Atom­wise inks Chi­na deal as list of AI col­lab­o­ra­tions length­ens

The long list of ma­jor AI bio­phar­ma col­lab­o­ra­tions has got­ten longer as one of the first ar­ti­fi­cial in­tel­li­gence star­tups has inked its first deal in Chi­na.

San Fran­cis­co-based start­up Atom­wise has signed an agree­ment to de­vel­op tar­get­ed drugs with Han­soh Phar­ma­ceu­ti­cals, a deal that could ul­ti­mate­ly be worth up to $1.5 bil­lion. Han­soh is flush with cash af­ter a $1 bil­lion IPO on the Hong Kong ex­change in June.

The promise of ma­chine learn­ing to speed up pre­clin­i­cal work and save de­vel­op­ers mil­lions of dol­lars has led to a string of new col­lab­o­ra­tions be­tween a hand­ful of soft­ware star­tups and some of the biggest drug de­vel­op­ers and re­search in­sti­tu­tions in­clud­ing Mer­ck, As­traZeneca, J&J, Bris­tol-My­ers Squibb, Pfiz­er and Duke Uni­ver­si­ty School of Med­i­cine. They’ve agreed to work on re­search rang­ing from on­col­o­gy to chron­ic dis­ease.

Part of the swarm like­ly comes from the hype that pe­ri­od­i­cal­ly sur­rounds a new tech­nol­o­gy — and few words are buzzi­er right now in both tech and pop­u­lar cul­ture than “ar­ti­fi­cial in­tell­gien­ce” and “ma­chine learn­ing” — and that has con­cerned some key fig­ures in phar­ma­ceu­ti­cal de­vel­op­ment. But al­though it’s too ear­ly for the AI plat­forms to have brought a drug to mar­ket, ear­ly stud­ies have in­di­cat­ed there could be some­thing be­neath the buzz. That in­cludes last week’s land­mark study from In­sil­i­co in Na­ture Biotech­nol­o­gy, in which over 21 days the com­pa­ny found six mol­e­cules that could be po­ten­tial treat­ments for fi­bro­sis.

At its most ba­sic, ar­ti­fi­cial in­tel­li­gence works like this: You feed an AI sys­tem a vast num­ber of, say, im­ages of a cow and im­ages not of a cow, and you tell it which is which. With each im­age of a cow and not-cow, the AI de­vel­ops a more and more re­fined set of cri­te­ria for what con­sti­tutes a cow (even if that cri­te­ria is far dif­fer­ent from what a hu­man might give). Pret­ty soon it can very ac­cu­rate­ly rec­og­nize whether a new pic­ture has a cow or not. You can al­so do this with, say, an im­age of your mom. It’s how your iPhone’s fa­cial recog­ni­tion works.

And you can do this with a mol­e­cule.

Atom­wise works by what’s called “vir­tu­al screen­ing,” mean­ing it us­es its AI sys­tem to rapid­ly search data­bas­es for mol­e­cules that re­sem­ble what its part­ners are look­ing for. Its June part­ner­ship with Ukraine-based Et­a­mine, the world’s largest chem­i­cal sup­pli­er, gives it ac­cess to a data­base of bil­lions of com­pounds to scan. Atom­wise can scan 10-20 mil­lion per day, up from con­ven­tion­al com­put­er meth­ods that cap out at about 100,000. This lat­est deal with Han­soh will see the com­pa­ny de­sign and dis­cov­er drugs for 11 undis­closed tar­get pro­teins.

How­ev­er, the In­sil­i­co study that grabbed head­lines was for a slight­ly dif­fer­ent form of AI.

This new­er AI, on­ly put forth in 2014, goes fur­ther. Rather than rec­og­niz­ing a face, it can imag­ine a face (or, say, art). The idea In­sil­i­co is bet­ting on and get­ting close to prov­ing is that if it can imag­ine a face, it can imag­ine a drug. Ac­cord­ing­ly, these are called “gen­er­a­tive” net­works, as op­posed to the “con­vo­lu­tion­al” ones Atom­wise us­es.

We’ll use cows again for the mod­el. These new AIs ac­tu­al­ly con­sist of two sys­tems. Loaded with da­ta, the “gen­er­a­tive” one at­tempts to come up with an im­age of a cow. Then a sec­ond one, which is called the “dis­crim­i­na­tor” and works likes the tech de­scribed above, tells the gen­er­a­tive one if it got a cow or not. The gen­er­a­tor learns from the dis­crim­i­na­tor, which learns from the vast store of up­loaded in­for­ma­tion. You have a learn­ing feed­back loop that should even­tu­al­ly gets you a brand new pret­ty pic­ture of a cow.

