June 9, 2026 | At this year’s PEGS Boston, industry experts gathered on a panel to explore how AI and machine learning are deployed in biologics R&D today. Moderated by Peter M. Tessier, Ph.D., Albert M. Mattocks professor of pharmaceutical sciences and chemical engineering at University of Michigan, the panel consisted of Andrew Buchanan, Ph.D., head of discovery at a stealth-mode biotech company; Norbert Furtmann, Ph.D., head of biologics AI and design of large molecules research at Sanofi; Konrad S. Krawczyk, Ph.D., founder and CSO at NaturalAntibody SA; Andrew C.R. Martin, Ph.D., emeritus professor of bioinformatics and computational biology at University College London; Melody Shahsavarian, Ph.D., senior director of data strategy and digital transformation of biotherapeutics discovery research at Eli Lilly & Company; and Bernhardt L. Trout, Ph.D., professor of chemical engineering at Massachusetts Institute of Technology.
The discussion covered data readiness, the feasibility of designing complex targets, and the boundaries of current predictive capabilities, as well as practical workflow strategies, where AI already provides measurable impact, and future opportunities, such as immunogenicity prediction.
Links from this episode:
Pharmaceutical Sciences & Chemical Engineering, University of Michigan
University of Michigan
Sanofi
NaturalAntibody SA
Bioinformatics, UCL
Biosciences Computational Biology, UCL
University College London
Eli Lilly & Company
PANELIST BIOS
Andrew Buchanan, Ph.D., FRSC, Head of Discovery, Stealth Mode Biotech
Andrew Buchanan is SVP and head of discovery at a stealth-mode biotechnology company. He has extensive expertise in large molecule drug discovery and development, spanning target selection through first-in-human (FiH) studies. Andrew has led pipeline projects and multifunctional teams that have delivered over 20 FiH drug candidates in oncology, inflammation, and cardiovascular therapy areas, resulting in three marketed medicines to date. A key highlight of his career has been fostering interdisciplinary collaborations with academic and industry partners in AI/ML, PKPD, and translational biology. These efforts have led to new partnerships and over 50 original publications and patents. As a science leader, Andrew is passionate about mentoring early-career scientists and advancing the development of tomorrow’s medicines.
Norbert Furtmann, Ph.D., Head, Biologics AI & Design, Large Molecules Research, Sanofi
Upon finishing his studies in pharmaceutical sciences, Dr. Furtmann pursued his interdisciplinary doctorate thesis in computational life sciences and pharmaceutical chemistry at the University of Bonn, focusing on computer-aided design, synthesis, and biological evaluation of protease inhibitors. After starting his professional career at Merck KGaA as principal scientist, he joined Sanofi in 2016 as lab head for data science within the biologics research department. Currently, Dr. Furtmann heads the global biologics AI and design teams responsible for the computational design and optimization of next-generation protein therapeutics.
Konrad S. Krawczyk, Ph.D., Founder & CSO, NaturalAntibody SA
Konrad Krawczyk specializes in computational methods to develop antibody-based therapeutics. He obtained doctorate and pursued a postdoc at the Oxford Protein Informatics Group, contributing to leading software currently used by academia and pharma industry alike. He was a postdoc and assistant professor of precision medicine at the University of Southern Denmark. Currently, he is the technical founder of NaturalAntibody, company that is focused on development and implementation of computational innovations in the pharma sector focused on antibody-based therapeutics.
Andrew C.R. Martin, Ph.D., Emeritus Professor, Bioinformatics and Computational Biology, University College London
Andrew Martin is emeritus professor of bioinformatics and computational biology at University College London (UCL). He obtained his undergraduate degree and doctorate degree from the University of Oxford. After some time self-employed developing scientific software, including working for Oxford Molecular on software developed during his doctorate program, he joined Professor Dame Janet Thornton's group at UCL. He then went on to be technical director at Inpharmatica before joining the University of Reading and then returning to UCL on 2004. His interests have been in developing software and methods for application to protein sequence and structure. In particular, he has focused on the effects of mutations and on antibodies. He developed one of the first methods for antibody modelling (AbM) and the first searchable antibody-specific sequence database (KabatMan), which has since developed into an integrated workbench for analysis of antibody sequence and structure (abYsis). He is co-founder of abYsis, Ltd. and consults for several companies. He has acted as an expert witness in a number of high-profile patent disputes and is an adviser to the WHO-INN on the naming and annotation of antibody-based drugs.
Melody Shahsavarian, Ph.D., Senior Director, Data Strategy & Digital Transformation, Biotherapeutics Discovery Research, Eli Lilly & Company
Melody Shahsavarian, Ph.D. is senior director of data strategy and digital transformation at Eli Lilly. Throughout her career, she has worked on development of different technology platforms for biologics discovery, such as implementation of immune in vitro phage display antibody libraries, droplet microfluidics for high-throughput sequencing of antibodies at single cell level, and next-generation-sequencing for immune repertoire profiling. She has a bachelor’s degree in bioengineering from the Jacobs School of Bioengineering at University of California San Diego and a master’s degree in biotechnology from Joseph Fourier University in Grenoble. During her doctorate program at the Enzymatic and Cellular Engineering Laboratory of Sorbonne University, she studied the presence and implication of catalytic antibodies in health and disease using mouse models and high-throughput in vitro display technologies. In her current role, she leads a team responsible for the establishment and execution of data strategy at BioTDR, in line with the company’s aspirations for digital transformation toward an AI-enabled biologics discovery process.
Bernhardt L. Trout, Ph.D., Professor, Chemical Engineering, Massachusetts Institute of Technology
Bernhardt L. Trout is the Raymond F. Baddour, ScD, (1949) professor of chemical engineering at MIT. He received his bachelor’s and master’s degrees from MIT and his doctorate degree from the University of California at Berkeley. In addition, he performed post-doctoral research at the Max-Planck Institute. Trout’s research focuses on the development of advanced manufacturing processes and rational tools for formulation and product design, primarily liquid formulations, but also lyophilized formulations. A major aspect of his research focuses on developing both microscopic and macroscopic models to design stable formulations efficiently. In addition, he is co-chair of the International Symposium on Continuous Manufacturing of Pharmaceuticals. He has published over 200 papers and has 18 patents issued or pending.
MODERATOR BIO
Peter M. Tessier, Ph.D., Albert M. Mattocks Professor, Pharmaceutical Sciences & Chemical Engineering, University of Michigan
Peter Tessier is the Albert M. Mattocks (Endowed) professor in the departments of chemical engineering, pharmaceutical sciences, and biomedical engineering, and a member of the Biointerfaces Institute at the University of Michigan in Ann Arbor, MI. He received his doctorate degree in chemical engineering from the University of Delaware (2003, NASA Graduate Fellow) and performed his postdoctoral studies at the Whitehead Institute for Biomedical Research at MIT (2003-2007, American Cancer Society Fellow). Tessier started his independent career as an assistant professor in the department of chemical and biological engineering at Rensselaer Polytechnic Institute in 2007, and he was an endowed full professor at Rensselaer prior to moving to the University of Michigan in 2017. Tessier’s research focuses on designing, optimizing, characterizing, and formulating a class of large therapeutic proteins (antibodies) that hold great potential for detecting and treating human disorders ranging from cancer to Alzheimer’s disease. He has received a number of awards and fellowships in recognition of his pioneering work: Pew Scholar Award in Biomedical Sciences (2010-2014), Humboldt Fellowship for Experienced Researchers (2014-2015), Young Scientist Award from the World Economic Forum (2014), Young Investigator Award from the American Chemical Society (2015), and NSF CAREER Award (2010-2015).