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Visual biology AI neural network recognize disease signatures in cellular pathway visualizations

Visual biology is an emerging paradigm that uses automated high-content, high- throughput visualization of cellular pathways, combined with AI analysis of large-scale experimental biology data. Images of cellular processes—such as protein-protein and protein-nucleic acid interactions, protein modifications, mRNA regulatory pathways, and enzymatic and cellular machinery activities—can now be generated from millions of diseased and healthy cells. This data enables the training of neural networks to recognize underlying disease mechanisms. AI technology combines this first-of-its-kind, unbiased large-scale experimental data with existing scientific knowledge to derive hypotheses on disease signatures, novel targets, and drugs. At the intersection of biology and AI, this webinar aims to demystify visual biology and showcase its practical applications in discovering novel targets and drugs. Join us to learn how Visual Biology can revolutionize your target discovery process and give you a competitive edge in developing novel therapies.

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Iris Alroy

Iris Alroy

Co-Founder and CSO, Anima Biotech

Iris Alroy, Ph.D., has over 25 years of experience in drug discovery, preclinical and early clinical development. Dr. Alroy has served as co-founder and CSO of Anima since 2015, supervising drug discovery and pipeline development in the emerging field of mRNA translation regulation. Prior to Anima, she acted as VP of Discovery at Proteologics and Pharmos Corp. and CEO of several startup biotech companies, including Fusimab, Ltd. and ProMining Therapeutics Ltd. Dr. Alroy earned her doctorate in Cell Biology from Cornell University and completed a post-doctoral fellowship at the Weizmann Institute. She has authored more than 20 scientific articles in peer-reviewed journals.

Vladislav Kim

Vladislav Kim

Machine Learning Researcher, Bayer

Vladislav Kim, PhD, is a machine learning researcher at Bayer, developing AI-driven computer vision solutions for early-stage drug discovery. Leveraging foundation models for complex bioimaging data, Dr. Kim is working on accelerating target discovery and improving the safety and efficacy profiles of preclinical drug candidates. Dr. Kim obtained his doctorate in Computational Biology from Heidelberg University.

Inbal Shapira Lots

Inbal Shapira Lots

Head of Data Analysis, Anima Biotech

Dr. Inbal Shapira Lots has served as Head of Data Analysis at Anima Biotech since 2016. She brings over a decade of expertise in algorithm design and machine learning, coupled with a unique blend of academic and industry experience. At Anima, Dr. Shapira Lots leads the development of advanced solutions for drug & target discovery, Mode of Action (MoA) studies, big data analytics, and automation. She earned her Ph.D. at the Leslie and Susan Gonda Multidisciplinary Brain Research Center at Bar Ilan University and has authored numerous publications in leading scientific journals, including SLAS Discovery and the Journal of Neuroscience Methods.

Surani Fernando
moderator

Surani Fernando

Healthcare journalist, writer & podcaster

Surani Fernando is a seasoned healthcare journalist and editor with over 13 years experience covering the biopharma industry. A Sydney native, she started her investigative journalism career in London covering clinical trials, M&A and financing deals for BioPharm Insight, later moving to New York to continue her work as an enterprise journalist and editorial leader for GlobalData and Reorg. She is now based in Madrid working as a freelance journalist, consultant writer and podcast producer.