Employ Artificial Intelligence to Revolutionize Drug Discovery
Deriving a data-driven principle that has the power of explaining physical and chemical nature of biological systems, which we harness to accelerate drug discoveries.
What is our philosophy
To derive a data-driven principle that has the power of explaining physical and chemical nature of biological systems, which we harness to accelerate drug discoveries.
What have we done
A data-driven atom-based scoring function is learned from 100,000 protein crystal structures containing information of >100 million amino acid side chains.
A dynamic deep neural network specifically designed for chemical informatics.
Why is our work impactful
Beating current gold standard in computation-aided drug discovery:
Drug pocket side chain conformation prediction and drug docking with significantly increased accuracy compared to standard method.
Prediction of chemical compound characteristics (solubility, binding affinity, etc) significantly better than current standard.

Recent News

Accutar Tops ongoing Kinase-drug binding affinity prediction Dream Challenge
Accutar to present at Amgen AI conference, Boston
Accutar presented at World Artificial Intelligence Conference 2018, Shanghai
Ligand docking and virtual screen for drug discovery
Dr. Fan was trained at UC, Berkeley in Biostatistics and obtained his Doctor degree from Cornell/Sloan-kettering in structural biology/Immunology. He was further trained by Dr. Gunter Blobel at Rockefeller University. With a dream of using a hybrid approach (by combining computation design and experimental validation) to accelerate drug discovery, and to reform current “hit-2-lead” drug discovery scheme, Dr. Fan founded Accutar biotech with the support of Dr. Gunter Blobel. Dr. Fan also hold a joint appointment at SUNY, Downstate medical school as a research assistant professor.
Wei He, Ph.D., brings to Accutar Biotechnology 11 years of oncology drug discovery experience in both small molecule and biologics. Most recently, he was Associate Director of Preclinical Pharmacology at Incyte Corporation. In this role, he oversaw cancer biology groups leading efforts of project initiation and progression to IND. Prior to joining Incyte, Wei served as scientific project leader at Abbvie Oncology and Roche Oncology, where he led cross-functional project teams working on immuno oncology, targeted therapy, antibody drug conjugate and therapeutic RNAi programs.
Wei obtained his B.S. and M.S. in chemistry from Peking University in China and his Ph.D. in biochemistry and molecular biology from Baylor College of Medicine. He completed his HHMI postdoctoral training at the Memorial Sloan-Kettering Cancer Center.
Yimin Qian, Ph.D., brings to Accutar Biotechnology over 20 years of drug discovery experiences in both Pharma and Biotech. Yimin held multiple leadership positions previously. Most recently, he was Senior Director at Arvinas (2014-2018), Director & Asian lead at Merck (2013-2014) and Research Leader at Roche (1997-2013). Yimin has published over 50 peer reviewed papers with over 3000 scientific citations. Yimin is an inventor of 29 issued U.S. patents and additional 26 pending patent applications. At Accutar, Yimin will lead efforts to train AI drug discovery platform using expert human knowledge and to further improve Accutar-Degrader (Accurate-target degrader) technology platform. Yimin obtained Ph.D. degree in organic chemistry from University of Pittsburgh. He received post-doc training from Yale University.
At Accutar, Xiangyan Sun leads a globally based team and oversees internal machine learning framework development with a focus on making significant progress in the application of artificial intelligence to drug discovery. Xiangyan won the championship of 2014 Beauty of Programming Challenge, a programming competition for college students in Asia and sponsored by Microsoft in collaboration with the Institute of Electrical and Electronics Engineers (IEEE). Xiangyan holds a B.S. and M.S. in Computer Science from Fudan University.