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Clinical trials are better, faster, cheaper with big data

MIT Technology Review

"One of the most difficult parts of my job is enrolling patients into studies," says Nicholas Borys, chief medical officer for Lawrenceville, N.J., biotechnology company Celsion, which develops next-generation chemotherapy and immunotherapy agents for liver and ovarian cancers and certain types of brain tumors. Borys estimates that fewer than 10% of cancer patients are enrolled in clinical trials. "If we could get that up to 20% or 30%, we probably could have had several cancers conquered by now." Clinical trials test new drugs, devices, and procedures to determine whether they're safe and effective before they're approved for general use. But the path from study design to approval is long, winding, and expensive.


Medidata launches AI company to help answer pharma's big questions

#artificialintelligence

Acorn AI is built on the Medidata platform, and as a Medidata company, will draw on the company's business development, sales and marketing resources, among others, said the company's newly-minted president, Sastry Chilukuri, who first joined Medidata in January of this year as executive vice president of digital and artificial intelligence (AI) solutions. Chilukuri told us Acorn AI is addressing two big trends: "The first is we're increasingly getting into a world of precision medicine, with CAR-T therapy, tissue engineering, gene and cell therapy, etcetera." The other is the advancement of the advancement of AI and new sources of data. Now, increasingly, Chilukuri said researchers have a 360-degree view of the patient, including clinical, genomic, molecular, as well as socioeconomic, behavioral, and environmental data, which is creating "an enormous opportunity around personalization," he explained. In order to fully capture this opportunity, Chilukuri said life science companies need to make data "liquid" to answer a few important questions.