Pharmacogenetic Testing: Proofs of Principle and Pharmacoeconomic Implications
Thierry Dervieux, Brian Meshkin, Bruce Neri
Mutation Research. 2005 Jun 3;573(1–2):180–194. doi:10.1016/j.mrfmmm.2004.07.025

This publication presents one of the earliest peer-reviewed frameworks examining the economic implications of pharmacogenetic testing. Co-authored by Brian Meshkin and colleagues at Prometheus Laboratories, the paper explores how pharmacogenetics can improve healthcare outcomes while reducing overall treatment costs, helping establish the field of pharmacogenomic health economics.

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Folate Nutrigenetics: A Convergence of Dietary Folate Metabolism, Folic Acid Supplementation, and Folate Antagonist Pharmacogenetics
Brian Meshkin et al.
Drug Metabolism Letters. 2007 Jan;1(1):55–60. doi:10.2174/187231207779814319

Building upon his work developing foundational pharmacogenetic assays for antifolate therapies, Brian Meshkin explores the relationship between dietary folate metabolism, nutritional genetics, and folic acid supplementation. The publication highlights the growing intersection between pharmacogenetics and personalized nutrition.

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Neurogenetic Interactions and Aberrant Behavioral Co-Morbidity of Attention Deficit Hyperactivity Disorder (ADHD): Dispelling Myths
David E. Comings, Thomas J. H. Chen, Kenneth Blum, Julie F. Mengucci, Seth H. Blum, Brian Meshkin
Behavior Genetics Review

This publication examines the complex genetic basis of ADHD, proposing that the disorder is highly polygenic and influenced by numerous genes involved in neurotransmitter metabolism, transport, and receptor function. The paper challenged conventional views of ADHD and contributed to the understanding of its biological foundations.

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An Observational Study of the Impact of Genetic Testing for Pain Perception in the Clinical Management of Chronic Non-Cancer Pain
Maneesh Sharma, Svetlana Kantorovich, Chee Lee, Natasha Anand, John Blanchard, Eric T. Fung, Brian Meshkin, Ashley Brenton, Steven Richeimer
Journal of Psychiatric Research. 2017 Jun;89:65–72. doi:10.1016/j.jpsychires.2017.01.015

Researchers from Proove evaluated the impact of incorporating genetic testing into the management of chronic pain. The study demonstrated how genetic information could assist clinicians in developing more individualized treatment strategies for patients experiencing chronic non-cancer pain.

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Observational Study to Calculate Addictive Risk to Opioids: A Validation Study of a Predictive Algorithm to Evaluate Opioid Use Disorder
Ashley Brenton, Steven Richeimer, Maneesh Sharma, Chee Lee, Svetlana Kantorovich, John Blanchard, Brian Meshkin
Pharmacogenomics and Personalized Medicine. 2017;10:187–195. doi:10.2147/PGPM.S123376

This validation study evaluated the Proove Opioid Risk algorithm, which integrates genetic and clinical variables to estimate an individual's risk for opioid use disorder. The publication provides evidence supporting the algorithm's application within precision medicine and opioid risk assessment.

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A Precision Medicine Approach to a Patient with Unresolved Pain Following Orthopedic Surgery: A Case Report
David Gazzaniga, Ashley Brenton, Brian Meshkin
Journal of Medical Case Reports. 2017;11(1):50. doi:10.1186/s13256-017-1207-5

This clinical case report describes the application of precision medicine in the treatment of a patient experiencing unresolved pain following orthopedic surgery. The report highlights how genetic testing informed clinical decision-making and personalized pain management.

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A Prospective, Longitudinal Study to Evaluate the Clinical Utility of a Predictive Algorithm That Detects Risk of Opioid Use Disorder
Ashley Brenton, Chee Lee, Katrina Lewis, Maneesh Sharma, Svetlana Kantorovich, Gregory A. Smith, Brian Meshkin
Journal of Pain Research. 2018;11:119–131. doi:10.2147/JPR.S139189

This prospective clinical study evaluated the real-world utility of the proprietary Proove predictive algorithm for opioid use disorder risk stratification. The findings support the use of integrated genetic and clinical data to improve individualized patient risk assessment.

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Adding Genetic Testing to Evidence-Based Guidelines to Determine the Safest and Most Effective Chronic Pain Treatment for Injured Workers
Brian Meshkin et al.
International Journal of Biomedical Science. 2015 Dec;11(4):157–165.

This publication outlines how pharmacogenetic testing can be incorporated into evidence-based treatment guidelines for injured workers suffering from chronic pain. The recommendations contributed to the broader discussion surrounding precision medicine in workers' compensation and informed later updates to clinical practice guidelines.

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Evaluation of a Predictive Algorithm That Detects Aberrant Use of Opioids in an Addiction Treatment Centre
J. Ramsay Farah, Chee Lee, Svetlana Kantorovich, Gregory A. Smith, Brian Meshkin, Ashley Brenton
Journal of Addiction Research & Therapy. 2017. doi:10.4172/2155-6105.1000312

This study evaluated the performance of the Proove Opioid Risk algorithm in an addiction treatment setting. The researchers reported strong predictive performance, supporting the algorithm's application for identifying individuals at elevated risk of opioid misuse within clinical addiction medicine.

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