Michael (Buz) Waitzkin JD

Buz Waitzkin

Core Faculty

Michael (Buz) Waitzkin, JD

Focus Areas
Degrees

LLM, Yale University

JD, Stanford University

After more than 30 years of litigation experience in Washington, DC, Michael “Buz” Waitzkin joined the faculty at Duke University where he teaches courses on science law and policy, ethics, data use and privacy, federal regulation and other issues related to emerging technologies. He is the Deputy Director of the Initiative for Science & Society, Director of Graduate Studies for the Masters in Bioethics & Science Policy, a Core Faculty Member in the Duke Margolis Institute for Health Policy and has appointments as Senior Lecturing Fellow in both the Law School and Science & Society and Adjunct Faculty in the Medical School.


He is a co-founder and member of the board of Orbit Genomics, a start-up company developing and commercializing a genomic diagnostic technology, based on microsatellites, which others have discarded as “junk DNA”.

 

He practiced law in the District of Columbia for 35 years, where he handled complex commercial and criminal cases in federal and state trial and appellate courts throughout the country. He has extensive experience in advising the biomedical research community on issues relating to legal and regulatory strategy, product acquisition, exclusivity strategies, clinical research and ethics. He also served as Special Counsel to the President in the White House Counsel’s Office.

He attended the University of Virginia (BA 1971; Phi Beta Kappa, Echols Scholar), Stanford Law School (JD 1974) and Yale Law School (LLM 1975, Commonwealth Fellow in Law, Science and Medicine).

Drake C, Hinz EM, Granger BB, Granados I, Rader A, Pitcher A, et al. Implementation of NCCARE360, a Digital Statewide Closed-Loop Referral Platform to Improve Health and Social Care Coordination: Evidence from the North Carolina COVID-19 Support Services Program. North Carolina Medical Journal. 2024 Jan 1;85(2):134–42.

Drake C, Rader A, Clipper C, Haney M, Bulgin D, Cameron B, et al. Adaptation to Telehealth of Personalized Group Visits for Late Stage Diabetic Kidney Disease. Kidney360. 2023 Dec 1;4(12):1708–16.

Wang SM, Hogg HDJ, Sangvai D, Patel MR, Weissler EH, Kellogg KC, et al. Development and Integration of Machine Learning Algorithm to Identify Peripheral Arterial Disease: Multistakeholder Qualitative Study. JMIR Form Res. 2023 Sep 21;7:e43963.