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

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

The PROTECT project

Progress Status: February 2011

An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

Page 2: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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PROTECT is receiving funding from the European Community's Seventh

Framework Programme (FP7/2007-2013) for the Innovative Medicine Initiative (

www.imi.europa.eu).

Page 3: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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PROTECT Goal

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

Page 4: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Clinical trials Observational studies

Electronic health records

Spontaneous ADR reports

Risks

Benefit-risk integration and representation – WP5

Signal detectionWP3

Benefits

Validation studies

WP6

Training and education

WP7

Signal evaluationWP2

Data collection from consumers – WP4

Page 5: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Partners

Public PrivateRegulators:

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 Upon Tyne

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

Page 6: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Objectives:

To create and maintain the conditions needed to achieve the objectives and deliverables of the

PROTECT project.

WP 1: Project Management and Administration

Financial monitoring and

accountancy

Track of work progress in line with the work programme

Knowledge management

tools and strategies

Administrative, organisational and financial

support

Quality control and assurance measures

Scientific steer towards the

overall project objectives and

strategy

Page 7: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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WP 2: Framework for pharmacoepidemiological studies

To:• develop

• test

• disseminate

of pharmacoepidemiological studies applicable to:

• different safety issues

• using different data sources

methodological standards for the:• design

• conduct

• analysis

Objectives:

Page 8: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Art is made to disturb. Science reassures. Georges Braque

Is it always true ?

Page 9: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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

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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

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Work Package 2

Work plan• Three Working Groups (WG1-WG3)

– Databases

– Confounding

– Drug Utilisation

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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

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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

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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

Antidepressants (incl. Benzodiazepines) - Hip Fracture

Antibiotics - Acute liver injury

Beta2 Agonists - Myocardial infarction

Antiepileptics - Suicide

Calcium Channel Blockers - Cancer

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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

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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

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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

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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

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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)

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Work Package 3: Signal Detection

Objective:

To improve early and proactive signal detection from spontaneous reports, electronic health records, and

clinical trials.

Page 21: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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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.

Page 22: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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Work Package 3: Sub-projects

1. Merits of disproportionality analysis

2. Structured database of known ADRs

3. Concordance with risk estimates

4. Signal detection recommendations

5. Better use of existing ADR terminologies

6. Novel tools for grouping ADRs

7. Other information to enhance signal detection

8. Signal detection based on SUSARs

9. Subgroups and risk factors

10. Signal detection in Electronic Health Records

11. Drug-drug interaction detection

12. Duplicate detection

Page 23: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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• Objective: Making available, in a structured format, already known ADRs to allow for

– Triaging out known ADRs

– Automatic reduction 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.

Work Package 3 – Structured database of SPC 4.8

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• Proof-of-concept analysis of free text extraction algorithm

– Initial match rate increased from 72% to 98%

Drug SPC Term Verbatim match Fuzzy matching algorithm

Aclasta FLU-LIKE SYMPTOMS Flu symptoms

Advagraf OTHER ELECTROLYTE ABNORMALITIES - Electrolyte abnormality

Advagraf PAIN AND DISCOMFORT - Pain and discomfort NEC

Advagraf PRIMARY GRAFT DYSFUNCTION - Primary graft dysfunction*

Advagraf PRURITUS PRURITUS Pruritus*

Advagraf PSYCHOTIC DISORDER PSYCHOTIC DISORDER Psychotic disorder*

Advagraf PULSE INVESTIGATIONS ABNORMAL - Investigation abnormal

Advagraf RASH RASH Rash*

Advagraf RED BLOOD CELL ANALYSES ABNORMAL - Red blood cell analyses*

Advagraf RENAL FAILURE RENAL FAILURE Renal failure*

Advagraf RENAL FAILURE ACUTE RENAL FAILURE ACUTE Acute renal failure, Renal failure acute*

