NAMI: Ask the Expert: Precision Medicine Research: Hope for the Future OD044

An on-demand video and transcript of the presentation are available here [opens in new tab].

About The National Alliance on Mental Illness (NAMI)

The National Alliance on Mental Illness (NAMI) is the nation’s largest grassroots mental health organization dedicated to building better lives for the millions of Americans affected by mental illness. They are an alliance of more than 650 local Affiliates and 49 State organizations who work in your community to raise awareness and provide support and education to people with mental illness and their loved ones. Through awareness, advocacy and education, NAMI is committed to building stronger communities and a better future for everyone affected by mental illness.

Course Summary

Practice Level: Advanced

This course, based on the Ask the Expert webinar series by NAMI, introduces precision medicine as an emerging framework for improving prevention, diagnosis, and treatment by integrating individual variability in biology, environment, lifestyle, and social determinants of health. Using precision psychiatry as the focal application, the training reviews why current symptom-based diagnostic categories and “trial-and-error” prescribing approaches often fall short and how genomics, brain-based measures, and data science are being used to refine risk prediction and treatment matching. The course also summarizes current evidence and limitations related to pharmacogenetic testing and artificial intelligence–enabled prediction models, with attention to clinical utility, bias, and interpretability. Finally, the presentation highlights the NIH All of Us Research Program as a large-scale, diversity-centered resource intended to accelerate equitable discovery while emphasizing privacy protections and participant partnership. 

The course, with an intended audience of social workers, psychologists, marriage and family therapists, and counselors, translates rapidly evolving evidence in precision psychiatry into practice-relevant considerations for assessment, risk formulation, referral, client education, and ethically informed, equity-centered care planning across service settings.

Course Format

This course contains a participant guide, practice test, and on-demand video. When you’re ready, purchase the course by clicking the “Add To Cart” or “Enroll” button. This will let you take the test, complete the course evaluation and receive your certificate for CE credits.

Learning Objectives

1. Identify core elements of precision medicine that inform precision psychiatry.
2. Describe how psychiatric genomics findings contribute to evolving models of diagnosis and risk stratification. 
3. Explain data-driven methods used to improve prediction and treatment matching in mental health care.

Course Syllabus

• Foundations of Precision Medicine and Precision Psychiatry
• Genomics, Diagnostic Boundaries, and Risk Stratification in Mental Health
• Data-Driven Prediction and Treatment Matching (AI/EHR, Pharmacogenetics, Neurophysiology)
• Research Infrastructure and Implementation Considerations (All of Us; Equity, Privacy, and Participant Partnership)Overview

Current References

Abdelmoteleb, S., Ghallab, M., & IsHak, W. W. (2025). Evaluating the ability of artificial intelligence to predict suicide: A systematic review of reviews. Journal of Affective Disorders, 382, 525–539. https://doi.org/10.1016/j.jad.2025.04.078[opens in new tab]

Barak-Corren, Y., Castro, V. M., Nock, M. K., et al. (2020). Validation of an electronic health record–based suicide risk prediction modeling approach across multiple health care systems. JAMA Network Open, 3(3), e201262.https://doi.org/10.1001/jamanetworkopen.2020.1262[opens in new tab]

Choi, K. W., Lee, Y. H., Liu, Z., et al. (2023). Social support and depression during a global crisis. Nature Mental Health, 1, 428–435.https://doi.org/10.1038/s44220-023-00078-0[opens in new tab]

Denny, J. C., Rutter, J. L., Goldstein, D. B., et al. (2019). The “All of Us” Research Program. The New England Journal of Medicine, 381(7), 668–676.https://doi.org/10.1056/NEJMsr1809937[opens in new tab]

Greden, J. F., Parikh, S. V., Rothschild, A. J., Thase, M. E., Dunlop, B. W., DeBattista, C., Conway, C. R., Forester, B. P., Mondimore, F. M., Shelton, R. C., Macaluso, M., Li, J., Brown, K., Gilbert, A., Burns, L., Jablonski, M. R., & Dechairo, B. (2019). 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, 111, 59–67. https://doi.org/10.1016/j.jpsychires.2019.01.003[opens in new tab]

International Society of Psychiatric Genetics. (2019). Genetic testing statement.https://ispg.net/genetic-testing-statement/[opens in new tab]

Lee, Y. H., Liu, Z., Fatori, D., et al. (2022). Association of everyday discrimination with depressive symptoms and suicidal ideation during the COVID-19 pandemic in the All of Us Research Program. JAMA Psychiatry, 79(9), 898–906. https://doi.org/10.1001/jamapsychiatry.2022.1973[opens in new tab]