In the In­sil­i­co study, they were search­ing for a new ty­ro­sine ki­nase in­hibitor for dis­coidin do­main re­cep­tor 1 (DDR1). The sys­tem was taught all DDRI lit­er­a­ture, a larg­er set of ki­nase in­hibitors, data­bas­es of med­i­c­i­nal­ly ac­tive struc­tures and a data­base of struc­tures that have al­ready been patent­ed. The re­sult? 30,000 can­di­date struc­tures, which the com­pa­ny then whit­tled down to 40. They pro­duced 6 of them in the lab, test­ed 2 of them on cells and one on mice.

Promi­nent sci­ence writer and not­ed skep­tic of biotech AI hype Derek Lowe damp­ened the ex­u­ber­ant head­lines, not­ing the DDRI is al­ready well re­searched (cre­at­ing an ide­al sam­ple size to train the neur­al net­works), the dis­cov­er­ies weren’t drugs but pos­si­ble drug tar­gets, and gen­er­al­iz­ing these tech­niques to oth­er drug ar­eas will take years and lots of cash. This ac­cords with a con­sen­sus view of the tri­al as a proof-of-con­cept. Still, he found it one of the most in­ter­est­ing pa­pers he had read on vir­tu­al screen­ing.

“The good news, though, is that there is no rea­son that vir­tu­al screen­ing can’t do great things, even­tu­al­ly,” he wrote in his blog, In the Pipeline. “We just have to get a lot bet­ter at it than we are now, and that’s as true as it was when I first heard about it in the mid-1980s.”

Patrik Jonsson, the president of Lilly Bio-Medicines

Who knew? Der­mi­ra’s board kept watch as its stock price tracked Eli Lil­ly’s se­cret bid­ding on a $1.1B buy­out

In just 8 days, from December 6 to December 14, the stock jumped from $7.88 to $12.70 — just under the initial $13 bid. There was no hard news about the company that would explain a rise like that tracking closely to the bid offer, raising the obvious question of whether insider info has leaked out to traders.

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2019 Trin­i­ty Drug In­dex Eval­u­ates Ac­tu­al Com­mer­cial Per­for­mance of Nov­el Drugs Ap­proved in 2016

Fewer Approvals, but Neurology Rivals Oncology and Sees Major Innovations

This report, the fourth in our Trinity Drug Index series, outlines key themes and emerging trends in the industry as we progress towards a new world of targeted and innovative products. It provides a comprehensive evaluation of the performance of novel drugs approved by the FDA in 2016, scoring each on its commercial performance, therapeutic value, and R&D investment (Table 1: Drug ranking – Ratings on a 1-5 scale).

How to cap­i­talise on a lean launch

For start-up biotechnology companies and resource stretched pharmaceutical organisations, launching a novel product can be challenging. Lean teams can make setting a launch strategy and achieving your commercial goals seem like a colossal undertaking, but can these barriers be transformed into opportunities that work to your brand’s advantage?
We spoke to Managing Consultant Frances Hendry to find out how Blue Latitude Health partnered with a fledgling subsidiary of a pharmaceutical organisation to launch an innovative product in a
complex market.
What does the launch environment look like for this product?
FH: We started working on the product at Phase II and now we’re going into Phase III trials. There is a significant unmet need in this disease area, and everyone is excited about the launch. However, the organisation is still evolving and the team is quite small – naturally this causes a little turbulence.

FDA’s golodirsen CRL: Sarep­ta’s Duchenne drugs are dan­ger­ous to pa­tients, of­fer­ing on­ly a small ben­e­fit. And where's that con­fir­ma­to­ry tri­al?

Back last summer, Sarepta CEO Doug Ingram told Duchenne MD families and investors that the FDA’s shock rejection of their second Duchenne MD drug golodirsen was due to some concerns regulators raised about the risk of infection and the possibility of kidney toxicity. But when pressed to release the letter for all to see, he declined, according to a report from BioPharmaDive, saying that kind of move “might not look like we’re being as respectful as we’d like to be.”

He went on to assure everyone that he hadn’t misrepresented the CRL.

But Ingram’s public remarks didn’t include everything in the letter, which — following the FDA’s surprise about-face and unexplained approval — has now been posted on the FDA’s website and broadly circulated on Twitter early Wednesday.

