Jack Scannell (@jackscannell13) 's Twitter Profile
Jack Scannell

@jackscannell13

Science, drugs, money: Interested in making better R&D decisions

ID: 1243566771770216448

calendar_today27-03-2020 15:53:32

208 Tweet

1,1K Followers

101 Following

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

I like the Freeman Dyson version: "In the days when I was a physicist, I could lie in the bath and think things out from first principles. In biology, I have to keep getting out of the bath to look up the facts."

Adam Gries -📍Vitalist Bay April 4-May 29🧬 (@adamgries) 's Twitter Profile Photo

+ 51 new speakers added to Vitalist Bay in Berkeley, CA. The world's biggest longevity event! Join us, starting with Unlimited Health Conference, from next Saturday April 5th, to April 7th. At Vitalist Bay, you'll have the healthiest time of your life!

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

Longevity is having a moment.... I've come late to the classic Olshanksy analyses of mortality rates at different ages: We've already done a great job beating the diseases that cause early death, so we now mostly die from diseases whose risks all increase massively with age. That

David Shaywitz (@dshaywitz) 's Twitter Profile Photo

Thanks for input Jack - I think this is where the view of metabolic dysfunction/chronic inflammation comes in, with view that Peter Attia’s “4 horsemen” are exacerbated by this, and potentially mitigated by improvements in diet (& decr IR) and exercise… Daniel J Drucker

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

AI can't "solve" all diseases for the simple reason that all diseases were solved by computational chemistry in 1985, by high throughput screening in 1995, by genomics in 2000, by RNAi in 2004, by stem cells and nanotechnology in 2005, before being solved by CRISPR in 2015.

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

Value in biopharma R&D is sensitive to decision quality. So it should be a surprise that current DCF models confuse bad decisions to keep bad candidates with good decisions to keep good ones. John Mellnik and I have a pre-print which puts decision quality into valuation.

Value in biopharma R&D is sensitive to decision quality. So it should be a surprise that current DCF models confuse bad decisions to keep bad candidates with good decisions to keep good ones. John Mellnik and I have a pre-print which puts decision quality into valuation.
Jack Scannell (@jackscannell13) 's Twitter Profile Photo

Horse racing or biotech investing? In an "accumulator" you bet on several races, get paid if all your horses win, with the payout calculated by multiplying the odds in each race. This makes sense because the races are statistically independent. Biopharma valuation uses

Horse racing or biotech investing? In an "accumulator" you bet on several races, get paid if all your horses win, with the payout calculated by multiplying the odds in each race. This makes sense because the races are statistically independent. Biopharma valuation uses
Jack Scannell (@jackscannell13) 's Twitter Profile Photo

Today I am experiencing "LinkedIntäuschung"; the feeling of disappointment when someone connects with you on a social network, only to immediately pitch an unwanted service or software product.

Patrick Schwab (@schwabpa) 's Twitter Profile Photo

One of the most common (and most attractive for human decision makers) mistakes in drug discovery is to assume correlation equals causation. It's the intellectual equivalent of recommending people get a hair transplant to live longer, because younger people tend to have more

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

I'll be in the Bay Area from the 1st to the 8th of July, and New York from the 9th to the 12th. DM me if want to meet about my biotech venture (Etheros; enzyme mimetics for inflammation / neurodegeneration) or the R&D productivity work.

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

I visited Axiom recently. Don't know their tech in great detail, but I really like this kind of approach. Lots of AI hype in drug R&D is misplaced because the data are absent and/or crap. Axiom, on the other hand, is serious about manufacturing the data on which the wheels of AI

Jack Scannell (@jackscannell13) 's Twitter Profile Photo

Hi zack chiang check this out for some thoughts on the causes of Eroom's Law (the inverse of Moore's Law which held for biopharma R&D productivity from 1950 to 2010) Dwarkesh Patel george church. Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov 11, 191–200