David Neasham Practical Use Pharmacoepi Drug Dev


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DIA Clinical Forum conference speaker: Practical use of Pharmacoepidemiology in Clinical Drug Development (Ljubljana Oct 20-23, 2008).

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  • David Neasham Practical Use Pharmacoepi Drug Dev

    1. 1. Practical use of Pharmacoepidemiology in clinical drug development Presenter: Dr David Neasham Company logo here
    2. 2. Contents <ul><li>Background, contributing areas & reasons to perform pharmacoepidemiology studies </li></ul><ul><li>Study design </li></ul><ul><li>Database studies </li></ul><ul><li>Two practical examples: </li></ul><ul><ul><li>YASMIN (ethinylestradiol with drospirenone) </li></ul></ul><ul><ul><li>CRESTOR (rosuvastatin) </li></ul></ul><ul><li>Summary </li></ul><ul><li>Discussion / Q & A </li></ul>
    3. 3. Background <ul><li>Pharmacoepidemiology </li></ul><ul><ul><li>Application of epidemiological techniques to the content area of clinical pharmacology </li></ul></ul><ul><ul><ul><li>Population level </li></ul></ul></ul><ul><ul><ul><li>Study of adverse drug effects </li></ul></ul></ul><ul><ul><ul><li>Many areas of contribution </li></ul></ul></ul>
    4. 4. Contributions <ul><li>Better quantification of incidence of known adverse and beneficial effects </li></ul><ul><ul><li>Higher precision </li></ul></ul><ul><ul><li>In patients excluded in pre-marketing studies – e.g., children, elderly, pregnant women </li></ul></ul><ul><ul><li>Interaction by other drugs or illnesses </li></ul></ul><ul><ul><li>Relative to other drugs used for same indication </li></ul></ul>
    5. 5. Reasons <ul><li>Regulatory </li></ul><ul><ul><li>e.g., obtain earlier approval for marketing </li></ul></ul><ul><li>Clinical </li></ul><ul><ul><li>e.g., hypothesis testing or generating </li></ul></ul><ul><li>Marketing </li></ul><ul><ul><li>e.g., assist in repositioning of drug </li></ul></ul><ul><li>Legal </li></ul><ul><ul><li>e.g. In anticipation of product liability litigation </li></ul></ul>
    6. 6. Study design
    7. 7. © Imperial College London Slide
    8. 8. Study design <ul><li>Case-cohort design </li></ul><ul><ul><li>Selecting all cases in cohort – i.e. all subjects with adverse event </li></ul></ul><ul><ul><li>Randomly selecting a sample of pre-determined size of subjects from the cohort </li></ul></ul><ul><ul><li>Reduced version of cohort, with all cases added </li></ul></ul>
    9. 9. Study design <ul><li>Large Simple trial (LST) </li></ul><ul><ul><li>Large randomized trials made simple by reducing data collection to minimum needed to test specific hypotheses </li></ul></ul><ul><ul><li>Randomization of treatment assignment </li></ul></ul><ul><ul><li>Controls of confounding by known or unknown risk factors </li></ul></ul><ul><ul><li>Sufficient statistical power  small risks of common events + large risks of rare events </li></ul></ul>
    10. 10. Study design <ul><li>Efficiency of LSTs could be enhanced using health delivery systems databases </li></ul><ul><li>Relevant outcomes (e.g., hospitalizations for gastrointestinal bleeding) could be captured electronically which would eliminate need to contact patients for follow-up </li></ul><ul><li>Still necessary to identify eligible subjects, obtain consent and randomize treatment </li></ul><ul><li>Could be a very effective hybrid method </li></ul>
    11. 11. A typical scenario: identifying risks INCIDENCE OF COMMONLY OCCURRING EVENT FROM CLINICAL TRIALS Background Epidemiology Risk management strategy  INCIDENCE OF EVENT IN GENERAL POPULATION IDENTIFICATION OF RISK FACTORS POTENTIAL SIGNALS OF RARE EVENTS Spontaneous Reports Observational Studies Other Activities 1/1,000 1/500 1/100 1/10,000 1/5,000 1/1,000 1/100,000 1/50,000 1/10,000 HYPOTHESIS TESTING 1/1,000,000 1/500,000 1/100,000, Clinical trial Data Insufficiently powered Evidence base Self-report bias Best study design….
