Speaker Profile
Biography
Sarah Jenna is the co-founder and CEO of My Intelligent Machines (MIMs) and was previously an associate professor specialized in genomics and genetics at UQÀM. Sarah received her Ph.D. in Cell and Structural Biology, from Aix-Marseille University in France. She completed her postdoctoral training in cell signalling at McGill University and was Platform Manager of the Montréal Proteomic Network. In 2006, her dual expertise in cellular and genomic signalling led her to be awarded a NSERC (Natural Sciences and Engineering Research Council of Canada) Junior Canada Research Chair in Integrative Genomics and Cell Signaling at UQÀM. At the helm of MIMs, she translates her 20 years of experience and expertise to provide clients with cutting-edge integrative genomics strategies & systems biology while paying particular attention to the specific needs of life scientists working in BioPharma, and research institutes. She was part of the Top 10 Most Influential Women Leaders in 2021 by Exeleon Magazine.
AI and Data Science Showcase:
MIMs
Founded in 2016, Montreal-based My Intelligent Machines (MIMs) is a leader in artificial intelligence & systems biology. MIMs provides Biopharma companies with easy-to-implement augmented intelligence systems, allowing for accurate biological simulations at early R&D stages, to assist life scientists in the development of targeted and personalized therapies.
Use of Augmented Intelligence for Target and Biomarker Discovery
At MIMs, we have developed a unique augmented intelligence system that enables life scientists to capitalize on machine-based computer modelling, distributed computing & federated learning while leveraging their own expertise in life sciences, to identify targets with more clinical potential than classical bioinformatic approaches.
Session Abstract – PMWC 2022 Silicon Valley
The PMWC 2022 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.