From Schrodinger's Karen Akinsanya on NewYorkBIO's #VirtualBreakfast webinar series · · NewYorkBIO Video Channel
“The biggest difference with our physics-based methods compared to typical AI/ML approaches is the ability to get accurate simulations of compound interactions. We often start with incredibly potent molecules, which means we're two steps ahead in drug discovery, making the process both faster and better.”
On , Karen Akinsanya, President of Research & Development Therapeutics at SCHRODINGER INC, spoke about drug discovery during Schrodinger's Karen Akinsanya on NewYorkBIO's #VirtualBreakfast webinar series on NewYorkBIO Video Channel.
In a September 2020 appearance on NewYorkBIO's Virtual Breakfast series, Karen Akinsanya, then President of Research & Development Therapeutics at Schrodinger, discussed the company's dual identity as both a software and biotech firm. She described Schrodinger's physics-based software as enabling atomistic-level modeling of molecular interactions, allowing researchers to explore chemical space computationally rather than through iterative synthesis. Akinsanya noted that she joined Schrodinger after using its software at Merck, where she saw the potential to apply the tools more broadly across multiple drug targets. Akinsanya highlighted Schrodinger's collaborative structure, describing the company as "completely virtual" with a lab that "extends around the world." She mentioned partnerships with Google Cloud and pharmaceutical companies including Novartis, Gilead, and Takeda to identify antivirals for COVID-19. She contrasted Schrodinger's physics-based methods with typical AI/ML approaches, stating that physics-based simulations can provide accurate compound interactions even when training data is limited. Akinsanya also discussed her passion for science education, noting that she co-founded My Tech Learning to create a lab where children can explore experiments, and expressed a desire to see "science coaches" in every community working with children at the bench.