The PROTECT project

1. The PROTECT project An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology Progress Status: February 2011

2. PROTECT is receiving funding from the European Community's Seventh Framework Programme (FP7/2007-2013) for the Innovative Medicine Initiative (www.imi.europa.eu).

3. PROTECT Goal • To strengthen the monitoring of benefit-risk of medicines in Europeby developing innovative methods These methods will be tested in real-life situations. to enhance early detection and assessment of adverse drug reactions from different data sources (clinical trials, spontaneous reporting and observational studies) to enable the integration and presentation of data on benefits and risks

4. Data collection from consumers – WP4 Observational studies Electronic health records Spontaneous ADR reports Clinical trials Benefits Risks Validation studies WP6 Signal detection WP3 Signal evaluation WP2 Training and education WP7 Benefit-risk integration and representation – WP5

5. Partners Public Private Regulators: EMA (Co-ordinator) DKMA (DK) AEMPS (ES) MHRA (UK) EFPIA companies: GSK (Deputy Co-ordinator) Sanofi- Aventis Roche Novartis Pfizer Amgen Genzyme Merck Serono Bayer Astra Zeneca Lundbeck NovoNordisk Takeda Academic Institutions: University of Munich FICF (Barcelona) INSERM (Paris) Mario Negri Institute (Milan) Poznan University of Medical Sciences University of Groningen University of Utrecht Imperial College London University of Newcastle Upon Tyne Others: WHO UMC GPRD IAPO CEIFE SMEs: Outcome Europe PGRx

6. WP 1: Project Management and Administration Objectives: To create and maintain the conditions needed to achieve the objectives and deliverables of the PROTECT project. Knowledge management tools and strategies Scientific steer towards the overall project objectives and strategy Quality control and assurance measures Financial monitoring and accountancy Track of work progress in line with the work programme Administrative, organisational and financial support

7. WP 2: Framework for pharmacoepidemiological studies Objectives: To: • develop • test • disseminate methodological standards for the: • design • conduct • analysis of pharmacoepidemiological studies applicable to: • different safety issues • using different data sources

8. Art is made to disturb. Science reassures. Georges Braque Is it always true ?

9. Two studies on the use of statins and the risk of fracture done in GPRD around the same period by two different groups.

10. Why such a difference ? • Different patients (source population, study period, exclusion criteria) • Study design (e.g. matching criteria for age) • Definition of current statin use (last 6 months vs. last 30 days) • Possibly different outcomes (mapping) • Possibly uncontrolled/residual confounding

11. Work Package 2 Work plan • Three Working Groups (WG1-WG3) • Databases • Confounding • Drug Utilisation

12. Work Package 2 – WG1: Databases Work Plan • Conduct of adverse event - drug pair studies in different EU databases • Selection of 5 key adverse event - drug pairs • Development of study protocols for all pairs • Compare results of studies • Identify sources of discrepancies Databases • Danish national registries • Dutch Mondriaan database • British GPRD database • British THIN databases • Spanish BIFAP project • German Bavarian claims database

13. Work Package 2 – WG1: Databases Progress status (1/3) Selection of key adverse events and drugs • Selection criteria: • Adverse events that caused regulatory decisions • Public health impact (seriousness of the event, prevalence of drug exposure, etiologic fraction) • Feasibility • Range of relevant methodological issues

14. Work Package 2 – WG1: Databases Progress status (2/3)  Selection of 5 key adverse events and drugs • Initial list of 55 events and >55 drugs • Finalisation based on literature review and consensus meeting

15. Work Package 2 – WG1: Databases Progress status (3/3) Development of study protocols • Descriptive studies for the Drug AE pairs in all databases • 5 different study designs in selected databases • Cohort design • Nested case control design • Population based case control • 6 Final protocols in Feb 2011 (separate protocols for antidepressants and benzodiazepines versus hip fracture) • Case crossover • Self controlled case series

16. Work Package 2 – WG2: Confounding Work Plan • Objective • To evaluate and improve innovative methods to control confounding • Method • Creation of simulated cohorts • Use of methods to adjust for observed and unobserved confounding e.g. time-dependent exposure, propensity scores, instrumental variables, prior event rate ratio (PERR) adjustment, evaluation of measures of balance in real-life study

