Predicting Developability of High-Concentration Antibody Therapeutics for Subcutaneous Delivery
Speaker Details:
Pin-Kuang Lai
Assistant Professor
Stevens Institute of Technology
Predicting Developability of High-Concentration Antibody Therapeutics for Subcutaneous Delivery
High-concentration monoclonal antibody formulations are essential for enabling subcutaneous delivery but often suffer from developability challenges such as elevated viscosity, aggregation, and unfavorable protein–protein interactions. Early identification of these liabilities remains difficult using traditional experimental approaches alone. In this seminar, I will discuss recent efforts from our group to predict and understand high-concentration antibody behavior by integrating machine learning, molecular modeling, and biophysical characterization. I will highlight how sequence- and structure-based models can enable early developability screening, how small-angle X-ray scattering (SAXS) can reveal interaction signatures linked to viscosity, and how formulation strategies such as excipient screening can mitigate developability risks. Finally, I will discuss emerging challenges associated with novel antibody modalities and opportunities for data-driven approaches to accelerate biologic drug development.
Speaker Biography:
Dr. Pin-Kuang Lai is an Assistant Professor in the Department of Chemical Engineering and Materials Science at Stevens Institute of Technology. He received his B.S. and M.S. degrees in Chemical Engineering from National Taiwan University, and completed his Ph.D. in Chemical Engineering at the University of Minnesota in 2018. His doctoral research focused on developing computational and experimental approaches to study antimicrobial peptides. From 2018 to 2021, Dr. Lai conducted postdoctoral research at Massachusetts Institute of Technology, where he investigated antibody stability at high concentrations.
Dr. Lai has collaborated with leading pharmaceutical companies, including AstraZeneca, Merck, Sanofi, Takeda, and Johnson & Johnson, as well as national laboratories such as National Institute of Standards and Technology and Brookhaven National Laboratory. His research focuses on advancing computational tools—including machine learning and molecular simulations—alongside biophysical characterization methods such as NMR and SAXS to predict and analyze antibody aggregation and viscosity at high concentrations. Dr. Lai was named a 2024 Top Scholar in Antibody Research by ScholarGPS. He has been invited as a keynote speaker at the Bioprocessing Summit, AAPS National Biotechnology Conference, and PEGS Boston. In addition to his academic and research endeavors, Dr. Lai serves as an Assistant Editor for mAbs, a leading journal in antibody research and development.