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The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences,

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Presentation on theme: "The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences,"— Presentation transcript:

1 The PROTECT project Olaf Klungel, PharmD, PhD Division of Pharmacoepidemiology & Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

2 ACKNOWLEDGEMENTS The research leading to these results was conducted as part of the PROTECT consortium (Pharmacoepidemiological Research on Outcomes of Therapeutics by a European ConsorTium, which is a public-private partnership coordinated by the European Medicines Agency. The PROTECT project has received support from the Innovative Medicine Initiative Joint Undertaking ( under Grant Agreement n° , resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/ ) and EFPIA companies in kind contribution. The views expressed are those of the authors only. PROTECT work in this presentation is work by WP2 colleagues.

3 Contents Background PROTECT - Work package 2 (WP2) WP2 working groups (WG) –Approach –Preliminary results (WG1) –Results (WG2 and WG3) –Next steps Conclusion 3

4 PROTECT Goal 4 These methods will be tested in real-life situations. To strengthen the monitoring of benefit-risk of medicines in Europe by developing innovative methods 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

5 5 Clinical trials Observational studies Electronic health records Spontaneous ADR reports Risks Benefit-risk integration and representation – WP5 Signal detection WP3 Benefits Validation studies WP6 Training and education WP7 Signal evaluation WP2 Data collection from consumers – WP4

6 Partners 6 PublicPrivate Regulators: EMA (Co-ordinator) DKMA (DK) AEMPS (ES) MHRA (UK) 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 EFPIA companies: GSK (Deputy Co- ordinator) Sanofi- Aventis Roche Novartis Pfizer Amgen Genzyme Merck Serono Bayer Astra Zeneca Lundbeck NovoNordisk Takeda SMEs: Outcome Europe PGRx Others: WHO UMC GPRD IAPO CEIFE

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

8 8 WP2 participants and their role WP2 has 3 Working groups (WG) WG1 Databases WG2 Confounding WG3 Drug utilization Number of participants n=46 33 public, 13 private n=14 10 public, 4 private n=9 5 public, 4 private Public partners EMA, LMU-Muenchen, AEMPS, CEIFE, GPRD, DKMA and UU UUFIFC, LMU Private partners Amgen, AZ, Genzyme, GSK, La-Ser, Merck, Novartis, Roche and Pfizer Amgen, Novartis, Roche and Pfizer Amgen, Novartis and Roche WG Coordinators Raymond Schlienger 1 (Novartis) Mark de Groot 2 (UU) Nicolle Gatto (Pfizer) Rolf Groenwold (UU) Joan Fortuny 3 (Novartis) Luisa Ibanez (FIFC) WP2 coleadersOlaf Klungel (UU) - Robert Reynolds (Pfizer) WP2 coleaders alternates Tjeerd van Staa (GPRD) - Jamie Robinson (Roche) WP2 Project Manager Ines Teixidor (UU) 1 from Oct 2010 replacing John Weil (GSK) 2 from 1 Feb replacing Frank de Vries (UU) 3 from 15 March 2012 replacing Hans Petri (Roche)

9 Work Package 2 – WG1: Databases 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 9 British THIN databases (THIN) Spanish BIFAP project (BIFAP) German Bavarian claims database (BAVARIA) Danish National registries (DKMA) Dutch Mondrian databases (MONDRIAAN) British GPRD databases (GPRD)

10 Work Package 2 – WG1: Databases 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 10

11 Work Package 2 – WG1: Databases Antidepressants (incl. Benzodiazepines) - Hip Fracture Antibiotics - Acute liver injury Beta2 Agonists - Myocardial infarction Antiepileptics - Suicide Calcium Channel Blockers - Cancer 11 Selection of 5 key adverse events and drugs –Initial list of 55 events and >55 drugs –Finalisation based on literature review and consensus meeting

12 Population nrs 6 EU databases 12 DatabaseCountrySourceCum Population nrActive population nr (2008) GPRDUKGP11 M3.6 M MondrianNLMultisource1.4 M (GP)1 M (GP), 13.5 (Pharmacy), 1.2 M (Claims) BifapESGP3.2 M1.6 M Danish registriesDKMultisource5.2 M (All DBs) THINUKGP7.8 M3.1 M Bavarian ClaimsDEClaims10.5 M9.5 M

13 Characteristics of 6 EU DBs 13 DatabaseCoding diagnoses Coding drugs Start yearNation wide GPRDReadBNF20017% UK MondrianICPC ICD ATC199190% NL (pharmacy) 0.6% NL (GP) BifapICPCATC2001 7% ES Danish registriesICDATC1994 (med prod) 1977 (pat register) 100% DK THINREADBNF % UK Bavarian ClaimsICDATC % (Bavaria)

