Six takeaways from JP Morgan 2024

With another JP Morgan in the rearview mirror, it’s time to take stock of the announcements, the presentations, and, above all, the vibes. While the event and its attendant satellite events comprise more content than anyone could ever consume, it also serves an important function to align goals and expectations for the year to come.

So. for those of you who couldn’t make it, or those of you who were there, but your head’s still spinning, here are my six big takeaways from the show. (And if you're looking for more coverage, you can still check out our archived live blog.)

#1. Dealmaking is back on the menu (at least for late-stage assets)

I’ve been working on my own 2024 predictions piece (still to come) and I started doing calls for that in mid-December. At that point, I was hearing doom and gloom about M&A reminiscent of 2023’s JP Morgan. 

But then the industry got an early Christmas present in the form of news that BMS was acquiring Karuna Therapeutics for $14 billion, followed by RayzeBio for $1.4 billion. Then AstraZeneca put up $1.2 billion for Gracell. Then, at the show itself, J&J, Novartis, and MSD all kicked in the door with acquisition announcements, as did GSK.

At this point, predicting a big year for acquisitions seems reminiscent of Mean Girls’ Karen Smith telling us there’s a 60% chance it’s already raining.

Nonetheless, there are lots of reasons to believe more acquisitions are coming, and there seemed to be a consensus on that at JPM. The headwinds make sense: big pharma has a lot of dry powder and is facing a patent cliff over the next few years, along with the still-uncertain effects of the Inflation Reduction Act (IRA). Diversifying portfolios with more assets is the best hedge they have and, with the economy on an upturn, prices might be as good right now as they’re going to get for a while.

If you’re looking to diversify your pipeline to fortify against looming threats, however, you’re going to be looking to buy late-stage, de-risked assets, and that’s exactly what experts predict will constitute the bulk of the deals.

By the way, there is certainly some trepidation about the FTC’s recent attitude. But investors on stage seemed to agree that, while it was likely to loom large in the back of acquisitors’ minds, it wasn’t likely to stop them from looking for and moving on deals.

If you want to go really deep on what 2024 M&A might look like, this survey from Syneos Health has a lot more, including therapeutic areas and IPOs. 

#2. Big tech is more than dipping its toe into life sciences, but they’re not going alone

Chipmaker NVIDIA announced a major push into Generative AI (GenAI) for drug discovery, working with high-profile partners like Recursion and Amgen. The demos were impressive and it was clear from CEO Jensen Huang’s fireside chat that the company is deeply invested in the vertical. Alphabet spinout Isomorphic Labs signed big-dollar deals with Eli Lilly and Novartis for AI drug hunting. And Amazon marched on with its gradual push into healthcare, announcing a programme with digital health stalwart Omada Health that takes the company into the chronic condition management space.

Big tech has been wading into healthcare for a while, sometimes falling on its face in the process (does anyone remember Haven?) and sometimes finding a measure of success (FDA-cleared health tracking on the Apple Watch and Amazon’s telehealth push, to name a couple.)

At one memorable panel at Fierce JPM Week, Vivodyne CEO Abraham Heifets described how tech and pharma are almost opposites in how they do business: tech companies secure a first-mover advantage early, then dominate the space for as long as they can, reinvesting to stay ahead of the competition (think Google in search, Amazon in commerce, Apple in mobile devices); pharma companies, on the other hand, have to extract value quickly from their leadership positions and then be ready with the next thing when they lose exclusivity. 

Healthcare requires specialised knowledge and specialised, robust datasets, whereas the AI leaps forward in consumer tech have happened on the back of broad, publicly available datasets of sometimes dubious quality. Tech people move fast and break things; healthcare can’t afford that kind of risk-taking.

All in all, it makes sense that the big tech announcements we saw this year were all rooted in partnerships, with big tech not trying to go it alone or reinvent healthcare, but rather bring their own expertise to bear in enhancing it, in partnership with experts who know the territory.

3. Everyone’s talking about AI. But only some people have anything to say.

Look, of course AI was going to be the topic du jour this year at JP Morgan. But for good reason: 2023 was the year that AI became table stakes for life sciences companies. Certainly, everyone needs a strategy for using AI in drug development. But applications go way beyond that, especially with the advent of large language models (LLMs). There are AI applications starting to transform the whole R&D value chain, from clinical trial recruitment to protocol writing and study design, and to data collection and analysis. Not to mention applications on the commercial side and in medical affairs, particularly for GenAI.

