1. Tailoring Medication to Patient Characteristics Farrokh Alemi, Ph.D. George Mason University

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

3. Privilege

4. What is informatics?

5. Anything you want it to be Anything you want it to be

6. It could be … Level 1 1. Identify the need for IT applications in medicine and healthcare 2. Demonstrate competence in the use of appropriate technologies, communication and organisational skills 3. Apply organisational techniques to interpret information and use knowledge 4. Deploy skills required in the administration of patients and their records 5. Describe the characteristics of health and social care information systems. 6. List the strengths and weaknesses of e-communication in healthcare. 7. Explain statistical reports. Level 2 8. Discuss and apply advanced theoretical and practical applications of informatics and computer science. 9. Demonstrate use and design of software. 10. Present data and information processing skills, analyse and assess different coding systems in healthcare. 11. Define and evaluate informatics standards. 12. Display an awareness of the fields of Medicine, health and biosciences and NHS organisation. 13. Show appropriate and professional customer service skills. 14. Describe applications of biomedical informatics specialities. Level 3 15. Critically discuss ethical issues and patients privacy. 16. Manage, implement and assess Information and Communication Technology. 17. Identify and synthesize solutions for technical/security faults 18. Present information regarding image and signal processing 19. Plan, implement, monitor, evaluate and complete projects. 20. Exhibit managerial skills and knowledge, demonstrate financial awareness, apply problem-solving skills and describe different project management frameworks.

7. It could be … Computational biogenetics Computational biogenetics Text processing & social networks Text processing & social networks Bioinformatics Bioinformatics Electronic Health Record Electronic Health Record Robotics Robotics Expert systems & machine learning Expert systems & machine learning Decision support systems Decision support systems Online management of patients Online management of patients Ergonomics Ergonomics …

8. Technology is Seductive Promises efficiency Promises efficiency

9. Technology is Seductive Promises efficiency Promises efficiency Takes you to new directions Takes you to new directions A classical bait and switch

10. You cannot take a car for a walk Go short distances Go short distances Drive to new destinations Drive to new destinations Roads, evolution Roads, evolution

11. Case of Personalized Medicine What is it and how it changes us?

12. Medication Benchmarks: Selection of Antidepressants Many options are possible: Many options are possible: tricyclic antidepressants (TCAs), tricyclic antidepressants (TCAs), monoamine oxidase inhibitors, monoamine oxidase inhibitors, selective serotonin reuptake inhibitors (SSRIs), selective serotonin reuptake inhibitors (SSRIs), nonselective serotonin–norepinephrine reuptake inhibitors (SNRIs), nonselective serotonin–norepinephrine reuptake inhibitors (SNRIs), the selective norepinephrine reuptake inhibitors (selective NRIs) the selective norepinephrine reuptake inhibitors (selective NRIs) other miscellaneous agents, such as mirtazapine. other miscellaneous agents, such as mirtazapine.

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

14. First Treatment not Enough Who responds to SSRI citalopram? Highly educated Currently employed Caucasian women Few complicating psychiatric or medical disorders. At least 70% of patients did not respond. Beyond Efficacy: The STAR*D Trial. By Thomas R. Insel Am J Psychiatry. available in PMC 2006 September 30.

15. First Treatment not Enough Who responds to SSRI citalopram? Highly educated Currently employed Caucasian women Few complicating psychiatric or medical disorders. At least 70% of patients did not respond. Beyond Efficacy: The STAR*D Trial. By Thomas R. Insel Am J Psychiatry. available in PMC 2006 September 30.

