Pfizer, AstraZeneca, Merck KGaA-backed Israeli AI incubator launches first biopharma startup

After Pfizer, AstraZeneca, Teva and Merck KGaA backed an Israeli startup incubator looking to wield artificial intelligence in the discovery and development of new drugs, they’re now celebrating the launch of their first company.

AION Labs—described as an alliance of global pharmas, tech leaders and investors that launched late last year—is raising the curtain on OMEC.AI, a venture tasked with employing machine learning to help predict which drug candidates will be most likely to succeed in human clinical trials and which will not.

The Israel Innovation Authority approved and financially boosted OMEC.AI's formation, the companies said in a release. Besides its pharma backers, AION is also backed by the Israel Biotech Fund Amazon Web Services and Germany’s BioMed X Institute.

OMEC.AI's goal is to identify potentially hidden safety liabilities, or even a drug’s lack of efficacy, by parsing preclinical data. AION and its pharma partners will support those efforts with supplies of multi-omics and pharmaceutical data for training its computer models, in addition to funding and mentorship. 

“There is currently no automated solution that employs all preclinical data in a way that allows a reliable assessment of the clinical trial readiness of a drug candidate. We are aiming to fill this gap,” OMEC.AI co-founder and CEO Ori Shachar said. 

AION’s startup construction model begins with crowdsourcing calls for computational biologists, AI researchers and biomedical scientists to propose their ideas for tackling specific R&D challenges.

After making the shortlist, candidates are invited to an innovation boot camp at AION’s labs in Rehovot, outside Tel Aviv. The winning team of selected scientists are trained through a fully funded incubation period of up to four years before becoming an independent startup, the company said.

In addition to AI programs for predicting clinical trial readiness, AION has also put out calls for applications in antibody design, targeted therapies and the prediction of clinical trial outcomes among patients with cancer.