14 Approach Common protocol for each drug-ae pair –Descriptive studies for drug-ae pairs in all databases –5 different study designs in selected databases –Extensive sensitivity analyses on main methodological issues Common standards, templates, procedures –Detailed data specification including definitions of exposures, outcomes, and confounders for each database. –Blinding of results of individual DB analyses Submission of protocols to ENCePP registry of studies 14

15 WG1 Preliminary results: Antibiotic use by age in 6 EU databases 15 DRAFT PRELIMINARY RESULTS

16 WG1 Preliminary results: Antidepressant use by year in 6 EU databases 16 DRAFT PRELIMINARY RESULTS

17 17 WG1 Preliminary results: BZD use by age in 6 EU databases Mondriaan-ZGA: results correspond to 2008 DRAFT PRELIMINARY RESULTS

18 18 WG1 Preliminary results: Incidence of hip/femur fracture by age in 2009 in 4 EU databases DRAFT PRELIMINARY RESULTS

19 19 Work Plan Objective –To evaluate and improve innovative methods to control confounding Method –Simulation studies to test methods –Application of methods to real-life data sets Work Package 2 – WG2: Confounding

20 20 Work Package 2 – WG2: Confounding Progress status Guideline for conduct of simulation studies –Propensity score methods –Instrumental variable methods First results –Usefulness of measures for balance for reporting of the amount of balance reached in PS analysis and selecting the final PS model –Comparison of methods to control for time-dependent confounding –Evaluation of IV in case-control and cohort studies

21 Simulation study propensity scores 21

22 Application of propensity scores 22

23 23 Work Package 2 – WG2: Confounding Next steps Analysis of instrumental variables (IV) in Drug AE pairs –Evaluate the potential for IV analysis on the selected Drug AE pairs in the databases that are available within PROTECT –Feb 2012: Identify potential IV for each of the 5 Drug AE pair and in each WG1 database –Aug 2013: Results of IV studies in databases (if an appropriate IV can be identified & measured)

24 24 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

25 25 Work Package 2 – WG3: Drug Utilisation Progress Status Inventory on Drug Use data Drug consumption databases in Europe (last version August 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)

26 26 Work Package 2 – WG3: Drug Utilisation Next steps Literature Search on Randomized Controlled Trials (RCT) –Search for existing meta-analyses or syntheses available in the literature (avoid duplication of work already done). –Dec 2011: Development of specific protocols for literature search Jan 2012: Start of literature search starts. –Dec 2012: Results of the literature search on RCTs expected. Public health impact of selected Drug AE pairs –Evaluate validity of drug use data –Estimate the exposed population to drugs and calculate population attributable risk

27 27

28 28 Reduce variation due to methodological choice of individual researchers Explain variation due to characteristics of country/database Disseminate methodological guidance for PE studies More consistency in drug-ae studies to improve B/R assessment of medicines Finally

29 29 Members of PROTECT WP2 J. Slattery, Y. Alvarez, G. Candore, J. Durand (European Medicines Agency); J. Hasford, M. Rottenkolber (Ludwig-Maximilians-Universität-München); S. Schmiedl (Witten University); F. de Abajo Iglesias, A. Afonso, M. Gil, C. Huerta Alvarez, B. Oliva, G. Requena (Agencia Espanola de Medicamentos y Productos Sanitarios); R. Brauer, G. Downey, M. Feudjo-Tepie, M. Schoonen (Amgen NV); S. Johansson (AstraZeneca); J. Robinson, M. Schuerch, I. Tatt (Roche); L.A. Garcia, A. Ruigomez (Fundación Centro Español de Investigación Farmacoepidemiológica); J. Campbell, A. Gallagher, E. Ng, T. Van Staa (General Practice Research Database); O. Demol (Genzyme); J. Logie, J. Pimenta, K. Davis (GlaxoSmithKline Research and Development LTD); L. Bensouda-Grimaldi (L.A. Sante Epidemiologie Evaluation Recherche); U. Hesse, P. F. Rønn (Lægemiddelstyrelsen (Danish Medicines Agency) ); M. Miret (Merck KGaA ); P. Primatesta, R. Schlienger, E. Rivero, J. Fortuny (Novartis); A. Bate, N. Gatto, R. Reynolds (Pfizer); E. Ballarin, L. Ibañez, J.R. Laporte, M. Sabaté, P. Ferrer (Fundació Institut Català de Farmacologia); V. Abbing-Karahagopian, D. de Bakker, M.L. de Bruin, F. de Vries, A.C.G. Egberts, B. Leufkens, P. Souverein, L. van Dijk, E. Voogd, M. De Groot, H. Gardarsdottir, F. Rutten, R. Van den Ham, O. Klungel, S. Belitser, A. De Boer, R. Groenwold, A. Hoes, W. Pestman, K. Roes, S. Ali, J. Uddin (Universiteit Utrecht).

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