17. Work Package 2 – WG2: Confounding Progress status • Finalisation of protocol to conduct simulation studies • Propensity score methods • Instrumental variable methods • Time-dependent confounding • First results on propensity scores (PS)/balance measures • Usefulness of measures for balance for reporting of the amount of balance reached in PS analysis and selecting the final PS model • Recommendation of methods to quantify balance of confounder distributions when applying PS methods: • standardised difference • Kolmogorov-Smirnov distance, or • overlapping coefficient

18. Work Package 2- WG3: Drug Utilisation Work Plan • Use of national drug utilisation data (incl IMS) • Inventory of data sources on drug utilisation data for several European countries • Evaluation and dissemination of methodologies for drug utilisation studies in order to estimate the potential public health impact of adverse drug reactions • Collaboration with EuroDURG agreed

19. Work Package 2- WG3: Drug Utilisation Progress Status • Inventory on Drug Use data “Drug consumption databases in Europe” (last version January 2011) • 11 research working groups across Europe identified • Databases heterogeneous, administrative focus and influenced by the national health system structure • Collecting DU data (in/out hospital) • from public databases (for 6 selected drugs) • from IMS (Antibiotics, Antidepressants and Benzodiazepines. Explored for other drugs)

20. Work Package 3: Signal Detection Objective: To improve early and proactive signal detection from spontaneous reports, electronic health records, and clinical trials.

21. Work Package 3: Signal Detection Scope • Develop new methods for signal detection in Individual Case Safety Reports. • Develop Guidelines for signal detection and strengthening in Electronic Health Records. • Implement and evaluate concept-based Adverse Drug Reaction terminologies as a tool for improved signal detection and strengthening. • Evaluate different methods for signal detection from clinical trials. • Recommendations for good signal detection practices.

22. Work Package 3: Sub-projects • Merits of disproportionality analysis • Structured database of known ADRs • Concordance with risk estimates • Signal detection recommendations • Better use of existing ADR terminologies • Novel tools for grouping ADRs • Other information to enhance signal detection • Signal detection based on SUSARs • Subgroups and risk factors • Signal detection in Electronic Health Records • Drug-drug interaction detection • Duplicate detection

23. Work Package 3 – Structured database of SPC 4.8 • Objective: Making available, in a structured format, already known ADRs to allow for • Triaging out known ADRs • Automaticreduction of masking effects • Approach: • Manual identification • Pooling of existing structured information (?) • Free text extraction! • Progress to date: • All 375 SPCs of CAPs (substances). Addition of non-CAPs under discussion.

24. Work Package 3 – Structured database of SPC 4.8 Better option: Red blood cell abnormal • Proof-of-concept analysis of free text extraction algorithm • Initial match rate increased from 72% to 98%

25. Work Package 3 – Database survey • Scope • EudraVigilance, VigiBase • National data sets: AEMPS, BFARM, DKMA, MHRA • Company data sets: AZ, Bayer, Genzyme, GSK • Focus • # reports, # drugs and # ADR terms • Types of reports (AEs or ADRs, Vaccines, Seriousness, ...) • Additional information (presence of data elements available for stratification and sub-setting, e.g. demographics) • Supporting systems (analytical methods, medical triages) • Current status • Survey deployed and completed by most organisations

26. Work Package 3 - Better use of existing terminologies • Proof of concept • Temozolomide • Not illustrating timeliness – VigiBase as of Feb 2009

27. Work Package 3 – Novel tools to group ADRs • Approach • Automatic generation of groups of MedDRA terms based on semantic information • Based on a mapping of MedDRA to SNOMED CT • Groups MedDRA terms based on semantic distance • Progress • Evaluation study completed • Comparison with standard MedDRA SMQs as gold standard • Next steps: • Refinement of methods • Use in signal detection!

