Insilico Medicine Secures $255M Series C Funding for AI Drug Discovery

Insilico Medicine Secures $255 Million in Series C Funding

Insilico Medicine, a pioneering AI-driven platform dedicated to drug development and discovery, revealed on Tuesday the completion of a $255 million Series C financing round. This substantial investment reflects a recent, significant achievement for the company: demonstrating its AI platform’s capability to identify a novel therapeutic target, engineer a specific molecule to address it, and initiate the clinical trial process.

AI and Drug Discovery Attract Investment

This funding event further underscores the growing investor interest in the intersection of artificial intelligence and drug discovery. The field is increasingly recognized for its potential to revolutionize pharmaceutical research.

Company Overview: Insilico Medicine

Founded in 2014 and based in Hong Kong, Insilico Medicine operates on the core principle that AI-assisted systems can pinpoint new drug targets for previously untreatable diseases. The company aims to facilitate the creation of innovative treatments and accurately forecast their performance in clinical trials. Prior to this round, Insilico Medicine had already secured $51.3 million in funding, as reported by Crunchbase.

A Novel Approach to Drug Development

While utilizing AI to accelerate drug development isn't a new concept, Insilico Medicine presents evidence suggesting it can successfully navigate the entire process, from initial discovery to trial prediction. In 2020, the company identified a previously unknown drug target for idiopathic pulmonary fibrosis, a condition characterized by scarring of the lung’s air sacs, leading to breathing difficulties.

Two AI platforms were instrumental in this process. They initially evaluated 20 potential targets, ultimately focusing on one, and subsequently designed a small molecule treatment that exhibited promising results in animal studies. The company is currently preparing an investigational new drug application for submission to the FDA and anticipates initiating human trials later this year or early next year.

Focus on Process Innovation

The primary significance of this achievement lies not solely in the drug itself, but in the streamlined process. This project compressed the typically multi-year, multi-million dollar preclinical drug development phase into just 18 months, at a total cost of approximately $2.6 million. Founder Alex Zhavoronkov believes Insilico Medicine’s greatest strength lies in minimizing the inherent uncertainty in drug discovery.

“We currently have 16 therapeutic assets, not just IPF,” Zhavoronkov states. “This has certainly garnered attention.”

He further explains, “It’s about improving the probability of success. The likelihood of successfully linking the correct target to the appropriate disease with an effective molecule is inherently low. Our success with IPF and other undisclosed diseases reinforces confidence in the potential of AI.”

Investor Confidence and Future Growth

The proof-of-concept demonstrated by the IPF project, coupled with the broader enthusiasm surrounding AI-driven drug development, attracted a diverse group of investors to this latest funding round.

Warburg Pincus led the round, with participation from Qiming Venture Partners, Pavilion Capital, Eight Roads Ventures, Lilly Asia Ventures, Sinovation Ventures, BOLD Capital Partners, Formic Ventures, Baidu Ventures, and several new investors including CPE, OrbiMed, Mirae Asset Capital, B Capital Group, Deerfield Management, Maison Capital, Lake Bleu Capital, President International Development Corporation, Sequoia Capital China, and Sage Partners.

Zhavoronkov reports that the round was oversubscribed by a factor of four.

The Cost of Drug Development

A 2018 study analyzing 63 drugs approved by the FDA between 2009 and 2018 revealed a median capitalized research and development investment of $985 million was required to bring a drug to market, encompassing the costs of failed clinical trials.

These substantial costs and the low probability of drug approval have historically hindered the pace of drug development. According to a 2021 Deloitte report, R&D returns for biopharmaceuticals reached a low of 1.6% in 2019, recovering to a modest 2.5% in 2020.

Insilico’s AI Platforms

Zhavoronkov envisions an AI platform, trained on comprehensive data, that can significantly reduce the number of failed clinical trials. This vision is supported by two key platforms: PandaOmics, an AI system for identifying potential drug targets, and Chemistry 42, a platform designed to synthesize molecules that interact with those targets.

“We have a tool that integrates over 60 different approaches to target discovery,” he explains.

“You are investing in something innovative, but you also have supporting evidence that strengthens your hypothesis. This is where our AI excels.”

Validation Through Research

While the IPF project’s full details haven’t yet been published in a peer-reviewed journal, a related project has been. A paper published in Nature Biotechnology demonstrated that Insilico’s deep learning model could identify potential compounds within just 21 days.

The IPF project represents an expansion of this concept. Zhavoronkov aims not only to identify molecules for known targets but also to discover entirely new targets and guide them through the entire clinical trial process, while simultaneously collecting data to refine future drug discovery efforts.

“So far, no one has challenged us to solve a disease in collaboration,” he says. “If that opportunity arises, I would be very pleased.”

Strategic Partnerships

Insilico Medicine’s approach to novel target discovery has already been implemented in collaborative projects. The company has partnered with Pfizer on identifying new targets, with Johnson & Johnson on small molecule design, and with Taisho Pharmaceuticals on both. Today, a new partnership with Teva Branded Pharmaceutical Products R&D, Inc. was also announced, with Teva intending to utilize PandaOmics for identifying new drug targets.

The Broader Trend in AI-Driven Drug Discovery

Insilico Medicine isn’t alone in attracting investment and forging partnerships. The entire field of AI-based target discovery is experiencing considerable attention.

In 2019, Nature reported at least 20 partnerships between major pharmaceutical companies and AI drug discovery technology firms. Investment in AI companies focused on drug development surged to $13.9 billion in 2020, a four-fold increase from 2019, according to Stanford University’s Artificial Intelligence Index annual report.

Drug discovery projects received the largest share of private AI investment in 2020, a trend partly driven by the urgent need for rapid drug development during the pandemic. However, the underlying momentum predates COVID-19.

Navigating the Hype

Zhavorokov acknowledges the current hype surrounding AI-based drug development. “Companies lacking substantial evidence to support their AI-powered drug discovery claims are still able to raise capital quickly,” he observes.

He believes Insilico Medicine differentiates itself through the caliber of its investors. “Our investors don’t speculate,” he asserts.

Ultimately, the success of these AI-based drug discovery platforms will depend on their ability to navigate the challenges of clinical trials. Only time will tell if they can deliver on their promise.