Pfizer teams up with Insilico to mine data for drug targets

Pfizer has entered into a research collaboration with Insilico Medicine. The partners will use Insilico’s technology to identify real-world evidence for drug targets in multiple therapeutic areas.

Led by Alex Zhavoronkov, Insilico has spent getting on six years working to apply machine learning techniques to R&D. Those efforts have given Insilico generative biology methods and synthetic data generation pipelines it thinks can support target identification. Insilico showcased its capabilities in a 2018 paper describing the identification of biomarkers of aging from gene expression profiles.

Pfizer has seen promise in Insilico’s techniques, leading it to enter into a collaboration based on its partner’s machine learning technology and platform for analyzing omics data.

“We look forward to working with Insilico as Pfizer continues to explore new technologies that may be able to help us identify targets and biomarkers that could assist in our discovery programs,” Morten Sogaard, vice president for target sciences at Pfizer, said in a statement.

The Pfizer deal continues a busy period for Insilico. Over the past two years, Insilico has entered into deals with companies including Elevian, TARA Biosystems and WuXi AppTec while setting up a subsidiary in Taiwan and raising a $37 million financing round. Further back, Insilico teamed up with GlaxoSmithKline to discover new targets and molecules.

Those activities are testament to Insilico’s prominent position in the application of machine learning to drug R&D. How valuable machine learning currently is to drug R&D remains a topic of debate, but Insilico has done more than most to try to validate the concept, including through the publication of details of its discovery of DDR1 kinase inhibitors in 21 days.