28. Work Package 3 - Signal detection from clinical trials • Overall scope • Inform best practices on which data should be used and which methods are optimal • Explore novel uses of existing clinical data in ongoing and completed clinical trials for safety signal detection • Progress  Draft protocol • Conduct benchmark survey of available methods and processes • Create a library of publications on this topic • Identify compounds and relevant data sets for retrospective analysis. • Conduct analyses and document results. • Create recommendations for best practices

29. Work Package 3 - Signal detection in Electronic Healthcare Records (EHRs) • Overall scope • EHRs versus ICSRs for early signal detection • Confirmatory vs exploratory data analysis • Focus so far has been on the adaptation of an existing analytical platform to THIN • Detailed protocols under development (completion by Aug 2011)

30. Work Package 3 - Other • Subpackage 11: Drug-drug interaction detection  reference set under construction • Subpackage 12: Duplicate detection  completed in VigiBase • Study protocols agreed for • Subpackage 1: Merits of disproportionality analysis • Subpackage 2: Concordance with risk estimates • Subpackage 5: Better use of existing terminologies

31. Work Package 4: Data collection from consumers Objectives: To assess the feasibility, efficiency and usefulness of modern methods of data collection including using web-based data collection and computerised, interactive voice responsive systems (IVRS) by telephone

32. Work Package 4 - Project Definition • Prospective, non interventional study which recruits pregnant women directly without intervention of health care professional • Collect data from them throughout pregnancy using either web based or interactive voice response systems (IVRS): • medication usage, lifestyle and risk factors for congenital malformation • Compare data with that from other sources and explore differences • Assess strengths and weaknesses of data collection and transferability to other populations

33. Work Package 4 - Issues with current methods Using health care professionals to capture data • Expensive and data capture relatively infrequent • Will miss drug exposure before comes to attention of HCP • Patients may not tell truth about “sensitive” issues

34. Work Package 4 - Issues with current methods Using EHR records • non prescription medicines, homeopathic and herbal medicines not captured • ? Women switch to “perceived safer” medicines • Medicines prescribed/dispensed may not be medicines consumed – problem with p.r.n. medicines (i.e. dosage as needed) • EHR may miss lifestyle and “sensitive” information

35. Work package 4 - Study population • 4 countries: • 1400 pregnant women per country • Self identified as pregnant • Volunteers may not be “typical” of pregnant population – can characterise Denmark The Netherlands United-Kingdom Poland

36. Study subject enrolls for the web or phone (IVRS) method of data collection. Web n = 1200 per country Study subject completes the surveys online. IVRS n = 200 per country Study subject completes the surveys via an outbound reminder or by inbound call she initiates. Final outcome survey is completed at the end of pregnancy. Work Package 4: Patient workflow overview Study subject picks up a leaflet in a pharmacy or browses specific web sites to find out about the study in one of 4 countries.

37. Work Package 5: Benefit-Risk Integration and Representation • Objectives: • To assess and test methodologies for the benefit-risk assessment of medicines • To develop tools for the visualisation of benefits and risks of medicinal products • Perspectives of patients, healthcare prescribers, regulatory agencies and drug manufacturers • From pre-approval through lifecycle of products

38. Work Package 5: Workstreams

39. Work Package 5: Work Plan • Review of methodologies used to model effects of medicines, elucidation of patients’ preferences and integrating effects and preferences. Review of methodologies for graphical representation and visualisation techniques. • Selection of case studies (waves 1 and 2) • Data selection/requirements for case studies • Identification/development of software for B/R. • Application of methodology, recommendations, finalisation of tools, protocols for validation studies.

40. Work Package 5: Workstream A - completed • Framework for B-R analysis: achieved through a Charter (SC approved) • Large scope covering principally post-approval setting, individual and population-based decision making, various perspectives (patients, prescriber, regulators, industry) • Address possible interdependencies with other PROTECT WPs • Review of B-R methodologies and graphical representation tools • Selection of candidate methodologies based on specified criteria • Process for selection of case studies, according to selection criteria • Implementation of case studies using relevant methodologies and including preferences of various stakeholders • Test available representation technologies applied to above mentionned case studies and B-R methodologies • Publication and presentation of case studies in various settings

