tox (which is less than a few weeks anyway!), doesn't bridge the in vitro to animal translation gap, and especially does not affect the dreaded animal-to-human jump. As such, perfecting predictive validity for preclinical work is the current best-case scenario for the industry. Though we don't have a sufficient amount and types of data to solve even that. "
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Probability of Success by Clinical Trial Phase and Therapeutic Area. (P1 = Phase 1)
Therapeutic AreaP1 to P2P2 to P3P3 to ApprovalOverall
Oncology57.632.735.53.4
Metabolic/Endocrinology76.259.751.619.6
Cardiovascular73.365.762.225.5
Central Nervous System73.251.951.115.0
Autoimmune/Inflammation69.845.763.715.1
Genitourinary68.757.166.521.6
Infectious Disease70.158.375.325.2
Ophthalmology87.160.774.932.6
Vaccines (Infectious Disease)76.858.285.433.4
Overall66.448.659.013.8
Overall (Excluding Oncology)73.055.763.620.9
https://www.metafilter.com/210242/Where-are-the-Trillion-Dollar-Biotechs