Unlocking New Drugs for Neurodegenerative Diseases with Victor Hanson-Smith from Verge Genomics

Today on the Impact AI podcast, I am excited to host Victor Hanson-Smith, Head of Computational Biology at Verge Genomics. He joins me today to talk about the unlocking of new drugs for neurodegenerative diseases and their mission at Verge to make drug discovery cheaper and faster.

In our discussion, Victor tells about current Verge ventures and the important part they have in developing new drugs, the role machine learning plays, and the type of data sets they work with.  We also hear about the complexity behind “omics” data and how Verge is validating machine learning models. Victor talks passionately about the importance of team building, leadership, and company culture, and the vital role they have in establishing effective machine learning models. To hear his advice to other leaders of AI-powered startups, including the three races underway, tune into today’s episode. 

Key Points:

• How Victor ended up at Verge Genomics as Head of Computational Biology.
• How his experience with his father’s disease ignited a curiosity in him.
• Verge Genomics’ ventures and why it is important in developing new drugs.
• The role machine learning plays in their technology and approach. 
• Victor elaborates on the types of data they work with in the different models.
• More about the Human Data Atlas and how it works.
• He talks about the Verge Genomics model setup and functionality.
• Different challenges they’ve encountered with human omics data and machine learning.
• How they ensure building the most effective models using complex “omics” data.
• Verge’s validation process for machine learning models. 
• How generative AI has influenced (or not influenced) advancements at Verge.
• Advice from Victor to other leaders of AI-powered startups.
• Where Victor sees the impact of Verge Genomics in three to five years.

Quotes:

“We like to say that Verge Genomics is a full-stack drug discovery and development company.” — Victor Hanson-Smith

“This revolution in systems biology has the potential for new treatments for countless human diseases and has the potential to make drug discovery cheaper and faster. Long-term, it might even transform our fundamental relationship with the concept of disease.” — Victor Hanson-Smith

“One of the key differentiators for Verge is that we base our discoveries in human data.” — Victor Hanson-Smith

“At Verge, we often say, to succeed in humans, we start in humans, and so we go direct to the source.” — Victor Hanson-Smith

“We believe that no single data set or a single piece of data is sufficient for the sorts of rigorous drug discovery we’re interested in. Rather, our platform combines lots of different data types and layers and we’re looking for signals that are consistent across those layers.” — Victor Hanson-Smith

“This problem of finding the right targets, I think, is existential and one of the most upstream problems for the drug discovery industry and that’s a problem right now I don’t think is crackable by generative AI but Verge is on the frontlines of getting us closer there.” — Victor Hanson-Smith

Links:

Victor Hanson-Smith on LinkedIn

Victor Hanson-Smith on Twitter

Verges Genomics

Converge Platform

Resources for Computer Vision Teams:

LinkedIn – Connect with Heather.

Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.

Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.

Computer Vision Advisory Services – Monthly advisory services to help you strategically plan your CV/ML capabilities, reduce the trial-and-error of model development, and get to market faster.