Wednesday, January 12, 2022
BigHat Biosciences, Inc., a biotechnology company with an artificial intelligence/machine learning-guided antibody discovery and development platform, today announced the successful completion of the first stage of a previously undisclosed research collaboration and licensing agreement with Amgen applying BigHat’s platform for multi-objective optimization of a next-generation antibody.
BigHat’s antibody design platform integrates a high-speed characterization with AI/ML technologies to engineer antibodies with more complex functions and better biophysical properties. This approach reduces the difficulty of designing antibodies and other therapeutic proteins to tackle conditions ranging from chronic illness to life-threatening disease. BigHat’s experimental platform massively speeds up candidate discovery and validation.
“This is an important milestone for BigHat, and the AI/ML biologics drug discovery field more broadly, as it demonstrates the ability of their platform to quickly and significantly optimize next-generation antibodies,” said Steve Doberstein, BigHat Independent Board Member and former Chief R&D Officer at Nektar Therapeutics, Inc.
Achievement of this first milestone shows that BigHat’s platform has the potential to design high-quality therapeutic antibodies effectively and efficiently. Its platform can synthesize, express, purify, and characterize antibodies in a fraction of the time compared to traditional labs to guide the search for better molecules.
“BigHat's platform for data-driven antibody design generated several antibodies significantly better than the starter molecules found using traditional technologies,” added Vineeta Agarwala, MD, PhD, General Partner at Andreessen Horowitz and BigHat Board Director. “Now that Amgen has validated the capabilities of BigHat's unique approach to antibody development, we're excited to continue working with them towards a lead antibody for their discovery research.”
This successful milestone triggers the initiation of work to create a lead panel of VHH antibodies for patients in need. “We are excited to show the power of our platform to rapidly improve biophysical characteristics and function by directing and learning from each cycle of our AI/ML-enabled experimental platform. We are looking forward to continuing our productive collaboration,” said Peyton Greenside, BigHat’s CSO and Co-Founder.
