MSACL 2019 US Abstract

Investigating the Skin Metabolome using Untargeted Metabolomics and the Initial Development Towards Non-Invasive Drug Monitoring

Alan K. Jarmusch(1,2), Emmanuel O. Elijah(1,2), Fernando Vargas(1,2), Amina Bouslimani(1,2), Ricardo R. da Silva(1,2), Madeleine Ernst(1,2), Mingxun Wang(1,2), Krizia Karen del Rosario(1), Shirley M. Tsunoda(1), and Pieter C. Dorrestein(1,2)
(1) Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California - San Diego, La Jolla, California 92093, United States of America (2) Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA 92093, United States of America

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Alan Jarmusch (Presenter) University of California, San Diego

Presenter Bio: Alan K. Jarmusch received his B.S. in Biochemistry from the University of North Carolina at Greensboro, mentored by Nadja B. Cech. He subsequently received a Ph.D. in Analytical Chemistry from Purdue University, specializing in mass spectrometry, and was mentored by R. Graham Cooks. His long-term research interest is translational medicine focusing on new mass spectrometry technology including ambient ionization, untargeted metabolomics, and big data.

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

Human skin is complex yet little is known about the chemicals on the skin. We aim to develop a non-invasive method for the detection and monitoring of drugs via human skin. Untargeted metabolomics using LC-MS/MS was used to explore what chemical information can be obtained from skin. Samples were collected from multiple body locations of 15 kidney transplant recipients. We will present the differences in the skin metabolome between axillary, face, and hand samples, and the detection and location of drugs. Proof-of-concept results will be presented which support that the reported method is currently capable of qualitative assessment of drugs.