Sr. Manager & Head, Academic Medicine, Amazon Web Services (AWS)
Biography
Ken leads the AWS Academic Medicine Vertical which includes a team of Principal Trusted Advisors in Digital Health, Hospital Modernization, Precision Medicine, Clinical Care and Informatics, and HealthTech sub-verticals, and a team of field based and customer facing Healthcare Executive Advisors. He has over 30 years of healthcare experience, including founding and taking public a cell and gene therapy company. Prior experience includes being a Chief Clinical Officer, President and CEO for 10 years prior to joining AWS. Ken has a strong background in building and commercializing regulated products in the device, combination product, clinical software, and therapeutic biologics space.
AI and Data Science Showcase:
Amazon
AWS for Health is used by thousands of healthcare customers globally. It provides proven and easily accessible capabilities that help organizations increase the pace of innovation, unlock the potential of health data, and develop more personalized approaches to therapeutic development and care.
Digital Health Data Strategy – The First Step in Precision Medicine
Linking big data at the patient level is essential to enable physicians and researchers to truly test their precision medicine hypothesis. However, different types of data have various value, and it is important for institutions to prepare and implement an upfront data plan that powers research. In this talk, we will present various technology approaches to link and validate existing PHI data.
Session Abstract – PMWC 2022 Silicon Valley
Track 7 - June 28 10.00 A.M.-1.15 P.M.,Track 7 - June 29 11.00 A.M.-1.15 P.M.,Track 7 - June 30 9.00 A.M.-11.15 A.M.
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.