    12. 12. Safety challenges in pre-approval phase <ul><li>Challenges of safety signal identification during pre-approval phase: </li></ul><ul><ul><li>pre-approval studies cannot usually be statistically powered to identify readily low frequency safety events of concern </li></ul></ul><ul><ul><li>samples often narrowly defined – therefore may not be truly representative of final treatment population </li></ul></ul><ul><ul><li>short time frames: mid to long-term effects cannot be thoroughly evaluated </li></ul></ul>
    13. 13. Post-marketing pharmacovigilance <ul><li>Limitations of post-marketing spontaneous reporting systems: </li></ul><ul><ul><li>patterns of spontaneous reporting vary by country, increase during early post-launch period and are affected by publicity -> s pontaneous reporting rates biased </li></ul></ul><ul><ul><li>limited population level denominator information </li></ul></ul><ul><ul><li>for common events (e.g., MI) difficult to separate actual signals from background noise </li></ul></ul>
    14. 14. Product life-cycle and safety studies Approval Product life-cycle FIM Ph I Ph II Ph III Ph IV <ul><li>Toxicology (e.g. genotoxicity assays) </li></ul><ul><li>In silico analysis/ structural alerts </li></ul><ul><li>Margin of safety & no observed adverse effect level defined </li></ul><ul><li>Ph I & II: dose ranging, efficacy & toxicity </li></ul><ul><li>Phase III: demonstration of efficacy and safety signal monitoring </li></ul><ul><li>Ph IV: spontaneous reporting systems </li></ul>Postmarketing pharmacovigilance Clinical Exposure in humans (Potential Denominator) Preclinical Sufficiently powered Easy study replication Large database studies No self-reporting bias
    15. 15. Example 1 <ul><li>The YASMIN (ethinylestradiol with drospirenone) study </li></ul>
    16. 16. Case Study - Yasmin and the Safety of DRSP <ul><li>Background </li></ul><ul><ul><li>Yasmin is an OC that contains drospirenone (DRSP) </li></ul></ul><ul><ul><li>DRSP has antimineralocorticoid activity and can raise serum potassium </li></ul></ul><ul><li>Phase IV commitment </li></ul><ul><ul><li>To obtain safety data related to: </li></ul></ul><ul><ul><ul><li>Complications related to hyperkalemia (elevated serum potassium) </li></ul></ul></ul><ul><ul><ul><li>Physician prescribing and patient monitoring </li></ul></ul></ul><ul><ul><ul><li>Breakthrough pregnancy and birth outcomes </li></ul></ul></ul><ul><ul><li>In 25,000 users of Yasmin and 50,000 users of other OCs </li></ul></ul><ul><li>Wider business implications </li></ul><ul><ul><li>Sponsor planned to introduce DRSP into menopausal therapy </li></ul></ul><ul><ul><li>Needed strong basis for later safety claims </li></ul></ul>
    17. 17. Cohort Formation INGENIX Research Database Women (10-59 yrs) n = 959,482 Propensity score matching of 12 initiator cohorts (n = 22,429) New dispensing of Yasmin (n = 31,149) New dispensing of other OCs (n = 360,505) ≥ 6 months continuous enrollment (n = 22,887) ≥ 6 months continuous enrollment (n = 227,596) Propensity score matching of 12 initiator cohorts (n = 44,858) 1:2 Ratio
    18. 18. Data Collection <ul><li>• Create matched cohorts of Yasmin and </li></ul><ul><li>other OC users </li></ul><ul><li>Collect comorbidities, demographics, </li></ul><ul><li>healthcare utilization, exposure to oral </li></ul><ul><li>contraceptives </li></ul><ul><li>• Identify women with hepatic, renal or </li></ul><ul><li>adrenal insufficiency </li></ul><ul><li>• Identify potassium-sparing meds </li></ul>New OC or New type of OC OC Rx 6 Months Before Dispensing Prospective Data Collection <ul><li>Identify clinical outcomes based on </li></ul><ul><li>claims data (prescription, diagnoses, </li></ul><ul><li>procedures and service) </li></ul><ul><li>Hospitalizations for new conditions, </li></ul><ul><li>clinical events potentially related to </li></ul><ul><li>hyperkalemia, electrolyte abnormality, </li></ul><ul><li>inappropriate prescribing, potassium </li></ul><ul><li>monitoring, pregnancy/fetal malformations </li></ul>
    19. 19. Yasmin Launch Q3 Time Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 2001 2002 2003 2004 Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow-Up Follow-Up Yasmin Control P Follow Follow Yasmin Control P 2005 Q1 Q2 Q3 Q4 Claims-Based Outcomes Chart-Based Outcomes Apr. Report Oct. Report Apr. Report Oct. Report Apr. Report Oct. Report Apr. Report Final Report