Oslin, D. W., Lynch, K. G., Shih, M.-C., et al. (2022). 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, 328(2), 151–161. https://doi.org/10.1001/jama.2022.9805[opens in new tab]

Purvis, R., Forrest, L. E., Young, M.-A., Limb, S., James, P., & Taylor, N. (2025). Defining next steps in the clinical implementation of polygenic scores: A landscape analysis of professional groups’ perspectives. Genetics in Medicine, 27(6), 101414. https://doi.org/10.1016/j.gim.2025.101414[opens in new tab]

Roberts, E., Flaum, N., & Evans, D. G. (2025). Clinical implementation of polygenic risk scores. European Journal of Human Genetics. https://doi.org/10.1038/s41431-025-01931-9[opens in new tab]

Serretti, A., Fabbri, C., & Fanelli, G. (2025). Polygenic scores and antidepressant treatment outcomes in major depression: A critical integrative review. Neuroscience Applied, 4, 105530. https://doi.org/10.1016/j.nsa.2025.105530[opens in new tab]

Simon, G. E., Johnson, E., Lawrence, J. M., et al. (2018). Predicting suicide attempts and suicide deaths following outpatient visits using electronic health records. American Journal of Psychiatry, 175(10), 951–960. https://doi.org/10.1176/appi.ajp.2018.17101167[opens in new tab]

Spittal, M. J., Guo, X. A., Kang, L., Kirtley, O. J., Clapperton, A., Hawton, K., et al. (2025). Machine learning algorithms and their predictive accuracy for suicide and self-harm: Systematic review and meta-analysis. PLOS Medicine, 22(9), e1004581.https://doi.org/10.1371/journal.pmed.1004581[opens in new tab]

Viale, L., Gentile, S., & Dell’Osso, L. (2025). Pharmacogenetic implications for antidepressant therapy in major depression: A systematic review covering 2019–2024. Journal of Clinical Medicine, 14(14), 5102. https://doi.org/10.3390/jcm14145102[opens in new tab]

White House Office of Science and Technology Policy. (2023). White House report on mental health research priorities.https://bidenwhitehouse.archives.gov/ostp/news-updates/2023/02/07/white-house-report-on-mental-health-research-priorities/[opens in new tab]  

American Academy of Child and Adolescent Psychiatry. (2020). Clinical use of pharmacogenetic tests in prescribing psychotropic medications for children and adolescents [Policy statement].https://www.aacap.org/AACAP/Policy_Statements/2020/Clinical-Use-Pharmacogenetic-Tests-Prescribing-Psychotropic-Medications-for-Children-Adolescents.aspx[opens in new tab]

Instructors

Dr. Jordan Smoller, MD, ScD, Director of Center for Precision Psychiatry, Department of Psychiatry at Massachusetts General Hospital

Dr. Jordan Smoller is the Massachusetts General Hospital (MGH) Trustees Endowed Chair in Psychiatric Neuroscience, Professor of Psychiatry at Harvard Medical School and Professor in Epidemiology at the Harvard School of Public Health. He is Associate Chief for Research in the MGH Department of Psychiatry, Director of the Center for Precision Psychiatry, Director of the Psychiatric and Neurodevelopmental Genetics Unit, an Associate Member of the Broad Institute, and President of the International Society of Psychiatric Genetics. He is an author of more than 500 scientific publications and is also the author of The Other Side of Normal (HarperCollins, 2012).

Nicole Errickson, LCSW

Nicole is a Licensed Clinical Social Worker (LCSW) in the state of Georgia. She brings over 19 years experience in the social work field, primarily working in school systems as a school social worker and with the McKinney-Vento grant. Over her career, Nicole has had several opportunities to help develop and execute professional development events. Nicole has a bachelor’s degree in psychology from the University of South Alabama and a Masters in Social Work from the University of Alabama.

Accreditation Approval Statements

CE4Less.com is approved by the American Psychological Association to sponsor continuing education for psychologists. CE4Less.com maintains responsibility for this program and its content.

CE4Less.com, provider #1115, is approved as an ACE provider to offer social work continuing education by the Association of Social Work Boards (ASWB) Approved Continuing Education (ACE) program. Regulatory boards are the final authority on courses accepted for continuing education credit. ACE provider approval period: 8/8/24-8/8/27.

Social workers completing this course receive 1 clinical continuing education credit.

We are committed to providing our learners with unbiased information. CE4Less never accepts commercial support and our authors have no significant financial or other conflicts of interest pertaining to the material.