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Cyclica Forms Multi-Year and Multi-Project Drug Discovery Partnership with the Genome Institute of Singapore

TORONTO & SINGAPORE--(BUSINESS WIRE)--#artificialintelligence--Cyclica announces a multi-year and multi-project collaboration with the Genome Institute of Singapore (GIS), a research institute under the Agency for Science, Technology and Research (A*STAR). Cyclica and GIS will carry out research efforts spanning from polypharmacology profiling to novel compound design for diverse drug discovery programs in oncology and related diseases. The collaboration will leverage GIS’ deep expertise in functional genomics, drug target discovery, and data analytics, and Cyclica’s AI-augmented and proprietary, Ligand Design and Ligand Express platform.

The world-class team of scientists at GIS will conduct new compound design and off-target profiling to discover hits and subsequently develop the lead compounds. GIS will perform functional analyses and testing of compounds derived from Cyclica’s drug discovery platform against gene targets of interest to GIS. This cross-border collaboration provides a unique opportunity to tailor drug identification and development efforts in a holistic way that will enable the advancement of precision medicine. By empowering researchers and healthcare institutes who are at the forefront of innovation, Cyclica and GIS will pave the way to decentralize the drug discovery process and develop the next generation of improved treatments for patients based on the individual’s disease features.

Dr. Tam Wai Leong, Group Leader of Precision Oncology at GIS, said, “Applying AI-augmented approaches towards drug design is innovative and forward-looking. It has the potential to rapidly grow the arsenal of new drugs in our fight against diseases like cancer, especially in an era of genomic medicine where physicians and scientists can better define the underlying genetic and molecular drivers of cancers.”

Professor Liu Jianjun, Deputy Executive Director at GIS, added, “Our ability to harness advanced genomic technologies has enhanced our discovery of genetic contributions to a spectrum of diseases, including cancer. Many of these important cancer drivers currently do not have drugs that target them. We believe that machine learning and deep learning models will shorten the time and cost for the development of new therapeutics, and are pleased to collaborate with Cyclica to further our efforts in developing therapeutics that can have a positive impact on patients.”

“The calibre of genomic research at GIS is world-class. We are thrilled to have the opportunity to work with many leading scientists at GIS to innovate novel therapeutics, based on genomic discoveries, for a wide range of diseases. This opportunity to make a meaningful contribution and impact to patients are common values we share with our partners at GIS,” said Dr. Verner De Biasi, VP, Global Head of Strategic Partnerships at Cyclica.

About Cyclica, Inc. (Cyclica)

Cyclica is a Toronto, Canada based biotechnology company that is 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.

Contacts

Davesh Chauhan

[email protected]

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