16. First Treatment not Enough Who responds to SSRI citalopram? Highly educated Currently employed Caucasian women Few complicating psychiatric or medical disorders. At least 70% of patients did not respond. Beyond Efficacy: The STAR*D Trial. By Thomas R. Insel Am J Psychiatry. available in PMC 2006 September 30. Not George

17. Medication Benchmarks: Selection of Antidepressants 70% not responsive 70% not responsive Six weeks before efficacy can be examined Six weeks before efficacy can be examined Sometimes 2-3 years searching for right medication Sometimes 2-3 years searching for right medication

18. Variability in Outcomes George is not alone, poor management of depression is affecting many.

19. What We Want? Medication That Works for Me

20. Rethinking Role of Data Patient data stored Data of others Patient data retrieved Care reminders Patient info displayed EHR Data warehousing Discovery Clinical Education Care Decisions

21. Rethinking Role of Data Patient data stored Data of others Patient data retrieved Patient info displayed EHR Data warehousing Discovery Clinical Education Care Decisions Care reminders Similar patients

22. Rethinking Role of Data Patient data stored Data of others Patient data retrieved Patient info displayed EHR Data warehousing Discovery Clinical Education Care Decisions Analytics: care forecasts Similar patients

23. Medication Benchmarks: Selection of Antidepressants Age Age Gender Gender Race Race Ethnicity Ethnicity Concurrent drugs Concurrent drugs Methadone Methadone Buprenorphine Buprenorphine Diet Diet Grapefruit Grapefruit Genetics Genetics CYP2D6 CYP2C19 CYP3A4 CYP1A2 Concurrent illness Concurrent illness Cancer Diabetes

24. Medication Benchmarks: Selection of Antidepressants Steps in Algorithm Steps in Algorithm 1. Select characteristics that make patient different from norm 2. Calculate similarity to patients in the database Based on GMU patent. Confidential communication

25. Medication Benchmarks: Selection of Antidepressants Steps in Algorithm Steps in Algorithm 1. Select characteristics that make patient different from norm 2. Calculate similarity to patients in the database Based on GMU patent. Confidential communication Number of features matched Features in one but not the other

26. Medication Benchmarks: Selection of Antidepressants Steps in Algorithm Steps in Algorithm 3. Reported average outcomes for different anti-depressants weighted by similarity of patients: Based on GMU patent. Confidential communication

27. Medication Benchmarks: Selection of Antidepressants Easy to implement Easy to implement 8 lines of SQL code 8 lines of SQL code Can work within any EHR Can work within any EHR Concurrent analysis Concurrent analysis No need to export data. No need for consent No need to export data. No need for consent No need to use data warehouses No need to use data warehouses No need to require same data on all patients No need to require same data on all patients

28. Medication Benchmarks: Selection of Antidepressants Easy to implement Easy to implement 8 lines of SQL code 8 lines of SQL code Can work within any EHR Can work within any EHR Concurrent analysis Concurrent analysis No need to export data. No need for consent No need to export data. No need for consent Current or warehoused data Current or warehoused data No need to require same data on all patients No need to require same data on all patients

29. Medication Benchmarks: Selection of Antidepressants Easy to implement Easy to implement 8 lines of SQL code 8 lines of SQL code Can work within any EHR Can work within any EHR Concurrent analysis Concurrent analysis No need to export data. No need for consent No need to export data. No need for consent Current or warehoused data Current or warehoused data No need to require same data on all patients No need to require same data on all patients

30. Data Source Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Sequenced Treatment Alternatives to Relieve Depression (STAR*D) 4,041 outpatients with non-psychotic depression 4,041 outpatients with non-psychotic depression 23 psychiatric and 18 primary care sites 23 psychiatric and 18 primary care sites 12-week course of the SSRI citalopram 12-week course of the SSRI citalopram Adjunct or replacement treatment in three subsequent phases Adjunct or replacement treatment in three subsequent phases

31. Technological Fix Technology is available Technology is available Data is available Data is available Analytical procedure is simple Analytical procedure is simple Will there be fewer George’s among us?

32. Transformation at Hand: Suppose the Dog Catches with the Car Process changes Process changes Confusion in responding Confusion in responding Patient first? Patient first? Liability for follow up Liability for follow up Organizational changes Organizational changes Formulary Formulary Must have software Must have software Consent to exclude Consent to exclude Other Other FDA approval FDA approval Publishing data Publishing data

33. Informatics Can Be Anything You Want Be Careful What You Wish For What is 1+1?