41. Work Package 5: Overview • Wave 1: has 4 case studies: Raptiva, Tysabri, Ketek, and Acomplia. • Drugs which have data readily available from EPARs. • Not revisiting EMA decisions, but use to demonstrate and test methodologies. WS C Case studies • PrOACT-URL framework for performing benefit-risk analysis. • Oversee working parties for extracting objective measures of magnitude / incidence of benefits and risks. • Review of existing methods not inventing new methods. • Emphasis on graphical representation. • Methods estimating(1) magnitude / incidence of events and (2) value elicitation of benefits and risks, from a patient and regulator perspective and how combine them into a single measure. WS DFramework / Data WS FApplication WS B Methods WS ESoftware / graphics • Apply the methodology to the case studies using the data • May also elicit the subjective value data for the benefits and risks. • Not developing software, but explore suitable existing software (possibly with adaptation).

42. Collaborators Other initiatives Literature search Literature search Other initiatives External meetings Methodological review Visual representations review Elicitation of suitable graphics Elicitation of suitable methods Integration of methodologies and visual representations Develop visual representations add-ons and software Application to case studies Present case-studies results emphasising on communication of, and use of graphical representations for, understanding benefits and risks Work Package 5: Workstream B Protocol for evidence synthesis endorsed by all members 34 items to review have been identified through literature search List of evaluation criteria has been generated Focus on their potential for graphical representation

43. Work Package 5: Workstream C • Progress • Criteria for wave 1 case studies and drugs for case studies (Acomplia ®, Raptiva ®, Tysabri ®, Ketek ®) • Draft criteria for wave 2 and library of possible candidates (more challenging) • Uncertainty about what the main benefits and risks are. • Uncertainty about the population who has the disease. • Different time for Benefit and for Risk (long term risks). • Individual benefit-risk, or subgroups of benefit risk. • New drugs vs. long marketed drugs.

44. Work Package 5: Workstream C • Next steps • Discussion with other workstreams for appropriate data identification and extraction (WS D), applicability of case studies for WS F to run. • Identify potential presentations and publications.

45. Work Package 5: Workstream D • Scope • Data Collection dependent from Framework used: • Using PrOACT-URL (generic framework for decision making), identification of data sources to be used depend on detailed description of each of the steps of the framework (see back up slide) • Lead to a draft “Guidelines for preparing a Case Study Report” • Based on Acomplia® experience, most data/information necessary for B-R assessement at time of market authorisation and of market withdrawal were included into EPAR (Regulators perspective) • In addition to EPAR, additional data sources for other drugs or for other perspectives will require • Additional data collection from existing data sets (PSURs, formal B-R reviews) • Creation of new data (e.g. questionnaires for patient preferences elicitation)

46. Work Package 5: Workstream D • Next steps • Prepare identification of data sources to be used/created for other Wave 1 case studies (Raptiva ®, Tysabri®, Ketec®) • Actual supply of data

47. Work Package 5: Workstream F • Scope • Workstream (WS) F is: • applying the methodology from WS B • to the case studies selected from WS C • using the data collected in WS D • with the software and graphical methods selected by WS E • Done by four interdisciplinary teams in four locations • More than one method will be applied to each case study, and several methods explored overall • The aim of the first wave is to test the application of the methods and framework on relatively simple case studies • This then feeds back into the second wave to refine the tools

48. Work Package 6: Validation • Objectives: • To validate and test the transferability and feasibility of methods developed in PROTECT to other data sources and population groups • To determine the added value of using other data sources as a supplement or alternative to those generally used for drug safety studies, in order to investigate specific aspects or issues.  Started in September 2010

49. Work Package 6 - Inventory of data sources Creating a comprehensive list of data sources (ongoing) Review of European databases (electronic healthcare records, cohorts, registries) ENCePP EFPIA Outcomes of other Work Packages (2-5) will be evaluated in light of the inventory of data sources (e.g. type of data, covariate information, mode of collection, type of prescription data, etc) 49

50. Work Package 7: Training & communication Objective: To identify training opportunities and support training programmes to disseminate the results achieved in PROTECT.