Genesis Therapeutics has a new simulation approach and cross-disciplinary team that has clearly made an impression: the company just raised a $52 million A round.
Founder Evan Feinberg got into the field when an illness he inherited made traditional lab work, as an intern at a big pharma company, difficult for him. The computational side of the field, however, was more accessible and ended up absorbing him entirely.
He had dabbled in the area before and arrived at what he feels is a breakthrough in how molecules are represented digitally. Machine learning has, of course, accelerated work in many fields, biochemistry among them, but he felt that the potential of the technology had not been tapped.
“I think initially the attempts were to kind of cut and paste deep learning techniques, and represent molecules a lot like images, and classify them — like you’d say, this is a cat picture or this is not a cat picture,” he explained in an interview. “We represent the molecules more naturally: as graphs. A set of nodes or vertices, those are atoms, and things that connect them, those are bonds. But we’re representing them not just as bond or no bond, but with multiple contact types between atoms, spatial distances, more complex features.