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Uniting Biology and Digital Drug Discovery to identify new therapeutic opportunities in neurodegeneration
Abstract:
If neuroinflammation is on your radar watch this on-demand webinar co-hosted with our partner Delta4.
Explore how the combination of iPSC-derived models of neurotoxic reactive astrocytes (NRA) with a mechanistically informed in-silico model of neuroinflammation, enables rapid target identification and virtual compound screening in neurodegeneration.
Learn how AI-driven computational modeling can reveal druggable targets in neuroinflammation insights and is accelerating the discovery of novel therapeutics - faster, smarter, and without reliance on animal models.
Learning objectives:
- Functional and transcriptomic profiling of human NRA models.
- Adaptive and dynamic modeling of reactive astrocytes enhanced by omics-informed pathways and real human data.
- Models to simulate disease states, screen thousands of compounds in silico, and predict their effect on astrocyte reactivity.
- Selecting the top-performing candidates for experimental validation in vitro.
Dr. Elise Malavasi | Neuroscience Associate Director | Concept Life Sciences
Elise holds a PhD in Cellular and Molecular Basis of Disease from the University of Edinburgh and brings over 15 years of experience in neuroscience research. Since joining Concept Life Sciences in 2022, she has led the neuroscience team, shaping strategic direction, strengthening external collaborations, and driving scientific innovation across the service line. Elise is passionate about integrating cutting-edge cellular models and technologies to accelerate the development of new therapies for diseases of the central nervous system.
Dr. Samuel Walters | Application Scientist and Computational Biologist | Delta4
Samuel Walter is a bioinformatician with a strong biological background.
He started his PhD in 2016 at the University of Vienna, working on urban metagenomics in collaboration with the FH Campus Wien, as well as on host-pathogen interactions of Neisseria meningitidis, utilizing transcriptomic and proteomic data. Beside his research, Samuel has also been active as a lecturer at the University of Applied Sciences Wiener Neustadt, teaching “Comparative Genomics” and “Transcriptomics” in the Master of Science program Bio Data Science."