Maryland Startup Developing AI-Enabled Drug Discovery Technology, Insilico Medicine, Just Raised $37M in Funding from Leading Chinese VC Firm
September 10, 2019
In the world of drug discovery and development, there is increasing pressure to get novel products to market faster, cheaper and ahead of the competition. This is exactly what Insilico Medicine is helping leading pharmaceutical companies to achieve through their artificial intelligence technology for drug discovery.
Insilico Medicine is an artificial intelligence company headquartered in Hong Kong, with R&D and management resources in six countries, including the BioHealth Capital Region. The company is led by CEO, Alex Zhavoronkov, PhD out of Hong Kong, and COO, Qingsong Zhu who is based in Maryland. Since 2014 they have advanced their technology and partnered with the most innovative biopharmaceutical companies to validate its AI solutions and rapidly deliver novel drug discovery targets.
Lead by Qiming Venture Partners, the $37 million Series B funding round was also joined by Eight Roads, F-Prime Capital, Lilly Asia Ventures, Sinovation Ventures, Baidu Ventures, Pavilion Capital, BOLD Capital Partners, among other investors that participated in the Series A round.
The Series B funding will be used to commercialize the validated generative chemistry and target identification technology. The company will also build up a senior management team with the experience in the pharmaceutical industry, further develop its pipeline in cancer, fibrosis, NASH, immunology and CNS for the purposes of partnering with the pharmaceutical companies on specific therapeutic programs.
“We are excited to lead the current round of financing in Insilico Medicine,” says Nisa Leung, Managing Partner of Qiming Venture Partners. “The company is an industry leader in the AI-powered drug discovery vertical. We look forward to seeing it shortening the time for drug discovery and creating synergies with our portfolio companies.”
Insilico Medicine and its scientists around the world are transforming the pharmaceutical industry by developing and applying the next-generation deep learning approaches to every step of the drug discovery and drug development process. The company is also using its technology to build its own pipeline of AI identify targets and novel molecules which it is now validating for several disease areas.
Zhavoronkov sees the future growth of Insilico Medicine not just in the AI-enabled drug discover services field, but fueld by the development of its own pipeline of novel molecules.
According to Zhavoronkov in a recent ContractPharma.com article, “Its now clear that the best way to keep a sustainable business as an AI company is to develop assets that biotech and pharma companies can acquire. We are building such a pipeline.”
Insilico Medicine has developed and validated a comprehensive drug discovery pipeline which includes a state-of-the-art molecular generator utilizing multiple proprietary generative and reinforcement learning technologies. The company identified promising targets in a variety of therapeutic modalities including cancer, fibrosis, NASH, immunology and CNS.
Insilico Medicine is not only a pioneer in next-generation artificial intelligence technology for drug discovery but also in their approach to building a premier global business through innovative hiring and partnerships strategies.
There are relatively few experts in the world that understand the convergent, next-generation fields of AI and drug discovery. Insilico tackled this talent obstacle by sourcing and hiring mainly through hackathons, such as their own molhack online hackathon. This has helped them to attract the best talent and expand around the world into six countries.
Insilico Medicine also recognized that partnerships between AI companies and biotechs were often hampered by contractual issues. To overcome this, the company invested in developing a universal partnership agreement that was flexible fully describes the multiple partnering options, and provides the ability to structure the contract through a semiautomatic process.
See the full press release in Yahoo Finance.