Advagraf RENAL IMPAIRMENT RENAL IMPAIRMENT Renal impairment*

Advagraf RENAL TUBULAR NECROSIS RENAL TUBULAR NECROSIS Renal tubular necrosis*

Advagraf RESPIRATORY FAILURES - Respiratory failure, Failure respiratory

Advagraf RESPIRATORY TRACT DISORDERS - Respiratory tract disorders NEC

Advagraf SEIZURES - Seizure, Seizures*

Advagraf SHOCK SHOCK Shock*

Better option:Red blood cell

abnormal

Work Package 3 – Structured database of SPC 4.8

Page 25: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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• 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

Work Package 3 – Database survey

Page 26: The PROTECT project Progress Status: February 2011 An Innovative Public-Private Partnership for New Methodologies in Pharmacovigilance and Pharmacoepidemiology

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• Proof of concept– Temozolomide

– Not illustrating timeliness – VigiBase as of Feb 2009

Work Package 3 - Better use of existing terminologies

Term Level of terminology

# Reports IC

Erythema Multiforme PT 13 +0.30

Stevens-Johnson Syndrome PT 19 +0.68

Toxic Epidermal Necrolysis PT 6 +0.51

Bullous Conditions HLT 42 -0.01

Severe Cutaneous Adverse Reactions

SMQ 47 -0.04

Erythema Multiforme WHO-ART HLT 35 +0.46

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• 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!

Work Package 3 – Novel tools to group ADRs

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• 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

Work Package 3 - Signal detection from clinical trials

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• 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)

Work Package 3 - Signal detection in Electronic Healthcare Records (EHRs)

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• 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

Work Package 3 - Other

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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

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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

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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

Work Package 4 - Issues with current methods

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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

Work Package 4 - Issues with current methods

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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

United-Kingdom

Poland

Denmark

The Netherlands

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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.

Study subject enrolls for the web or phone (IVRS) method of data collection.

Work Package 4: Patient workflow overview

Final outcome survey is completed at the end of pregnancy.

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.

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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

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Work Package 5: Workstreams

Workstreams

A Develop framework for benefit-risk analysis

B Review of methodologies used, elicitation of preferences and integrating effects and preferences

C Criteria for case study selection & case study selection

D Determine data to be gathered from case studies and format required

E Develop software to support application of methodology and graphical representation

F Application of methodology and graphical methodology to case studies wave 1

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Work Package 5: Work Plan

1. 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.

2. Selection of case studies (waves 1 and 2)

3. Data selection/requirements for case studies

4. Identification/development of software for B/R.

5. Application of methodology, recommendations, finalisation of tools, protocols for validation studies.

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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

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Work Package 5: Overview

WS B Methods

WS B Methods

WS C Case studies

WS C Case studies

WS DFramework /

Data

WS DFramework /

Data

WS ESoftware / graphics

WS ESoftware / graphics

WS FApplication

WS FApplication

• 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.

• 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.

• PrOACT-URL framework for performing benefit-risk analysis.

• Oversee working parties for extracting objective measures of magnitude / incidence of benefits and risks.

• PrOACT-URL framework for performing benefit-risk analysis.

• Oversee working parties for extracting objective measures of magnitude / incidence of benefits and risks.

• Not developing software, but explore suitable existing software (possibly with adaptation).

• Not developing software, but explore suitable existing software (possibly with adaptation).

• Apply the methodology to the case studies using the data

• May also elicit the subjective value data for the benefits and risks.

• Apply the methodology to the case studies using the data

• May also elicit the subjective value data for the benefits and risks.

• 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.

• 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.

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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

Collaborators

Literature search

Other initiative

s

Methodological review

Elicitation of suitable methods

Literature search

External meeting

s

Other initiative

sVisual representations review

Elicitation of suitable graphics

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

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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.

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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.

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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)

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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

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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

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Work Package 6: Validation

Started in September 2010

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. 

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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)

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Work Package 7: Training & communication

Objective:

To identify training opportunities and support training programmes to disseminate the results achieved in

PROTECT.

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• Development of a platform of training opportunities.

• Regular interaction with EU2P Consortium.

• Communication Plan: draft list of conferences and other international forums suitable for the presentation of the results of PROTECT.

Work Package 7: Scope

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Work Package 7: Training Platform

https://w3.icf.uab.es/trainingopp(under development)

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More information?

Website: www.imi-protect.eu

Email: [email protected]