During BIO this year, I had a chance to moderate a panel among some of the top tech experts in biopharma on their real-world use of artificial intelligence in R&D. There’s been a lot said about the potential of AI, but I wanted to explore more about what some of the larger players are actually doing with this technology today, and how they see it advancing in the future. It was a fascinating exchange, which you can see here. The transcript has been edited for brevity and clarity. — John Carroll

As a co-inventor of sildenafil — a pill originally designed to treat coronary hypertension — David Brown knows how big of an impact drug hunters can make when they take a therapy being used to treat one disease and direct it to another. After 40 years in the industry, repurposing is at the center of his latest rare disease venture at Healx.

And now, stepping the gas pedal on new discovery projects, Brown has recruited Neil Thompson as the Cambridge, UK-based startup’s new CSO.

Oxford is allying itself with Evotec and artificial intelligence outfit Sensyne Health to ramp up some new biotech spinouts while looking to “accelerate data-driven drug discovery and development.”

The big idea here is that Oxford scientists — some of the best drug hunters in the world — can utilize Sensyne’s AI platform for their work, relying on the chemists and hands-on developers at Evotec to push ahead to a critical proof of concept moment. And they’ll do it through a project leader called LAB10x, which gets £5 million over the next three years to fund the work.

As a biotech exec with a background in computational chemistry, Rosana Kapeller has been watching the hubbub over artificial intelligence and machine learning in biopharma play out with a considerable degree of skepticism.

“People talk about ML and AI without knowing what they are talking about,” the outspoken Nimbus alum told me earlier in the week. And there are some big pitfalls the uninitiated are likely to drop into without warning if they follow the crowd into AI without thinking things through first. 

When it comes to using artificial intelligence to speed up drug discovery and development, the former may be grabbing the most attention with the crop of AI upstarts vowing to find better candidates faster and cheaper, but the possibility of accelerating existing clinical programs is equally enticing — if less visible — to the biopharma industry.

That’s at least part of the rationale behind Perceptive Advisors’ $40 million infusion into Saama, a software company selling a clinical data analytics platform powered by AI.

Celgene clearly isn’t waiting in limbo to see when, or if, the big Bristol-Myers Squibb deal will go through. It’s still executing deals, and the R&D side of the business has just enlisted one of the more prominent AI players to go to work on a trio of new drug projects in oncology and immunology. They’re paying $25 million up front to get the tech party started.

Celgene, a top 15 R&D group worldwide by research budget, tied up with Exscientia in Oxford, UK for the work. We aren’t getting any specifics about the targets, but the company is exploring AI to see how it lives up to the emerging field’s big boast: That they can deliver new drugs for human testing faster and more accurately than the standard industry approach the big players have been using. In Celgene’s case, that would commonly mean going out and doing a discovery deal with a biotech, but the majors also have their own in-house operations.

Beset with setbacks, a once cash-poor Agenus had something to cheer late last year when behemoth Gilead signed on as a partner on up to five of its immuno-oncology programs. On Tuesday, the biotech offered investors an intriguing proposal: fund the development of a single drug, while preserving shareholder equity.

In perhaps the first instance of a biopharma company conducting such a ‘digital security’ offering, Agenus said it was launching a token  designed to enable qualified investors to directly invest in a single biotech product – in this case, the tokens issued will represent a portion of potential future US sales of AGEN2034, Agenus’ late-stage anti-PD-1 antibody.

Since Vas Narasimhan’s Day 1 as CEO of Novartis, he has championed data science and digital technologies as a key priority at the pharma giant. Almost a year into his tenure, in a recent conversation with the tech VC firm Andreessen Horowitz, he highlighted the abilities to analyze pathology images and centralize clinical trial planning as two promising applications of machine learning.

But, he admitted, there are areas where it’s “simply not met up”:

Some of the earliest connections Alex Zhavoronkov has built for his AI shop at Insilico Medicine involves marrying anti-aging and AI research, two of the buzziest areas in drug development. He’s now doubling down on it with a new R&D partnership with “young blood” startup Elevian.

The collaboration is aimed at developing oral medications targeting the GDF11, or growth differentiation factor 11, pathway and associated targets — a concept that Elevian has been working on since inception. Elevian is supplying the biological and structural target data that Insilico will use to identify small molecules via its generative adversarial networks (GANs) and reinforcement learning (RL) AI technologies.