Computational Antibody Discovery: State of the Art, June 22, 2023
Computational Antibody Discovery Symposium - Tzvika Hartman
Proteins are complex machines that can sense, and dynamically respond to, changes in their surroundings. Moreover, they have the capability to agonize other proteins or bind to diverse targets, depending on the prevailing biological conditions. Despite this incredible functional potential, therapeutic proteins are currently being utilized primarily as inert antagonists. This underutilization of protein functionality represents a significant missed opportunity. Biolojic Design’s computational platform enables the creation of dynamic antibodies. These antibodies are programmed to react to environmental changes and exhibit distinct actions under varying biological conditions. This approach is geared to yield more effective and safer therapies. The first computationally designed dynamic antibody is currently in phase 1/2 clinical trials. During this talk, I will provide an overview of Biolojic’s design process, which combines both computational and experimental techniques. I will also highlight the distinctive characteristics and functions of the antibodies created through this approach.
Tzvika Hartman, Senior Vice President Computation at Biolojic Design since 2021, has over 30 years of experience in computer science research and software engineering. He started his career in an Elite intelligence unit in the IDF as a mathematics researcher. He received degrees in mathematics and computer science from Bar-Ilan University, then conducted post-graduate work in the Weizmann Institute. During his studies, which focused on computational complexity and on algorithms for bioinformatics, mainly DNA sequencing and genome rearrangements, he also worked as a part-time software engineer in Orbotech. While at Google Tel-Aviv as a software engineer and researcher for 13 years, Dr. Hartman worked on projects and products such as search engine infrastructure and quality, Google Trends, and routing optimization of Google’s internal data center network. He then initiated, founded, and managed Google Tel-Aviv’s Health group for 5 years, leading various projects such as de-identification of healthcare data, extracting information from medical notes, and predictions based on EHR of ICU patients.
Agenda
Introduction - Janice Reichert (The Antibody Society); Konrad Krawczyk (Natural Antibody); Andrew Buchanan (AstraZeneca)
Speaker 1) Pietro Sormanni (University of Cambridge). Third-generation approaches of antibody discovery and optimization
2) Tzvika Hartman (Biolojic Design). AI-driven design of smart therapeutics
3) Victor Greiff (University of Oslo). Computational developability profiling of antibody repertoire data
4) Sandeep Kumar (Boehringer Ingelheim). Biopharmaceutical Informatics: Syncretic use of computation and experimentation in discovery and development of biotherapeutics
5) Ben Holland (Antiverse). Machine learning-based design of antibodies against difficult targets
Panel discussion: Panelists provided their opinions and insights on these questions:
1. What properties are more urgent to be able to design in silico - binding specificity, developability or something else?
2. What performance should computational antibody design achieve to improve upon established protocols?
3. What are the biggest hurdles for computational antibody discovery to achieve its full potential (models, data or something else)?
4. How could industry and academia complement each other to solve the problem of computationally designing antibodies?
5. What role does big tech/biopharma have to play in development and adoption of computational antibody design paradigms?
Concluding remarks: Andrew Buchanan (AstraZeneca)
