In this episode of Evaluating Biopharma, host Ben Locwin and Scott Endicott, executive leader of Healthcare Solutions Integration, talk about data governance and data provenance—why they matter and how the industry can achieve them. With 30 years of experience, Endicott has a deep understanding of training AI and ML models, particularly when patient data is included, and offers advice on how to navigate the challenges of data governance and provenance in the near-term future. Links from...
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In this episode of Evaluating Biopharma, host Ben Locwin and Scott Endicott, executive leader of Healthcare Solutions Integration, talk about data governance and data provenance—why they matter and how the industry can achieve them. With 30 years of experience, Endicott has a deep understanding of training AI and ML models, particularly when patient data is included, and offers advice on how to navigate the challenges of data governance and provenance in the near-term future. Links from...
Episode: 06 - Process Intensification: PAT, AI, ML to Support Intensified Bioprocessing
Evaluating Biopharma
19 minutes
2 years ago
Episode: 06 - Process Intensification: PAT, AI, ML to Support Intensified Bioprocessing
Arthi Narayanan, innovation team leader of pharma technical operations at Genentech, and John Bonham-Carter, board member and VP of business development and product management at Erbi Biosystems, discuss how process analytical technology, artificial intelligence, and machine learning support intensified bioprocessing and improve inefficiencies. Narayanan talks about the expected outcomes predictive modeling will likely produce in the coming years, why data is the “power” of bioprocessing, and...
Evaluating Biopharma
In this episode of Evaluating Biopharma, host Ben Locwin and Scott Endicott, executive leader of Healthcare Solutions Integration, talk about data governance and data provenance—why they matter and how the industry can achieve them. With 30 years of experience, Endicott has a deep understanding of training AI and ML models, particularly when patient data is included, and offers advice on how to navigate the challenges of data governance and provenance in the near-term future. Links from...
