Artificial intelligence (AI) has become an increasingly popular tool for drug companies discovering and designing new therapies. According to analysis by Deloitte, the AI market in drug discovery is expected to grow from $159.8m in 2018 to $2.9bn by 2025. Of the almost 180 start-ups involved in AI-assisted drug discovery in 2019, 40% were working on repurposing existing drugs or generating novel drug candidates using AI, machine learning, and automation. AI-enabled drug design company Valence Discovery, formerly InVivo AI, was founded in 2018. Since its rebrand last month, the company has announced a series of impressive drug discovery and design partnerships, with the aim of making advanced technology accessible to R&D organisations of all sizes.

It often takes years and hundreds of millions of dollars to discover a novel drug candidate. It requires the identification of promising molecules that can grab on to the right protein, synthesizing a compound, and then testing it. The process is so complicated that it has defied most computational methods to shorten it. But a paper published Monday in Nature Biotechnology describes a new method using artificial intelligence that, within 46 days, generated compounds capable of hitting a specific disease target. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free!

Insilico Medicine has achieved a world first by successfully designing, synthesizing, and validating a new drug from the ground up and taking just 46 days to do so. It achieved this impressive feat using AI. This is the first time that AI has been used to successfully create a new drug, and it took record time compared to traditional methods. The company used Generative Adversarial Networks (GANs) back in 2016 to design new kinds of molecules and have further developed the system, combining it with reinforcement learning (RL) in order to develop new drugs and biomarkers. The new drug works by blocking the activity of the DDR1 kinase, which is implicated in fibrosis.

This is Pharma's AlphaGo moment when the potential for AI to radically transform the normal operating procedures and business models of the entire industry becomes tangibly obvious to the public. In the case of the AI industry, this happened in 2015, when AI company DeepMind succeeded in developing the first AI capable of beating a human Go champion in Go. This study by Insilico Medicine may be an analogous game-changing moment for Pharma. While it typically takes 2-3 years to go from initial drug discovery to preclinical validation, Insilico Medicine has done this in less than 2 months end-to-end. This is 15 times faster than Pharma companies capable of conducting the most efficient R&D processes. In a landmark study published in Nature Biotechnology on September 2, 2019, Insilico Medicine showed that they generated and validated a novel small molecule in just 46 days, and designed the drug from scratch based on specified molecular properties in just 21 days.

Artificial intelligence (AI) is steadily reshaping healthcare from all sides, introducing technologies we wouldn't have thought possible five or 10 years ago. It's happening in the clinic (see HealthTap's Doctor A.I.), it's happening in diagnostics (see IBM Watson), and now it's moving into earlier-stage drug discovery with Palo Alto, California-based twoXAR. "In the couple years that we have been around, we've been told hundreds of times that computers cannot do this; that biology is too complex; that this will never work," said Andrew A. Radin, CEO of the AI-driven biopharmaceutical company. "Yet, in every single disease program where we have run proof-of-concept studies on our novel AI-identified candidates, we have generated efficacious results across standard end points." Using a custom-built computational platform, twoXAR works to identify what it calls "unanticipated associations between drug and disease."