In this talk, Murat speaks withTzvika Hartman, Senior Vice President of Computation at Biolojic Design, a company curating AI-designed antibodies focused on autoimmune diseases and immuno-oncology applications.
Biolojic uses machine learning to design 'programmable' antibodies with more precise molecular effects. These antibodies work dynamically with their environment, both temporally and spatially, opening avenues for new ways to alter biology. Their lead candidate, AU-007, pioneered by spin-out company Aulos Bioscience, is being advanced through Phase II clinical studies in solid tumour cancers.
Don't miss this exciting opportunity to learn about the technology and strategies at Biolojic Design directly from Tzvika. Furthermore, we'll be exploring Tzvika's fascinating and eventful career.
About Tzvika:
Tzvika has more than 30 years of experience in computer science research and software engineering. He worked at Google, Tel Aviv for 8 years as a software engineer, before founding Google's Health group in Tel Aviv, leading various projects over 5 years. Tzvika now leads the computational advancements at Biolojic Design. Things mentioned:
Tzvika Hartman, Senior Vice President of Computation at Biolojic Design.
Weitzman Institute
Google, Tel Aviv
Google Trends
'Multibodies', Biolojic's proprietary antibody format.
ChatGPT
Novartis
Eli Lilly
AstraZeneca
AU-007, selective effector cells agonist for IO - Anti-IL2 epitope-specific antibody.
Additional Materials:
Watch the recording of the live event! https://youtu.be/XKJFFcFMt5c?feature=shared
About Antiverse:
Antiverse was co-founded in 2017 with the goal of engineering the future of drug discovery to change people's lives. Based in Cardiff, Antiverse combines machine learning and phage display techniques to model antibody-antigen interactions. The current version of the platform uses next-generation sequencing and AI to design diverse antibody candidates for any given target. The technology is being developed to enable the discovery of biologics for difficult-to-drug targets associated with cancer, heart, and lung diseases.
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