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Selecting Anti-Depressants

Personalized Medicine. Selecting Anti-Depressants. Patent. This presentation is based on a patent application on personalized medication held by George Mason University. Scientists and government organizations have free access to this patent. Acknowledgement. Farrokh Alemi, Ph.D.

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Selecting Anti-Depressants

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  1. Personalized Medicine Selecting Anti-Depressants

  2. Patent • This presentation is based on a patent application on personalized medication held by George Mason University. Scientists and government organizations have free access to this patent

  3. Acknowledgement • Farrokh Alemi, Ph.D. • Manaf Zargoush • Harold Erdman, Ph.D. • Igor Griva, Ph.D. • Charles H. Evans, Jr., M.D., Ph.D. • Jee Vang, Ph.D. • Manabu Torii, Ph.D. • Steven Epstein, M.D.

  4. Case of George • Military service • Industrial manager, polite, defines himself a “medieval knight.” • First depression episode at 26, treated with clomipramine, dose unknown. • At 30 married with a daughter • At 45 return of depressive symptoms, treated with fluvoxamine 200–300 mg and mirtazapine 15 mg • Depression continues, loss of interest in work, difficulty with bi-polar daughter • Loss of daughter, divorce and loss of work • At 48, suicide

  5. Who Benefits from Citalopram? Beyond Efficacy: The STAR*D Trial. By Thomas R. Insel Am J Psychiatry. available in PMC 2006 September 30.

  6. Potential for Guided Treatmentto Increase Remission Citalopram

  7. Are Some People Hardwired to Get the Blues? Will they benefit from specific antidpressants? Read more: http://www.time.com/time/health/article/0,8599,1905083,00.html#ixzz0kWKdxlNH

  8. Terminology • Response to medication • Quick Inventory of Depressive Symptomlogy <=5 • Predictors of response • SNP • Allele • Most likely predictors • Serotonin transporter gene SLC6A4 • Serotonin transporter polymorphic region 5HTTLPR

  9. Predicting Response from Genetic Profile Source: http://www.youtube.com/watch?v=IMeJA_inoEM

  10. Success with Genetic Profiling: Hype or Hope

  11. Success with Genetic Profiling: Hype or Hope “… limited clinical utility in matching antidepressants to patient’s genetic profile” Peters EJ, Slager SL, Kraft JB, Jenkins GD, Reinalda MS, McGrath PJ, Hamilton SP. Pharmacokinetic genes do not influence response or tolerance to citalopram in the STAR*D sample. PLoS One. 2008 Apr 2;3(4):e1872.

  12. STAR*D Database • 12 month follow up post experimentation • Careful baseline and exit data • 4300 patients • 1933 with genetic data • 430,198 SNP per case • 25 likely SNP Garriock HA, Kraft JB, Shyn SI, Peters EJ, Yokoyama JS, Jenkins GD, Reinalda MS, Slager SL, McGrath PJ, Hamilton SP. A genome wide association study of citalopram response in major depressive disorder. Biol Psychiatry. 2010 Jan 15; 67(2): 133-8.

  13. Patients Like Me Algorithm • Test statistical significance of findings among the K most similar cases • Nearest defined? • Euclidian distance (percent of features matched) • CART classification • Statistical test? • CUSUM • Exponentially weighted cases

  14. Patients Like Me Algorithm • Test statistical significance of findings among the K nearest neighbors • Nearest defined? • Euclidian distance (percent of features matched) • Severity of illness • Statistical test? • CUSUM • Exponentially weighted cases

  15. Analysis for One Case

  16. Response to Citalopram Hypothetical Data

  17. Response to Citalopram Hypothetical Data

  18. Response to Citalopram Non responders Not sure Hypothetical Data

  19. Start of Classification and Regression Tree

  20. Classification and Regression Tree

  21. A Branch in a Classification and Regression Tree

  22. Classification and Regression Tree 25 Fold Cross-Validation Pruning

  23. Classification and Regression Tree Boosted

  24. Sample Rules from CART Branches

  25. Overall Percent of Cases Correctly Classified

  26. Conclusion • Response to citalopram is predictable • A large effect size is observed • Combination of genes matter • Subgroup of patients have different predictors Clinical Practice Can be Improved

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