Implementation of preemptive DNA sequence–based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study

Liewei Wang, Steven E. Scherer, Suzette J. Bielinski, Donna M. Muzny, Leila A. Jones, John Logan Black, Ann M. Moyer, Jyothsna Giri, Richard R. Sharp, Eric T. Matey, Jessica A. Wright, Lance J. Oyen, Wayne T. Nicholson, Mathieu Wiepert, Terri Sullard, Timothy B. Curry, Carolyn R. Rohrer Vitek, Tammy M. McAllister, Jennifer L. St. Sauver, Pedro J. CaraballoKonstantinos N. Lazaridis, Eric Venner, Xiang Qin, Jianhong Hu, Christie L. Kovar, Viktoriya Korchina, Kimberly Walker, Harsha Vardhan Doddapaneni, Tsung Jung Wu, Ritika Raj, Shawn Denson, Wen Liu, Gauthami Chandanavelli, Lan Zhang, Qiaoyan Wang, Divya Kalra, Mary Beth Karow, Kimberley J. Harris, Hugues Sicotte, Sandra E. Peterson, Amy E. Barthel, Brenda E. Moore, Jennifer M. Skierka, Michelle L. Kluge, Katrina E. Kotzer, Karen Kloke, Jessica M. Vander Pol, Heather Marker, Joseph A. Sutton, Adrijana Kekic, Ashley Ebenhoh, Dennis M. Bierle, Michael J. Schuh, Christopher Grilli, Sara Erickson, Audrey Umbreit, Leah Ward, Sheena Crosby, Eric A. Nelson, Sharon Levey, Michelle Elliott, Steve G. Peters, Naveen Pereira, Mark Frye, Fadi Shamoun, Matthew P. Goetz, Iftikhar J. Kullo, Robert Wermers, Jan A. Anderson, Christine M. Formea, Razan M. El Melik, John D. Zeuli, Joseph R. Herges, Carrie A. Krieger, Robert W. Hoel, Jodi L. Taraba, Scott R. St. Thomas, Imad Absah, Matthew E. Bernard, Stephanie R. Fink, Andrea Gossard, Pamela L. Grubbs, Therese M. Jacobson, Paul Takahashi, Sharon C. Zehe, Susan Buckles, Michelle Bumgardner, Colette Gallagher, Kelliann Fee-Schroeder, Nichole R. Nicholas, Melody L. Powers, Ahmed K. Ragab, Darcy M. Richardson, Anthony Stai, Jaymi Wilson, Joel E. Pacyna, Janet E. Olson, Erica J. Sutton, Annika T. Beck, Caroline Horrow, Krishna R. Kalari, Nicholas B. Larson, Hongfang Liu, Liwei Wang, Guilherme S. Lopes, Bijan J. Borah, Robert R. Freimuth, Ye Zhu, Debra J. Jacobson, Matthew A. Hathcock, Sebastian M. Armasu, Michaela E. McGree, Ruoxiang Jiang, Tyler H. Koep, Jason L. Ross, Matthew G. Hilden, Kathleen Bosse, Bronwyn Ramey, Isabelle Searcy, Eric Boerwinkle, Richard A. Gibbs, Richard M. Weinshilboum

Research output: Contribution to journalArticlepeer-review


Purpose: The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. Methods: Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response–related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug–gene pairs, were deposited preemptively in the Mayo electronic health record. Results: For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. Conclusion: Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.

Original languageEnglish (US)
Pages (from-to)1062-1072
Number of pages11
JournalGenetics in Medicine
Issue number5
StatePublished - May 2022


  • Clinical translation
  • Implementation
  • Individualized medicine
  • Pharmacogenomics
  • Pre-emptive clinical DNA sequencing

ASJC Scopus subject areas

  • Genetics(clinical)


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