The CRL raises plenty of fresh questions about why the FDA abruptly decided to reverse itself and hand out an OK for a drug a senior regulator at the FDA believed — 5 months ago, when he wrote the letter — is dangerous to patients. It also puts the spotlight back on Sarepta $SRPT, which failed to launch a confirmatory study of eteplirsen, which was only approved after a heated internal controversy at the FDA. Ellis Unger, director of CDER’s Office of Drug Evaluation I, notes that study could have clarified quite a lot about the benefit and risks associated with their drugs — which can cost as much as a million dollars per patient per year, depending on weight.

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Aymeric Le Chatelier, Ipsen

A $1B-plus drug stum­bles in­to an­oth­er big PhI­II set­back -- this time flunk­ing fu­til­i­ty test -- as FDA hold re­mains in ef­fect for Ipsen

David Meek

At the time Ipsen stepped up last year with more than a billion dollars in cash to buy Clementia and a late-stage program for a rare bone disease that afflicts children, then CEO David Meek was confident that he had put the French biotech on a short path to a mid-2020 launch.

Instead of prepping a launch, though, the company was hit with a hold on the FDA’s concerns that a therapy designed to prevent overgrowth of bone for cases of fibrodysplasia ossificans progressiva might actually stunt children’s growth. So they ordered a halt to any treatments for kids 14 and under. Meek left soon after to run a startup in Boston. And today the Paris-based biotech is grappling with the independent monitoring committee’s decision that their Phase III had failed a futility test.

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Roche's check­point play­er Tecen­triq flops in an­oth­er blad­der can­cer sub­set

Just weeks after Merck’s star checkpoint inhibitor Keytruda secured FDA approval for a subset of bladder cancer patients, Swiss competitor Roche’s Tecentriq has failed in a pivotal bladder cancer study.

The 809-patient trial — IMvigor010 — tested the PD-L1 drug in patients with muscle-invasive urothelial cancer (MIUC) who had undergone surgery, and were at high risk for recurrence.

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Stephen Hahn, AP

The FDA has de­val­ued the gold stan­dard on R&D. And that threat­ens every­one in drug de­vel­op­ment

Bioregnum Opinion Column by John Carroll

A few weeks ago, when Stephen Hahn was being lightly queried by Senators in his confirmation hearing as the new commissioner of the FDA, he made the usual vow to maintain the gold standard in drug development.

Neatly summarized, that standard requires the agency to sign off on clinical data — usually from two, well-controlled human studies — that prove a drug’s benefit outweighs any risks.

Over the last few years, biopharma has enjoyed an unprecedented loosening over just what it takes to clear that bar. Regulators are more willing to drop the second trial requirement ahead of an accelerated approval — particularly if they have an unmet medical need where patients are clamoring for a therapy.

That confirmatory trial the FDA demands can wait a few years. And most everyone in biopharma would tell you that’s the right thing for patients. They know its a tonic for everyone in the industry faced with pushing a drug through clinical development. And it’s helped inspire a global biotech boom.

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UP­DAT­ED: New play­ers are jump­ing in­to the scram­ble to de­vel­op a vac­cine as pan­dem­ic pan­ic spreads fast

When the CNN news crew in Wuhan caught wind of the Chinese government’s plan to quarantine the city of 11 million people, they made a run for one of the last trains out — their Atlanta colleagues urging them on. On the way to the train station, they were forced to skirt the local seafood market, where the coronavirus at the heart of a brewing outbreak may have taken root.

And they breathlessly reported every moment of the early morning dash.

In shuttering the city, triggering an exodus of masked residents who caught wind of the quarantine ahead of time, China signaled that they were prepared to take extreme actions to stop the spread of a virus that has claimed 17 lives, sickened many more and panicked people around the globe.

CNN helped illustrate how hard all that can be.

The early reaction in the biotech industry has been classic, with small-cap companies scrambling to headline efforts to step in fast. But there are also new players in the field with new tech that has been introduced since the last of a series of pandemic panics that could change the usual storylines. And they’re volunteering for a crash course in speeding up vaccine development — a field where overnight solutions have been impossible to prove.

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Wuhan virus out­break trig­gers in­evitable small-biotech ral­ly

Every few years, a public health crisis (think Ebola, Zika) spurred by a rogue pathogen triggers a small-biotech rally, as drugmakers emerge from the woodwork with ambitious plans to treat the mounting outbreak. In most cases, that enthusiasm never quite delivers.

Things are no different, as the coronavirus outbreak in Wuhan, China takes hold. There have been close to 300 confirmed human infections in China, and at least four deaths. Coronaviruses are a large family of viruses, which include MERS and SARS. On Tuesday, the CDC reported the virus was detected in a US traveler returning from Wuhan.