It's no longer enough to say, “We use AI.” What are you using AI for? Are your models high-quality? Are they trained on high-quality data? How are you solving for bias and hallucination? AI winners and losers will emerge based on companies’ ability to answer those questions. The strength of ChatGPT is that anyone can use it, but that makes it inherently commodified. The question pharma companies have to answer is, “What can my AI application do that Chat GPT can’t?”

I’m planning to dive more deeply into this in my predictions piece, so, stay tuned for that next week.

4. Answers are starting to emerge to cell and gene therapies’ big questions

If the most discussed topic at JP Morgan was AI, cell and gene therapy may have been the second-most-discussed. With the meeting coming just a month after the FDA’s landmark approval of two gene therapies for sickle cell disease, perhaps it’s no surprise that it was top of mind.

There are a number of approvals expected this year for cell and gene therapy, but the big news, such as it is, is that the big questions around business model and implementation are starting to be answered. Payers are recognising the lifetime value of these therapies and accepting the large price tags associated with curative cell and gene therapies – an,d often, the outcomes-based arrangements they come with. Biotechs are building out their networks of experienced treatment centres to administer these treatments. Bespoke CROs and CDMOs are working to solve manufacturing and development challenges.

I did a whole article on FDA CBER Director Dr Peter Marks’ talk where he focused exclusively on the potential for gene therapy and the FDA’s commitment to it. 

There is optimism and positive energy around cell and gene therapy, but the hurdles are far from cleared. And some of the start-ups working in that space may not make it if the various pieces don’t move fast enough. Andrew Obershain, CEO of bluebird bio, said as much on stage. A year before the FDA approved his company’s gene therapy for sickle cell, he was telling reporters that the company was running out of runway and might shut down.

"Not every company is going to make it," he said. "There's going to be a winnowing down, some of it fair, some of it not fair. But that's how innovation goes down."

5. ADCs are poised for a third act

Antibody-drug conjugates were a somewhat unexpected star of the show, but the space is in an interesting spot. After a promising beginning and a notable trough of disillusionment, they’ve emerged as a major bright spot in oncology research and a space that continues to brim with potential.

One of the best single talks of the show for me was Daiichi Sankyo CEO Ken Keller, who told the story of how his company restructured around oncology when it became apparent how much opportunity was in ADCs. 

“The success of Enhertu has put a new kind of feeling into this space," he said. "In 2013, there were 32 trials in this space. Last year there were over 300 [...] So, something that was thought of as old has truly become the hot new thing. And now that we've cracked the code on these ADCs, the sky's the limit."

In the Syneos report I mentioned above, oncology was the top area of interest for potential buyers and antibody-drug conjugates were tied with machine learning-derived drugs as the hottest area of interest for acquirers. JP Morgan’s 2023 report, which came out at the start of the conference, tells the same story, with ADCs making up the biggest deals of the year.

Cell and gene therapy may be leading on hype, but ADCs are moving into that final stage of the Gartner hype cycle. Stay tuned for my interviews with Genmab and Takeda, which also focused on this topic.

6. A real world evidence paradigm shift is coming… Eventually

AI has made it possible to use synthetic data to replace the placebo arm in drug trials, something that is increasingly necessary, as the drugs with accelerated approvals struggle to recruit for post-market studies and maintain the integrity of their placebo groups. As Tracy Hayne from Slipstream IT put it, we shouldn’t be expecting people to voluntarily put their lives on the line for science, but that’s what we’re asking 50% of people to do when we enrol an RCT of a drug that’s already in the market. 

Synthetic controls also have a lot of advantages over placebos – they’re cheaper, they can be much easier to put together for rare disease cohorts, and they can even provide more expansive data than clinical trials when it comes to investigating safety protocols.

The big hurdle for synthetic controls is the FDA. Though parts of the agency are very supportive of real-world evidence (RWE) and synthetic controls, they’re treating the space with understandably strict scrutiny. Until more trials have been completed this way and accepted by the agency, there’s a hesitancy to pursue this pathway. But there have been a few successes and there are more underway that could tip that scale.

Of course, synthetic trial arms are just one application of RWE – better algorithms and better data are also poised to have profound effects on things like post-market safety monitoring, clinical trial recruitment, and site selection. Once we build the guard rails on real-world data and everyone, including regulators, learns to trust it, it should lead to a huge shift in how the work of pharma R&D is done.