Eroom's Law is Moore's Law spelled backwards. It's the bitter name in the pharma industry for the fact that R&D costs per drug have been steadily rising since the 1950's.
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The famous Nature review article "Diagnosing the decline in pharmaceutical R&D efficiency" offers a model as to why. http://lukemuehlhauser.com/wp-content/uploads/Scannell-Diagnosing-hte-decline-in-pharmaceutical-RD-efficiency.pdf …
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Drug development is a series of experimental filters (the pipeline) that narrow down a huge collection of potential molecules to the few that actually can be used to treat a disease.
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The development of high-throughput screening in the 90's automated the first few and allowed us to test far more molecules in parallel. BUT, the chance that any compound succeeds in clinical trials has been CONSTANT since the 1950's.
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The funnel has been made at least a thousand times larger; initial screens now look at millions of compounds, compared to thousands in the days before HTS.
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Since there's been no improvement in the rate of clinical trial success, this tells us that the highly automated modern preclinical pipeline is thousands of times *less predictive* than the old manual process was.
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The authors cite "molecular reductionism" as a related problem. "Nearly all drugs are sold with a biological story...“drug x works by binding receptor a, which influences pathway b, which adjusts physiological process c, which alleviates disease d.”"
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Obviously, most hypotheses of this form turn out to be false. A drug discovery process that starts with screening for molecules that bind a target will be futile if the disease does not depend solely on that target (which is usually the case.)
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Of course, this is what target validation is meant to discern, and there's a lot of good science in this field. But failure is normal in science.
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The target-based paradigm means that, for instance, basic researchers were making discoveries that raised doubts about the amyloid hypothesis of Alzheimer's *decades* before amyloid-targeting Alzheimer's drugs failed in the clinic. That's expensive.
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