You could feel the buzz of innovation in the air when top minds from science and industry came together for the second annual #GenAI4Pharma NYC at Cure’s Manhattan headquarters. Here’s how they see AI transforming pharma in the short and long-term, to save time, money — and lives.
AI will enable simulation of human cells in experiments.
“Biology is such an exciting space for AI because there are these field-wide efforts to generate data. One thing we can really count on over the coming years is an even more unprecedented map of the codes of life and of biology. And the other thing that we can count on is the cost of compute falling and the flops [floating point operations per second] doubling every two years. You can think of the possibilities there, as you bring more and more types of data. I think a really big area is going to be single cell data, because we can collect information about cellular states at scale. You can imagine models that are not only reasoning over proteins but reasoning over genomes, and not just reasoning over sequences, but reasoning over cellular states, and building a virtual cell, where you'd be able to simulate a cell in silica, rather than having to do experiments in the lab.” — Alex Rives, PhD, Chief Scientist, EvolutionaryScale, an AI-powered protein-generating technology
AI will level the playing field for women’s health.
“Women were not required to be in clinical trials in the US until 1993, and that was only in federally funded studies, so we really have a data gap when it comes to gender. If you look at the cell models we're using for research, most of those are male cells. And we're predominantly using male mice because they’re less expensive than female mice. We need to do a better job of looking at sex-based differences, because that could be the reason 80 percent of autoimmune diseases are women, two-thirds of Alzheimer's disease cases are women, and women are 50 percent more likely to die within the year after a heart attack than men. According to the Office of Inspector General report, eight out of the 10 drugs that were recalled from the market were because of side effects in women that were worse than in men. Those side effects weren't seen in the trials because there wasn't enough female representation. There's a tremendous amount to be gained quite quickly when we use AI to start focusing on sex-based differences.” — Jessica Federer, MPH, Board Member, Angelini Ventures, a fund investing in health technology companies
Medical writers won’t be replaced — AI will allow them to do more higher-order thinking.
“With AI there’s that sensitivity of, ‘Are the robots going to replace us?’ but with PeerAI, we've created a place where medical writers can more easily take advantage of the way the artificial intelligence can support what they do. Because what they do is difficult, and they end up having to focus on a lot of tasks that would be better for a computer to take care of. What we’re doing is all about freeing up these knowledge workers to be more creative and do the higher order tasks that really need their thinking, in terms of the strategy, in how research is being described. Peer AI has attended conferences and published white papers through the American Medical Writing Association (AMWA), we’ve gotten a lot of meaningful engagement that’s driven our product design.” — Christopher Ceppi, Co-Founder, President and COO, Peer AI, a GenAI tool that transforms regulatory medical writing
Good old-fashioned human “grit” will be a deciding factor in which AI applications go to market.
“When investors are considering a technology, they look at the team behind it. The reason you invest in a company starts with the talent, the relentless belief system, and the sheer grit. If you're dealing in multi-stage investments, how has the grit effectively translated into better use of capital, throughout the different discovery stages, and is that moving the milestone in an accelerated path? Don't just say you're doing an AI company. Come in and talk about your models, about how you're trained, about what's meaningful that puts you in a completely differentiated category than anybody else.” — Milind Kamkolkar, MS, Venture Partner, RA Capital, a life sciences and healthcare investment fund
For AI technologies to flourish, experts will need to learn to speak each other’s “languages.”
“These are technologies that are going to serve patients and extend lifespans. Currently, there are a lot of technologists who understand the technology well but know nothing about life sciences and the biopharma industry. And then there are biology and life sciences experts who know nothing about the AI side. The critical building block in these teams will be the ability to have that bilingual fluidity to build the right culture and translate each other's language, to build at that intersection, and that's hard to find. When you find teams that have all those ingredients, that's when we get really excited.” — Sooah Cho, MBA, MPP, Partner, SignalFire, an AI native venture capital fund
AI will be democratized — sooner than we think.
“This is very nascent, but what we're seeing is a recognition that [AI] tools are going to be important for the future, and there’s a willingness in making investments towards that. And this is really important because today, these tools are only accessible to specialists who have deep domain knowledge, both on the biology side and on the machine learning side. This skill set is not very widespread in this industry. So the next stage of adoption has to come from building the right interfaces around these tools so that someone who doesn't have that special expertise can use it. Imagine combining agents and systems that can reason in natural language, can interact with human beings, and can also natively reason in the language of biology. That's probably coming a lot sooner than one would think and that step will really unlock a lot.” — Alex Rives, PhD, Chief Scientist, EvolutionaryScale