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When Using Artificial Intelligence In Pharma R&D, Start With Identifying Problem To Solve

 
• By Malcolm Spicer

VeriSIM uses generative AI for questions such as changing a drug molecule’s chemistry and machine learning to better predict potential biological implications. “When a child is learning a language, you're teaching a child starting from A-to-Z structures, and then suddenly they start speaking. Then they start learning different things, and then they get into problem solving. That's really what AI is getting really good at now,” says CEO Jo Varshney.

VeriSIM Life's BioSIM “virtual drug development engine” narrows the number of drug compounds that offer anticipated value for the treatment or cure of specific illness or disease. • Source: VeriSIM Life

Artificial intelligence can provide paths for pharmaceutical firms to cut costs and time for getting additional OTC as well as Rx drugs to market. Their first step, says the CEO of a pharmaceutical AI developer, is determining the questions they need to answer.

“I ask people, what is the problem that you want me to solve instead of what kind of AI do you want to use? It's a simple change in the question, but a huge, huge difference on what AI can do versus cannot do,” said Jo Varshney, CEO of VeriSIM Life Inc

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