One of China’s premier government-backed, elite academic research institutions, Institute of Materia Medica, Chinese Academy of Medical Sciences, entered into a strategic research collaboration with a small Canadian-based biotech upstart called Cyclica to discovery and develop antiviral drug candidates for COVID-19 while also exploring opportunities to develop multi-targeted antiviral compounds. This partnership seeks to leverage artificial intelligence (AI) to rapidly identify drug repurposing targets—there isn’t enough time to follow the traditional drug development pathway.
Why did one of China’s premier research centers pick Cyclica?
As it turns out the underlying premise driving the memorialization of this partnership is the need for speed to find therapies for COVID-19. Traditional approaches will not suffice. Hence, the Chinese government-backed institution was interested in the Toronto-based upstart, founded in 2013 that uses its proprietary deep learning engine, MatchMaker TM, to screen a collection of more than 6,700 FDA-approved drugs and drug candidates with at least Phase I clinical data against the structurally-characterized human proteome.
How did the two come together?
The two organizations found each other thanks to historical relationship that stemmed from the China-Canada Angel Alliance (CCAA), an angel investment group registered in Ontario, Canada.
Use of MatchMaker & PolypharmDB to Identify potential COVID-19 targets
The company uses its Matchmaker as “a leap forward in proteome screening beyond molecular docking.” The product is trained on millions of known human drug-target interactions (DTI) in addition to structural data. This extensive amount of data and associated training results in a first-in-class database called PolypharmDB, a library of clinically assessed molecules and their polypharmacological profiles used to identify repurposing opportunities for drug candidates. By leveraging PolypharmDB and MatchMaker, it turns out Cyclica’s scientists have investigated both human targets as well as viral proteins with potential therapeutic relevance for COVID-19. According to a technical briefing, the deep learning (DL)-based product combines molecular biophysics and AI to predict binding of new drug molecules to all proteins seep, accuracy and generalizability and hence allowing discovery organizations to move beyond the reliance of molecular docking.
MatchMaker & PolypharmDB results in actionable list of targets
To date, Cyclica has produced a set of molecules with a higher probability of ability to interact with the putative therapeutic targets for COVID-19. As it turns out the process of modeling viral proteins pushed MatchMaker beyond established benchmarks but by leveraging PolypharmDB in combination they have produced a prioritized set of molecules representing an actionable collection of molecules primed for testing.
In this collaboration, Institute of Materia Medica will conduct in vitro and in vivo antiviral assessment for molecules generated by the Cyclica work (discussed above). Moreover, the two organizations will collaborate on long-term projects focusing on the design of multi-target antiviral compounds with the goal of reducing drug resistance.
Founded in 2013, this Toronto, Canada-based Cyclica has raised approximately $7 million in venture capital funds and employs about 40 employees. They leverage AI and computational biophysics to reshape the drug discovery process. Led by CEO Naheed Kurji the venture was founded by Jason Mitakidis. the company uses its technologies contribute to the movement of decentralizing the discovery of new medicines with its integrated structure-based and AI-augmented drug discovery platform, Ligand Design and Ligand Express.
Taken together, Ligand Design and Ligand Express design advanced lead-like molecules that minimize unwanted off-target effects, while providing a holistic understanding of a molecule’s activity through integrated systems biology and structural pharmacogenomics. Cyclica’s differentiated platform opens new opportunities for drug discovery, including multi-targeted and multi-objective drug design, lead optimization, ADMET-property prediction, target deconvolution, and drug repurposing for a wide range of indications. With a world-class team with deep roots in industry and a first-in-class integrated drug discovery platform, Cyclica will spark a surge of innovation through a combination of venture creation and partnerships with early-stage and emerging biotech companies. By doing more with AI, Cyclica will revolutionize a system troubled with attrition and costly failures, accelerate the drug discovery process, and develop medicines with greater precision.
China-Canada Angel Alliance
China-Canada Angel Alliance (CCAA) is an angel investment agency registered in Ontario, Canada, established in 2014 by a group of angel investors from Zhongguancun River Capital and the Zhongguancun Angel 100. CCAA is committed to building a cross-border ecosystem between China and Canada, and promoting international exchanges and collaboration between Chinese and Canadian entrepreneurs through joint investment, entrepreneurial mentorship, and connecting cross-border resources.
China’s Material Medica
The Institute of Materia Medica (IMM) was founded in 1958. Its scientists use the latest biomedical theories, cutting-edge technologies, and state-of-the-art laboratory equipment to develop drugs from botanical compounds, synthetic chemicals, and bioproducts. Since the institute’s establishment, its scientists have discovered or developed hundreds of new drugs and acquired 130 new drug certificates from the China Food and Drug Administration, IMM’s contributors have won 230 awards from the government and professional societies for drug research and development.
Call to Action: Interested in learning more about decentralizing drug discovery? Contact Cyclica’s global head of partnerships, Vern de Biasi.