From banking to big pharma to AI biotech – Alban de La Sablière’s take on JPM and industry trends

Duration:10 mins

Tags: AI / ML


Date:January 31st, 2023


From banking to big pharma to AI biotech – Alban de La Sablière’s take on JPM and industry trends

As a former banker, the head of partnerships at a big pharma company and now Chief Business Officer at an AI biotech, I was able to enjoy this month’s JP Morgan Healthcare Conference from the three most common perspectives that can be found stomping the San Francisco pavement every January.

A return to normality

Of course everyone was happy to be back to live interactions, not only because of how more genuine they feel, but also because of the serendipity that makes you think out of the Zoom box. The newfound cost consciousness did make it feel like numbers were roughly 30% down from the peak – hopefully the hotel rates will follow. 

Owkin attempted a viral street art installation (see above) – but four straight days of heavy rain had better ideas. The masterpiece was instead knocked up in the hotel lobby and has since taken centre stage in Owkin’s new Paris office – and you can learn more about the meaning behind it below.

Without being gloomy, the backdrop was full of caution, with no big announcements, limited scientific excitement and depressed valuation and funding levels. Quantitative easing made a lot of higher beta or cyclical industries' last five year performance look like Berkshire Hathaway’s – safe and always up. In addition, the collective success of the industry in the Covid-19 fight made pharma and biotech stocks a must-have asset class. So what changed and what would trigger a return to better days? The macro environment is improving but some specific industry issues will take more time to digest.

In the face of uncertainty

The dramatic change in the macro and geopolitical environment caught investors by surprise in 2022 just as it seemed that normality was returning after Covid-19. The perfect storm created by geopolitical uncertainty, significant rate hikes and inflation spikes created a fear that the 70s were back (and all those who were there and could provide advice were long retired –at best). However, without commenting on geopolitics, recent economic data is somewhat reassuring on this front, with most large economies somewhat outperforming growth expectations and inflation on the way down. But free money is over, so expect fund flows to come back to an average cycle level, rather than peak.

This might help big pharma stock prices but does not mean biotech will benefit in the same way for two reasons:

As the average biotech sought to fundraise and IPO earlier and earlier, the journey to a company’s major first readout (call it phase 2 proof of concept) has become very distant. Some expect a big M&A wave, driven by attractive prices, could come back to save the day, but looming patent cliffs and inflation are making big pharma hesitant about anything that is not earnings accretive or at least close to approval. The comeback will be gradual, as it will take two to three years to catch up to the normalized maturity of pipelines.

The Inflation Reduction Act is also creating significant uncertainty that is impacting biotech much more than big pharma. Even if some comments about the demise of small molecules are not shared by most VC I met (as all regulations can be adjusted), the comments of large industry players about the impact of IRA on the relative attractiveness of small molecules vs biologics and the rethinking of standard development plans will translate into much more caution about the valuation of earlier stage small molecules.

The year of AI biotech

Anecdotally, the AI biotech mood had more bullish tones. First, having had meetings with most big pharmas, it was clear that all had a very significant investment in AI drug discovery and development and were very clear about how they wanted their R&D platforms to look in five years' time, at least in terms of improved productivity with an objective to cut drug development time by more than 30%. Big pharma is also much more comfortable in handling both the building of internal competencies and partnerships with many having moved from running small proof of concept projects to more ambitious partnerships over the last two to three years. BioNTech seemed even more bullish by acquiring InstaDeep. Historically, pharma companies have been concerned about acquiring businesses in which people and know-how comprised a significant part of their value. This often led pharma companies to try to both build in-house for the long term and partner to catch up, but shy away from straight acquisitions. This can sometimes lead to conflicting objectives and confusion if both routes are not well coordinated, which requires upfront planning. For example, Owkin’s partnership with Sanofi involves not only a joint lab but also the integration of our AI software into Sanofi’s AI platform. 

Will we see more AI biotechs acquisitions – or will those remain limited to more recent and bolder companies that have less concern about integration? One other interesting trend was that most VCs I talked to had a significant AI biotech effort, either through dedicated companies or through in-house efforts that remain stealth but aimed at leading to specific company formations.

The potential of AI to improve all aspects of drug development is now well accepted: there are three main applications: novel target discovery, lead optimization and clinical plan de-risking and acceleration. One of the big questions is regarding the data sets that will drive the best results, especially in target discovery and clinical plan de-risking. At Owkin, we are focusing on rich and deep datasets with the belief that translational approach and ability to directly interrogate biology based on AI findings. Other approaches focus on mining the vast amount of unstructured literature and public data. I think there is no real conflict between these approaches, as you need to have a different approach depending on the disease and the data that is available. Precision medicine approaches by definition require researchers to be as close as possible to the biology of the patient. While a translational approach is the gold standard, the building of complete datasets is fundamental. 

While the return to normality was welcome, the lasting impression from JPM 2023 is one of uncertainty. Whether the disruption of the industry will be ‘Singing in the Rain’ or ‘Babylon’ remains to be seen – but at Owkin, we are confident that the rapid acceleration in the use of AI means that the future is bright. We are investing heavily in AI capabilities, investing in accessing and generating rich multimodal data, working closely with the biopharma industry and connecting the academic world together – all in the pursuit of finding the right treatment for every patient. This year, we are creating the world’s leading AI biotech company, aligning human and artificial intelligence to discover breakthrough treatments. I look forward to being able to share our successes at JPM 2024 – come rain or shine.