Moving from US FDA focus to Global focus – Importance of Standards

1. Moving from US FDA focus to Global focus – Importance of Standards Margaret Minkwitz Sept 16, 2010

2. Definitions of terms used • Health authorities – agencies responsible for review and approval of new medicines (US Food & Drug Administration (FDA) • Common Technical Document – Internationally agreed structure and content details for a submission to the health authorities • Standards: agreed format and data structure details • Includes meaning of the variables • Details in agreed structure • Globally agreed and maintained – updated and reviewed • Version controlled

3. Do we have a common understanding of the issues? Are we talking the same language?

4. Health Authorities: reasons to standardize data collection and reporting • Ability to evaluate data across products / companies • Evaluation of common effects across treatments (class effects) • Ability to use common tools to verify the reported results • Primarily the FDA • Other health authorities starting to follow suit • Ability to compare across data presented on public web sites – common terms and reporting structure • Ability to standardize the product labels so that doctors can compare the properties of treatments when deciding which treatment to prescribe to a patient

5. Additional reasons for companies to embrace standards • Co-development – 2 companies sharing the development costs and risks (example: AstraZeneca and BMS – ONGLYZA® for diabetes, TV ad notes both companies) • Outsource partnering with a Contract Research Organization (CRO) for study conduct and reporting • CRO partner doing studies for Pharmaceutical Company • From protocol to report (full service) • Strategic (portion of the study outsourced – analysis programs) • In-licensing product from development at another company • Work with some studies in original company sources • Need to integrate that data with new studies done

6. International Conference on Harmonization • Health Authorities agreed to accept the Common Technical Document (CTD) for submissions for market authorization • European Medicines Agency • US Food and Drug Administration • Japanese Health Authority • Canadian Health Authority • Industry guidance available for design, analysis, and reporting clinical studies • FDA has specific guidance documents • ICH guidance documents • Other health Authorities have guidance documents

7. In preparing for Product Market Authorization (Submission of CTD) • Need to ensure that all relevant guidance documents are reviewed • Determine the studies needed to provide data required for agreed key markets (1st countries to receive package, CTD) • Plan study designs with details around • Error control • Approaches to handling missing data • Approaches to handling multiple comparisons • Appropriate analysis models given the primary variable for study • Location of studies (multi country study – evaluate issues) • Statistical power and sample size • Plan for data collection and reporting (standards)

8. Tools to standardize data collection and reporting • MedDRA – Medical Dictionary for Regulatory Activities • Adverse event reporting • Medical terminology reporting (Medical history) • CDISC – Clinical Data Interchange Standards Consortium • SDTM – Standard Data Tabulation Model • ADaM – Analysis Data Model • eCTD – Electronic Common Technical Document • Clinical Trials web site reporting requirements (FDAAA) • Web sites • Reporting clinical studies being run • Reporting data from completed clinical studies (within 1 year)

9. MedDRA structure Adverse event reported by patient • Reported Rapid heart rate Hierarchical structure (text and code) – coded to common terminology • System Organ Class Cardiac • High level term Rhythm abnormality • Preferred term Tachycardia If instead of rapid heart rate, a heart rate value was reported • Reported/Preferred term Heart rate120 beats/minute • System Organ Class Investigations • High level term Vital sign

10. Features of SDTM • Domain – aggregation of specific type of information • DE - Demography – age, sex, race, ethnicity, country, etc. • VS - Vital signs – pulse, diastolic blood pressure, systolic blood pressure, respiration rate, temperature, etc. • Variable – information includes • VS test name DIABP • VS test description Diastolic Blood Pressure • VS test units mmHg • VS test result 74 • Variable extensions: position code list supine, sitting, standing, not specified method code list manual, automatic, etc.

11. Features of ADaM Similar to SDTM but the data are statistical analysis an parameters • Analysis method Analysis of Variance • Comparison A vs. B estimate (trt diff) • Statistical test t-test • Test value 5.66 • Prob > |t| <0.0001 • Parameter name mean • Parameter estimate 5.61 • Parameter variability name Standard Error • Parameter variability estimate 0.99

12. eCTD Standards • Common structure – Table of Content • Clinical Section includes • Section 2: Clinical Overview; Clinical Summary of Pharmacology. Efficacy, Safety, Benefit/Risk • Section 5: Study reports for key studies; detailed supporting tables (Integrated summary of safety and efficacy) • Regulatory Section: • Section 1: Specifics around the particular health authority submission • Information on communications and interactions during the program • Details specific to local requirements • Delivered as an electronic CTD – electron transfer

13. Web site expectations of links • Study design • Planned analysis • Primary variable • Secondary variable • Adverse Events • Serious events • Study results • Descriptive statistics • Estimate and dispersion • Estimate and dispersion • Counts • number reporting event • Number at risk (exposed) Presentation of the facts, no discussion or conclusions

14. Expectations for statisticians • Ensure link between question (hypothesis), data collected and analysis methods and reporting (using standards) • Plan for reporting at the study design stage • Have analysis plan early • Plan for handling issues (missing data, multiple testing, variance /covariance structure) • Develop statistical models and programs • Validate that statistical programs • When data available • Check model assumptions (distribution, dispersion, model fit) • Provide data visualization tools to help with interpretation • Provide statistical interpretation of the results

15. Statistical Contribution to CTD • Plan for integrated analysis (what should be combined, how, why) • Prepare subset analysis and interpretation • May need separate analysis of results in population relevant to country where submitted (example – Chinese patients) • Assist in quantifying Benefit/Risk • Review documents and ensure that statements of statistical nature are phrased correctly and any interpretation or conclusion can be supported with the data • Prepare for challenges to the data from the health authorities (what might they ask, why) • Identify any bridging studies which might be needed (Japanese PK study)

16. Controversial Design or Analysis • Plan to discuss with Health Authorities • Need to supply • Written question • Documentation if appropriate (publication) • Include justification for selection among options available • May consult with Academic Statistical Expert • Method of discussion • US FDA – can request a meeting to discuss (Face to face or teleconference) • Europe – request consultation – often written request & response

17. Some areas of interest • Adaptive study design • Not an issue for early studies (exploring dose response) • Needs agreement if in the confirmatory development phase • Dropping treatments • Early termination (efficacy related) • Application of new methods • May need to be used as sensitivity analysis if not routine approach • Multiple imputation methods for missing data • New multiple testing methods • Need to be able to define/support the level of control of error • Data exploitation • Looking for new insights given a large data set (hypothesis generation)