2022.06.16
Why I Left Big Pharma for AI:
Insilico Medicine's Co-CEO
Dr. Feng Ren
Insilico Medicine's Co-CEO
Dr. Feng Ren
In many respects, Dr. Feng Ren had risen to the top of the career ladder in drug discovery. After over 11 years in drug discovery and development at GSK he became Senior Vice President of Medicilion, a multibillion dollar contract research organization providing drug development services to pharma companies that he helped to take public.
But all that time spent bringing drugs to market through traditional channels also led to frustration with the persistent roadblocks: long timeline, high cost, and low success rate.
Dr. Ren had heard about the promise of artificial intelligence (AI) to accelerate the drug discovery process and around 2019, he began seriously analyzing the market. He saw that despite traditional pharma's reservations, the AI-driven drug discovery industry had matured, with tangible results and the ability to substantially accelerate and de-risk the process. He also found that while a number of companies claimed to be developing AI capabilities, only one had an end-to-end platform leading from novel target identification to small molecule design to clinical trial prediction – Insilico Medicine, founded by Alex Zhavoronkov, PhD, a pioneer in GANs and reinforcement learning for molecule design.
For six months, Dr. Ren served as an advisor to Insilico to better understand their process, during which time the company's AI-driven anti-fibrotic program progressed to a preclinical candidate (the novel small molecule has now advanced to phase 1 clinical trials). He decided it was time to make the leap.
But all that time spent bringing drugs to market through traditional channels also led to frustration with the persistent roadblocks: long timeline, high cost, and low success rate.
Dr. Ren had heard about the promise of artificial intelligence (AI) to accelerate the drug discovery process and around 2019, he began seriously analyzing the market. He saw that despite traditional pharma's reservations, the AI-driven drug discovery industry had matured, with tangible results and the ability to substantially accelerate and de-risk the process. He also found that while a number of companies claimed to be developing AI capabilities, only one had an end-to-end platform leading from novel target identification to small molecule design to clinical trial prediction – Insilico Medicine, founded by Alex Zhavoronkov, PhD, a pioneer in GANs and reinforcement learning for molecule design.
For six months, Dr. Ren served as an advisor to Insilico to better understand their process, during which time the company's AI-driven anti-fibrotic program progressed to a preclinical candidate (the novel small molecule has now advanced to phase 1 clinical trials). He decided it was time to make the leap.
"I talked to several companies, Insilico was the best one. Insilico has developed AI software including PandaOmics for target identification and Chemistry42 for compound generation in their end-to-end AI drug discovery platform [Pharma.AI]. This AI platform has been validated by internal programs and external collaborations. People can test it. This is really cool and unique."
Feng Ren
PhD, Co-CEO of Insilico Medicine.
Creating Seamless AI-Driven Drug Discovery
In Feb. 2021, Dr. Ren became Chief Scientific Officer and Head of Research and Development at Insilico and in June he became the company's co-CEO. He has since grown a team of 70 scientists in Shanghai across a range of specialties, including biology, bioinformatics, medicinal chemistry, computer aided design and drafting, preclinical, and clinical expertise. This team discovers novel targets using PandaOmics and designs novel molecules for those targets utilizing Insilico's Chemistry42 platform. The most promising molecules — based on successful scores across a series of measures — are then selected for synthesis and test through cells, tissues, and animals towards Investigational New Drug (IND) applications and then human studies. At the far end of Insilico's pipeline is InClinico — its AI platform for predicting the outcome of clinical trials which was launched during the recent BIO Convention in San Diego. And the company, which just raised $60m in a Series D funding round, bringing its funding total to $380m+ to date, revealed that it will launch a fully automated AI-run robotics lab later this year.
"Dr. Ren combines a very unique set of expertise working in academia, big pharma companies, and one of the largest CROs that services hundreds of clients on a very diverse set of programs. He knows what is possible in terms of the timelines for drug discovery. From the beginning, Dr. Ren put AI systems first. Every time we generate a result, and validate our own internal discovered therapeutic, the vast amount of data we generate goes back into training our AI systems. In brief, he managed to create a seamless end-to-end system and feedback loop that transformed us into a true AI-powered biotech company."
Alex Zhavoronkov
PhD, CEO of Insilico Medicine.
Winning the Race Against Big Pharma
With its end-to-end AI-driven drug discovery system, Dr. Ren says Insilico is capable of producing promising drug candidates at a pace that outstrips pharma's years-long timeline, at a fraction of the cost, and without sacrificing quality.
Since 2021, Insilico has delivered eight preclinical candidates designed using its AI platform targeting fibrosis, cancer, anemia, and inflammatory bowel disease. The team discovered and developed its lead drug for Idiopathic Pulmonary Fibrosis with a novel mechanism of action in just 18 months, bringing it to phase 1 clinical trial just a year later.
With other drug candidates well on their way, Dr. Ren will soon lead a team dedicated to clinical trials. "The speed is really fast," he says, "and I'm looking forward to how we can continue to apply the AI platform to make it even more efficient."
Since 2021, Insilico has delivered eight preclinical candidates designed using its AI platform targeting fibrosis, cancer, anemia, and inflammatory bowel disease. The team discovered and developed its lead drug for Idiopathic Pulmonary Fibrosis with a novel mechanism of action in just 18 months, bringing it to phase 1 clinical trial just a year later.
With other drug candidates well on their way, Dr. Ren will soon lead a team dedicated to clinical trials. "The speed is really fast," he says, "and I'm looking forward to how we can continue to apply the AI platform to make it even more efficient."
Pharma Turns to Insilico's AI Platform
Dr. Ren isn't the only pharma veteran taking an interest in AI. Since PandaOmics and Chemistry42 were commercialized during the second half of 2020, numerous pharma companies have licensed Insilico's technology or formed partnerships, including Fosun Pharmaceuticals, PAQ Therapeutics, Huadong Medicine, Arvinas, Westlake Pharma, and GenFleet Therapeutics.
"They saw our success in AI-powered drug discovery and want to utilize not only our AI tools but our very efficient drug discovery team," Dr. Ren says.
Sharing expertise is a testament to Dr. Ren's science-first approach, adds Dr. Zhavoronkov.
"Many companies in our field do not make their AI platforms available to others," says Dr. Zhavoronkov. "But those systems do not evolve and incorporate human intelligence from thousands of people. Dr Ren supported the idea of allocating substantial resources that other companies usually put into their internal drug discovery programs into building the AI platform and developing our own internal AI robotics capabilities."
"They saw our success in AI-powered drug discovery and want to utilize not only our AI tools but our very efficient drug discovery team," Dr. Ren says.
Sharing expertise is a testament to Dr. Ren's science-first approach, adds Dr. Zhavoronkov.
"Many companies in our field do not make their AI platforms available to others," says Dr. Zhavoronkov. "But those systems do not evolve and incorporate human intelligence from thousands of people. Dr Ren supported the idea of allocating substantial resources that other companies usually put into their internal drug discovery programs into building the AI platform and developing our own internal AI robotics capabilities."
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