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Scott, Stuart A

0000-0001-5720-1864

Mayo Clinic

Department of Pathology, Stanford University, Stanford, California, USA.

Citations 5

Progress in Pharmacogenomics Implementation in the United States: Barrier Erosion and Remaining Challenges
Smith, D. Max , Aquilante, Christina L. , Deverka, Patricia A. , Devine, Emily Beth , Dunnenberger, Henry M. , Empey, Philip E. , Hertz, Daniel L. , Monte, Andrew A. , Moyer, Ann M. , Pratt, Victoria M. , Saulsberry, Loren , Oni‐Orisan, Akinyemi , Douglas, Michael P , Devine, Beth , Dunnenberger, Henry M , Empey, Philip E , Hertz, Daniel L , Moyer, AM , Patel, Jai N , Pratt, Victoria M , Saulsberry, Loren , Scott, Stuart A , Voora, Deepak , Woodahl, Erica L , Whirl-Carrillo, Michelle , Oni-Orisan, Akinyemi , Smith, D Max , Scott, Stuart A. , Whirl‐Carrillo, Michelle

Clinical Pharmacology & Therapeutics | June 5, 2025 | Volume: 118 | Issue: 4 | Pages: 778-789

10.1002/cpt.3736 Get It

Barriers to incorporating pharmacogenetics into routine clinical practice in the United States are well documented. Initial surveys by the Clinical Pharmacogenetics Implementation Consortium (CPIC) in 2009 and 2010 identified barriers across four key domains that have hindered the widespread adoption of clinical pharmacogenetic testing. These are presented verbatim as: (i) absence of a definition of the processes required to interpret genotype information and to translate genetic information into clinical actions; (ii) need for recommended drug/gene pairs to implement clinically now; (iii) clinician resistance to consider pharmacogenetic information at the bedside; and (iv) concerns about test costs and reimbursement. Over time, many of these challenges have been overcome, and clinical pharmacogenetic testing has subsequently reached broader implementation. Despite this progress, several barriers remain that block further adoption. This narrative review used authors' expertise and experience to identify and describe current barriers to pharmacogenetic implementation across seven domains in the United States: equity and inclusion; guidelines and supporting evidence; regulatory agency oversight; payer coverage and insurance; availability of quality pharmacogenetic tests; electronic health records; and provider and patient education. Within each domain, it revisits past successes and challenges and explores remaining barriers. We also propose solutions to address ongoing challenges across these domains, including further expansion of recommendations beyond pharmacogenetic‐specific guidelines, standards for designing clinical decision support tools, and broader pharmacogenetics education. Addressing these remaining obstacles directs work to enable broader adoption of clinical pharmacogenetic implementation to ultimately improve patient outcomes.
Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network
Crosslin, DR, Owusu‐Obeng, Aniwaa, Wallace, John R. , Almoguera, Berta , Basford, MA, Bielinski, Suzette J. , Carrell, DS, Connolly, John J. , Doheny, KF, Gallego, CJ, Gordon, Allan , Kirby, Jacqueline, Kitchner, Terrie, Manzi, Shannon , Mejia, A R, Pan, Vivian , Perry, Cassandra, Peterson, JF, Prows, CA, Ralston, James D. , Scott, Stuart A. , Scrol, Aaron, Smith, Maureen E. , Stallings, SC, Veldhuizen, Tamra L., Wolf, W.A., Volpi, Simona , Wiley, Kenneth L , Manolio, Teri A. , Böttinger, Erwin P. , Brilliant, MH, Carey, David J. , Chisholm, Rex L. , Chute, CG, Jl, Haines, Håkonarson, Håkon , Harley, JB, Holm, Ingrid A. , Kullo, IJ, Jarvik, GP, Larson, EB, McCarty, Catherine A. , Williams, MS, Denny, Joshua C. , Rasmussen‐Torvik, LJ, Roden, DM, Ritchie, MD, Rasmussen‐Torvik, Laura J. , Jarvik, Gail P. , Peterson, Josh F. , Bush, William S. , Wallace, J, Crawford, Dana C. , Keating, Brendan J. , Perry, CL, Peterson, JF, Stallings, SC, Li, R, Roden, DM, Ritchie, M.D., Holm, Ingrid A , Hakonarson, Hakon , Denny, Joshua C , Jarvik, Gail P , Bielinski, Suzette , Gordon, Adam S , Connolly, John J , Peterson, Josh F , Scott, Stuart A , Rasmussen-Torvik, Laura J

Clinical Pharmacology & Therapeutics | February 9, 2016 | Volume: 100 | Issue: 2 | Pages: 160-169

10.1002/cpt.350 Get It

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.
Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting
Kalman, LV, Agúndez, JAG, Appell, Malin Lindqvist , Black, J.H., Bell, GC, Boukouvala, Sotiria , Bruckner, Carsten, Bruford, Elspeth A. , Caudle, KE, Coulthard, SA, Daly, Ann K. , Tredici, AL Del, Dunnen, Johan T. den , Drozda, Katarzyna, Everts, Robin E. , Flockhart, David A., Freimuth, Robert R. , Hachad, Houda , Hartshorne, Toinette, Ingelman‐Sundberg, Magnus , Klein, Teri E. , Lauschke, Volker M. , Maglott, DR, McLeod, HL, McMillin, GA, Ua, Meyer, Dj, Müller, Nickerson, D. A., Oetting, WS , Pacanowski, MA, Vm, Pratt, Relling, MV, Roberts, Angharad M. , Ws, Rubinstein, Sangkuhl, Katrin , Schwab, Matthias , Scott, Stuart A. , Sim, SC, Thirumaran, RK, Toji, LH, Tyndale, Rachel F. , Schaik, RHN van, Whirl‐Carrillo, Michelle , Yeo, K. L. B., Zanger, UM, Agúndez, José A. G. , Müller, Daniel J. , Agúndez, JAG, Gaedigk, Andrea , Relling, Mary V. , Toji, Lorraine H., Whirl-Carrillo, Michelle , Agúndez, José A G , Hachad, Houda , Müller, Daniel J , Tyndale, Rachel F , Freimuth, Robert R , Klein, Teri E , Scott, Stuart A , Schwab, Matthias

Clinical Pharmacology & Therapeutics | October 20, 2015 | Volume: 99 | Issue: 2 | Pages: 172-185

10.1002/cpt.280 Get It

This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.
Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors
Hicks, J K, Bishop, JR, Dj, Müller, Leckband, SG, Leeder, JS, Graham, RL, Chiulli, DL, LLerena, Adrián , Skaar, TC, Scott, Stuart A. , Stingl, Julia , Klein, Teri E. , Caudle, KE, Leeder, J. Steven , Müller, Daniel J. , Sangkuhl, Katrin , Ji, Yuan , Skaar, T.C., Gaedigk, Andrea , LLerena, Adrián , Müller, Daniel J , Klein, Teri E , Scott, Stuart A

Clinical Pharmacology & Therapeutics | May 13, 2015 | Volume: 98 | Issue: 2 | Pages: 127-134

10.1002/cpt.147 Get It

Selective serotonin reuptake inhibitors (SSRIs) are primary treatment options for major depressive and anxiety disorders. CYP2D6 and CYP2C19 polymorphisms can influence the metabolism of SSRIs, thereby affecting drug efficacy and safety. We summarize evidence from the published literature supporting these associations and provide dosing recommendations for fluvoxamine, paroxetine, citalopram, escitalopram, and sertraline based on CYP2D6 and/or CYP2C19 genotype (updates at www.pharmgkb.org ).