For experts on Boston Consulting Group’s generative AI panel, effectively using the technology in the biotech industry will be a collaborative process.
Pictured, from left: Ashkan Afkhami, managing director & partner, Boston Consulting Group; Parry Bhatia, chief AI officer, GE Healthcare; John Doyle, global chief technology officer for healthcare and life sciences, Microsoft
Generative AI may conjure images of art made through software applications such as Midjourney, but its applications could run deep in the biotech and healthcare industries, according to experts who participated in a Biotech Showcase panel discussion Wednesday.
Conversations around AI have been plentiful at the 42nd J.P. Morgan Healthcare Conference this week. During a panel hosted by Boston Consulting Group (BCG), experts discussed the practical applications of generative AI and its potential uses in the biotech setting.
Parry Bhatia, chief AI officer at GE Healthcare, told the crowd that over the past 18 months, large language models have been put to use by the industry and further integrated into science and technology. It will become even further incorporated into the vast healthcare ecosystem, he said.
John Doyle, global chief technology officer for healthcare and life sciences at Microsoft, noted that while he is optimistic about more generative AI developments in 2024, a framework must be “developed collectively” as the space is not heavily regulated.
But it’s not just theory anymore, as generative AI is already used in biotech companies. Jean-Philippe Vert, chief research and development officer at AI biotech Owkin, said his company is in the “business of a quite complex biology” and that using generative AI can help the company see all of the data and then train models to capture information in its search for treatments.
For broader use cases, Doyle said generative AI is also being applied to software development and the automation of processes.
In the physical healthcare space, Bhatia said he sees generative AI assisting with workstations and MRI machines but noted that there are more applications here as well.
“Many models that are being built right now across the healthcare system are unicorns solving a particular problem [in a] particular space,” he said. “Healthcare is multimodal, and even before we apply AI and machine learning to the diagnosis, [generative] AI foundation models can synthesize the data.” Bhatia asked how EMR data could be combined with medical imaging data for meaningful monitoring. “I think that’s where [generative AI] can help streamline the data,” he said.
As for the future, Doyle said it is crucial for biotech companies to have “domain-specific knowledge and expertise.” The generative AI field is complex, he said, and there will not be a single approach to building connections or a model. Therefore, as the industry moves forward, it is vital to figure out how to apply this technology “in a way that is appropriate.”
Doyle said the number one thing to consider is that “It’s not actually about the technology. It’s about us all collectively working together to solve the same problem.” No one organization will be the expert, he said, adding that across its partner community and customer community, Microsoft has seen partnerships becoming deeper and more strategic in nature and are typically outcome-driven.
Tyler Patchen is a staff writer at BioSpace. You can reach him at tyler.patchen@biospace.com. Follow him on LinkedIn.
