Insilico Medicine and Other AI Drug Discovery Companies Leading the Race

A Hong Kong-based artificial intelligence (AI)-driven drug discovery company Insilico Medicine has just announced the appointment of Dr. Michelle Chen as a Chief Business Officer (CBO) to oversee the company’s corporate strategies and business development activities. Dr. Chen is a lofty hire, having more than 20 years of experience in biopharma and such brands as WuXi Biologics, Roche, Merck, and BioMarin on her resume’s executive track record. 

The news comes as a continuation of Insilico Medicine's hiring spree, including recent C-suite appointments of Nirav Jhaveri as Chief Financial Officer (CFO) and Dr. Robert Spiegel, the former Chief Medical Officer (CMO) of Schering Plough, as CMO to oversee the advancement of Insilico’s therapeutic pipeline. It also follows the company’s impressive growth trajectory, including a streak of collaboration milestone achievements, AI-software deployments, and a recent $255 million Series C financing led by Warburg Pincus in June. The financing was also participated by a group of prominent investors with expertise in biotechnology and artificial intelligence.

Insilico Medicine’s external partnerships have been piling up, including the company’s recent target discovery collaboration with Teva, a partnership with protein degradation pioneers Arvinas, and PAQ Therapeutics. Insilico’s growth in China is exceeding ambitious expectations with a substantial partnership struck at a rate of almost one every two weeks, according to the companies press release. 

The prominent growth dynamic is enabled by Insilico’s ability to deliver successful drug candidates out of its AI-driven system Pharma.AI in a remarkably “conveyor” fashion -- both for the internal pipeline and for the external partnerships. Pharma.AI includes three essential components: PandaOmics -- for multi-omics target discovery and deep biology analysis; Chemistry42 -- for machine learning de-novo design of novel drug-like molecules, and InClinico -- for predicting clinical trials success rates, and optimizing trial experiment design.

In 2019, Insilico’s deep learning software had a major proof of concept run where it managed to “imagine” novel molecules -- potent inhibitors for DDR1 kinase -- within just days. Much as it was impressive, DDR1 was a well-known target. A much more challenging milestone was achieved in February 2021 when the company successfully validated a novel preclinical candidate with nanomolar potency against a completely novel target addressing idiopathic pulmonary fibrosis ("IPF") -- all the processes have taken the company just under 18 months and a fraction of cost for the traditional drug discovery. Just half a year later, Insilico nominated the second preclinical candidate with a novel target -- this time for kidney fibrosis, and again, in the record time and budget. 

A wave of AI-enabled milestones

One may recall several other recent announcements, where drug candidates were designed and validated rapidly using sophisticated AI platforms. 

For instance, UK-based AI-company BenevolentAI has just announced it identified a novel target for ulcerative colitis and advances a drug candidate to IND/CTA-enabling studies. The company managed to nominate preclinical candidate within just two years of novel target validation. Last year, BenevolentAI also applied AI to quickly identify potential COVID-19 treatment baricitinib – a known rheumatology therapeutics via repurposing. Exscientia, another UK-based AI-drug design company, has several drug candidates entering clinical trials, including the first AI-designed molecule for immuno-oncology. The company secured more than $500 million in an upsized IPO this month. 

In 2019, Canadian-based Deep Genomics made headlines with discovering a novel target and a novel RNA therapeutics candidate for rare Wilson disease using their AI Workbench platform -- all within 18 months of initiating target discovery effort. 

Finally, a digital biology company Recursion Pharmaceuticals, founded in 2013, managed to rapidly build an impressive pipeline of preclinical and clinical drug candidates for various indications using their AI-enabled automation and cell image analysis platform. The company also had success stories with external partners, including Takeda. Recursion went public in April, banking more than $430 million.  

Topics: Biotech Companies