    20. 20. Blinded Chart Reviews to Confirm Outcomes Claims Based Abstraction Medical Chart Abstraction Screen Claims Data Medical Review
    21. 21. Rate Ratios Some outcomes may be continuations of pre-existing conditions * No rate ratio calculated as no case in Yasmin Cohort ** Composite hyperkalemia outcome comprised of chart-confirmed cases of arrhythmia, syncope, electrolyte disturbance, hyperkalemia, and myocardial infarction. Syncope Arrhythmia Hyperkalemia Other Electrolyte Disturbance Dialysis* Myocardial Infarction* Hospitalization with Hyper/Hypokalemia* Death Composite Hyperkalemia** 0 0 0 0 Incidence Rate Ratio –Yasmin versus Other OC (95% CI) 5.0 1.0 2.0 4.0 3.0 0.5 0.25 0.33 0.2 0.1
    22. 22. <ul><li>Does Yasmin lead to more VTE than other OCs? </li></ul><ul><ul><li>NO. We added a new outcome which we could evaluate both retrospectively and prospectively for the full cohort. </li></ul></ul><ul><li>Why do physicians prescribe to women with apparent contraindications of renal, hepatic, or adrenal disease? </li></ul><ul><ul><li>MAY IGNORE NOMINAL CONTRAINDICATION FOR MILD DISEASE. We directly interviewed physicians with apparently contraindicated prescribing patterns. </li></ul></ul><ul><li>Why do physicians not perform potassium monitoring as recommended in the label? </li></ul><ul><ul><li>DISAGREE WITH LABEL. We surveyed physicians with patients who by label should have been monitored, but were not. </li></ul></ul>Flexible Data Collection Facilitates Risk Management
    23. 23. Example 2 <ul><li>The CRESTOR (rosuvastatin) studies </li></ul>
    24. 24. Brief background <ul><li>Rosuvastatin </li></ul><ul><li>Hepato-selective and relatively hydrophilic hydroxy-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor (statin) </li></ul><ul><li>Approved by FDA on 12 August, 2003 </li></ul><ul><li>Management of dyslipidemia </li></ul>
    25. 25. Potential safety issues <ul><li>Added concerns from withdrawal of cerivastatin in 2001 due to excess cases of fatal rhabdomyolysis </li></ul><ul><li>Comorbidities and concomitant medications may increase risk of myotoxicity, depending on properties of given statin </li></ul>
    26. 26. Evolution of Lipid Management ATP Guidelines* ATP I (1988) ATP II (1993) ATP III (2001) Diet; low-dose, non-statin monotherapy High-dose statin, combination therapy Low- to moderate-dose statin monotherapy Increasing aggressiveness of cholesterol-lowering therapy * The National Cholesterol Education Program Adult Treatment Panel (ATP)
    27. 27. The CRESTOR study program <ul><li>An international collaborative pharmacoepidemiology </li></ul><ul><li>safety program involving many groups… </li></ul><ul><li>AstraZeneca R&D </li></ul><ul><li>Centro Espa ñol de Investigación Farmacoepidemiológica (CEIFE), Spain </li></ul><ul><li>PHARMO Institute, Netherlands </li></ul><ul><li>i3 Drug Safety, US </li></ul><ul><li>Drug Safety Research Unit (DSRU), UK </li></ul>
    28. 28. Pharmacoepidemiology program design <ul><li>Program consisted of nine studies grouped into three components: </li></ul><ul><ul><li>Patient characteristics studies (x 4 databases) </li></ul></ul><ul><ul><li>Safety evaluation studies (x 4 databases) </li></ul></ul><ul><ul><li>Prescription-event monitoring study (DSRU) </li></ul></ul><ul><li>All studies performed according to GPP guidelines and reviewed and approved by ethics committees </li></ul>
    29. 29. Pharmacoepidemiology program overview <ul><li>Table: Study parameters </li></ul>
    30. 30. <ul><li>Numbers and incidence rates of study outcomes </li></ul><ul><li>Results from McAfee et al. (2006) (Ingenix) </li></ul>Safety evaluation studies
    31. 31. Pooled person-time and outcomes
    32. 32. Summary <ul><li>Contributing areas and reasons to perform pharmacoepidemiology studies </li></ul><ul><li>Study design </li></ul><ul><li>Database studies </li></ul><ul><li>Two practical examples: </li></ul><ul><ul><li>YASMIN (ethinylestradiol with drospirenone) </li></ul></ul><ul><ul><li>CRESTOR (rosuvastatin) </li></ul></ul>
    33. 33. Dr David Neasham [email_address] +44 (0)1628 408442 Questions & answers Company logo here Practical use of Pharmacoepidemiology in clinical drug development