Head of Insilico Medicine’s Hong Kong R&D Center to Give Keynote on AI Drug Discovery at HKUST Big Data Institute

Hong Kong, May 04, 2023 (GLOBE NEWSWIRE) -- Frank Pun, PhD, Head of the Hong Kong R&D Center of Insilico Medicine (“Insilico”), a generative artificial intelligence (AI)-driven drug discovery company, will give a keynote presentation titled “How AI is Transforming Drug Discoveries” at the Hong Kong University of Science and Technology Big Data Institute Workshop on Big Data and Biomedical & Chemistry Science on May 8, 10am, HKT.

Insilico is a leading innovator in advancing new therapeutics using generative AI and reinforcement learning, with early patents in the space, and uses an end-to-end Pharma.AI platform for identifying novel targets (PandaOmics), designing new drugs (Chemistry42), and predicting the outcomes of clinical trials (InClinico). The Company’s software is trained on aging and focused on diseases with high unmet need, and two of its AI-designed drugs have reached clinical trials. Insilico’s lead drug for the devastating chronic lung disease idiopathic pulmonary fibrosis (IPF) will soon be entering Phase 2 trials with patients and its drug for COVID-19 and related variants has been approved for clinical trials and has a number of design advantages over existing COVID-19 drugs. In all, there are 31 drugs in Insilico’s internal pipeline available for partnering and licensing for indications including cancer, fibrosis, and immunology and the Company has partnered with top pharma companies like Fosun and Sanofi to advance their programs. 

Insilico first proved the concept of an AI drug discovery engine in 2016 – screening 72 million compounds and identifying candidate molecules with anti-cancer properties in a paper published in Oncotarget. Its Pharma.AI platform has grown increasingly more sophisticated since, with a major relaunch in November 2022, and the addition of an AI-powered robotics lab capable of performing validating experiments as well as chat functionality. 

Dr. Pun leads a team of application scientists in Hong Kong who are further developing PandaOmics, the AI-enabled biological target discovery engine of Insilico’s end-to-end platform and has published widely in top peer-reviewed journals related to his research in AI drug discovery. Recent publications include the use of PandaOmics to discover dual-purpose therapeutic targets implicated in aging and glioblastoma multiforme, published in the journal Aging; applying AlphaFold to Insilico’s generative AI platform to develop a potent hit molecule for hepatocellular carcinoma in under 30 days along with researchers at the University of Toronto’s Acceleration Consortium, published in the journal Chemical Science; using PandaOmics to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets, published in the Nature journal Cell Death & Disease; applying PandaOmics to analyze the expression profiles from Answer ALS to identify new targets for potential therapeutic interventions for Amyotrophic Lateral Sclerosis, published in the journal Frontiers in Aging Neuroscience; and using PandaOmics to find high confidence and novel targets associated with hallmarks of aging across multiple disease areas, published in the journal Aging

About Insilico Medicine

Insilico Medicine, a clinical stage end-to-end generative artificial intelligence (AI)-driven drug discovery company, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties. Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases.

Learn more at www.insilico.com.  


Frank Pun, PhD, Presents Keynote at HKUST Big Data Institute Workshop