This week, we’re delighted to be joined by Cody Schiffer, Associate Director, Machine Learning at SMPA - a biopharmaceutical company focused on delivering therapeutic and scientific breakthroughs in areas of critical patient need,
During this conversation, Cody and Ross discuss the construction, maintenance, and application of a knowledge graphic in biopharma, including how to integrate structured and unstructured data to support tasks like literature searches, competitive intelligence and drug discovery and the challenges in keeping a knowledge graph updated with new, real-time information.
Data in Biotech is a fortnightly podcast exploring how companies leverage data innovation in life sciences.
Discussed:
[1:09] Cody shares his background and career to date.
[2:43] Cody outlines how SMPA leverages data science to support its pipeline of investigational assets in healthcare.
[7:36] Cody explains how his team approaches helping scientists better understand scientific literature.
[12:44] Cody explains how the SMPA knowledge graph was constructed and how it is updated over time.
[18:13] Cody discusses how his team incorporates unstructured data in the knowledge graph.
[23:05] Cody explains how they apply weighting to the information that is gathered and ultimately fed into the knowledge graph.
[28:16] Cody shares the biggest lessons he has learned from building and maintaining the knowledge graph.
[34:48] Cody explains how he and SMPA view the build versus buy question when developing internal tools.
[38:47] Cody shares his thoughts on what the future holds for his team and the tools they are building internally.
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Data in Biotech