A market-leading pharmacogenomic test
Offering the GeneSight test to your patients can provide a more personalized approach to mental health treatment. By analyzing how a patient’s genes may affect their outcomes to certain medications, the genetic insights from the GeneSight test can help healthcare providers in making more informed treatment decisions, potentially reducing the trial-and-error process.
GeneSight Psychotropic only includes genes in the algorithm that have a variant that has a significant impact on medication outcomes, as demonstrated in multiple well-designed studies.
The GeneSight Psychotropic test uses a weighted multi-gene approach that measures multiple genomic variants for each individual and weighs them together to provide comprehensive information about how an individual’s genetic variation may impact their outcomes with certain medications.
There are multiple peer-reviewed publications that support the clinical validity, clinical utility, and economic utility of the GeneSight Psychotropic test.
* Based on a review of six months of past claim data for major insurance carriers across the US. Last updated 2023.
Clinicians have ordered the GeneSight test for over 3,000,000 patients and counting
References: 1. Jablonski MR, King N, Wang Y, et al. Analytical validation of a psychiatric pharmacogenomic test. Personalized Medicine. 2018;15(3):189-197. doi:https://doi.org/10.2217/pme-2017-0094. 2. Shelton RC, Parikh SV, Law RA, et al. Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder. Psychiatry Research. 2020;290:113017. doi:https://doi.org/10.1016/j.psychres.2020.113017. 3. Parikh SV, Law RA, Hain DT, et al. Combinatorial pharmacogenomic algorithm is predictive of sertraline metabolism in patients with major depressive disorder. Psychiatry Research. 2022;308:114354. doi:https://doi.org/10.1016/j.psychres.2021.114354. 4. Rothschild AJ, Parikh SV, Hain D, et al. Clinical validation of combinatorial pharmacogenomic testing and single-gene guidelines in predicting psychotropic medication blood levels and clinical outcomes in patients with depression. Psychiatry Research. 2021;296:113649. doi:https://doi.org/10.1016/j.psychres.2020.113649. 5. Oslin DW, Lynch KG, Shih MC, et al. Effect of Pharmacogenomic Testing for Drug-Gene Interactions on Medication Selection and Remission of Symptoms in Major Depressive Disorder: The PRIME Care Randomized Clinical Trial. JAMA. 2022;328(2):151-161. doi:https://doi.org/10.1001/jama.2022.9805. 6. Greden JF, Parikh SV, Rothschild AJ, et al. Impact of pharmacogenomics on clinical outcomes in major depressive disorder in the GUIDED trial: A large, patient- and rater-blinded, randomized, controlled study. Journal of Psychiatric Research. 2019;111:59-67. doi:https://doi.org/10.1016/j.jpsychires.2019.01.003. 7. Winner JG, Carhart JM, Altar CA, et al. Combinatorial pharmacogenomic guidance for psychiatric medications reduces overall pharmacy costs in a 1 year prospective evaluation. Current Medical Research and Opinion. 2015;31(9):1633-1643. doi:https://doi.org/10.1185/03007995.2015.1063483.