Data Quality in Clinical Trials: a Sponsor's view Elena Carzana Data Manager Chiesi Farmaceutici Padova, 27 th September 2012 IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials
Agenda Definition Impacts of quality Chiesi approach & organisation How is the data quality overseen and measured by the Sponsor? Standardization Tools CDISC validators Rationale Cleaning Quality checks & listings Blind Review activity Medical Review activity Relationship (CROs / study team) Metrics Key Performance Indicators Quality Assurance IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 1
Data Quality - DEFINITION Data that support conclusions and interpretations equivalent to those derived from error free data * Quality is commonly defined as fitness for purpose. Quality of information generated should therefore be sufficient to support good decision making ** Is a measure of the degree of usefulness of the data for a specific purpose Institute of Medicine (IOM): Davis Jr, Nolan VP, Woodcock J, Estabrook RW.eds. Assuring Data Quality and Validity in Clinical Trials for Regulatory Decision Making. Workshop Report. Roundtable on Research and Development of Drugs, Biologics, and Medical Devices, Division of Health Sciences Policy, Institute of Medicine. Washington DC: National Academy Press; 1999 ** EMA: Reflection paper on risk based quality managment in clinical trials 4 th August 2011 IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 2
The impacts of Data Quality: STATISTICAL ASPECTS Good data quality means data fit for their use. Data quality may impact on results : STATISTICS: More errors more variability (wider distribution) Errors can introduce variability into the analysis Variability makes it more difficult to see a treatment effect, if there is one Fewer errors less variability (narrower distribution) IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 3
The impacts of Data Quality: REGULATORY ASPECTS Good data quality means data fit for their use. Data quality may impact on: REGULATORY APPROVAL: BAD QUALITY is an INTERNAL FAILURE COST Bad data quality can cause delays in product registrations Regulations do not address a minimum acceptable data quality levels for clinical trial data* Each pharma company sets their own minimum acceptable quality level and methodology for implementing practices to assure that level * Good Clinical Data Management Practices (GCDMP), September 2008 IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 4
Data Quality: CHIESI APPROACH - WHAT QUALITY LEVEL Studies from phase I to phase III Registrative studies (USA and EU) From few dozen to thousands of patients HIGH LEVEL OF DATA QUALITY IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 5
Data Quality: CHIESI APPROACH HOW IT WORKS Standard approach is outsourcing study services ciao CROs contracted to manage data Final responsible for data SI 2006/1928, Regulation 3 ICH E6 HOW DOES THE SPONSOR KNOW THAT A CRO IS WORKING WITH THE EXPECTED LEVEL OF QUALITY? IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 6
Data Quality: CHIESI APPROACH - INTERNAL ORGANISATION Final responsible for data 4 DATA MANAGERS guarantors of data quality members of study teams: Study Manager Clinical Reaserch Physician Statistician Pharmacovigilance Drug Supply Coordinator support the team offering appropriate tools to review data IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 7
Data Quality: HOW IS THE DATA QUALITY OVERSEEN and MEASURED BY THE SPONSOR? Sponsor s actions to be reassured about data quality Quality listings & Blind Data Control Validator tools Review Data cleaning plan Standardization Relationship (CROs / study team) Measurement Key Performance Indicators Quality assurance Metrics (QA) IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 8
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? STANDARDS Document standardisation - CRF Sponsor library - SDTM datasets Process standardisation - Chiesi SOPs to be followed by CROs (SAE reconciliation, Blind Review Meeting, DMP ) IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 9
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? DEDICATED TOOLs OpenCDISC Validator is a collaborative project to develop an open source, easy to use, and commercial-quality tool for ensuring clinical data compliance with CDISC standards. The following are available standard Validator: SDTM 3.1.2 Amend 1 [v1.0] SDTM 3.1.2 [v1.3] SDTM 3.1.1 [v1.3] Define.xml 1.0 [v1.3] ADaM 1.0 [v1.1] SEND 3.0 [v1.0] IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 10
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? OPEN CDISC VALIDATOR IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 11
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? CLEANING Self Evident Corrections avoid sending queries to investigators when the correct answer is obvious 1. ACCURATE DEFINITION OF SEC DOCUMENT (CRO/SPONSOR) 2. RATIONALE USE OF CHECKS (CRO/SPONSOR) 3. COMMON SENSE!! A large number of queries bores investigators and may lead to unaccurate resolution IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 12
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? QUALITY LISTINGS and CHECKS Internal quality listings & checks are run periodically to : check data quality assess the cleaning process (proof of work) identify outliers explore the trends EVIDENCE OF QUALITY To be implemented a QUALITY CONTROL PLAN describing the specifications for these listings IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 13
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? QUALITY LISTINGS PRACTICAL EXAMPLE PULMONARY FUNCTION CURVES (patient specific) Is a TOOL for the team (physician) to review and monitor data. Detected issues never highligthed by CROs ADDED VALUE IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 14
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? BLIND REVIEW ACTIVITY SET UP DATA REVIEW PLAN Active action to decide which data to review and how these data need to be listed MEETING DATA REVIEW MEETING Internally performed Team work Queries definition FINAL DECISION DATA REVIEW REPORT Internally reviewed Team work Strong involvement of Sponsor in data evaluation in order to define the populations of the study IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 15
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? MEDICAL REVIEW Medical review is comprehensive review of medical data to be conducted by the physician (CRO/Sponsor) during the course of the study. NEED: EASY TOOL THAT ALLOWS PHYSICIANS TO REVIEW DATA COLLABORATION: Sponsor/ CRO Sponsor physicians DM DM CRO TOOL: CUMULATIVE EXCEL FILE/s WHERE DATA ARE CATHEGORISED BY ITEMS, FLAGGED IF MODIFIED AND FILTERED GOAL: valid and reliable medical data with an early recognition, identification and reporting of issues impacting on patients' health and well-being IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 16
HOW IS THE DATA QUALITY OVERSEEN BY THE SPONSOR? RELATIONSHIP WITH CRO RELATIONSHIPS BUILD A TEAM Good relationship is the key to success Sponsor has not to replace the CRO in the activities but collaborate with them in the common goal of good data quality! Consolidate and trusted relashionship with CRO makes easier and faster activities! IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 17
HOW IS THE DATA QUALITY MEASURED BY THE SPONSOR? METRICS Periodically the CRO sends Sponsor a summary containing: -query status -data entry status -patients disposition All this info are shared with the monitoring CRO Sponsor project team You can not control what you cannot measure Tom de Marco IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 18
HOW IS THE DATA QUALITY MEASURED BY THE SPONSOR? KEY PERFORMANCE INDICATORS (KPIs) Measures of success that can be used throughout the project to ensure that it is progressing towards a successful conclusion (APM BODY OF KNOWLEDGE 5 TH EDITION) Measurement of CRO execution of the contracted activities MSA in place with a limited pool of CROs where the KPIs are agreed. - Periodic evaluation of study specific performance - Periodic evaluation of overall performances Every KPI is described, specifing how it has to be calculated and the target IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 19
HOW IS THE DATA QUALITY MEASURED BY THE SPONSOR? QUALITY ASSURANCE From dabatabase audit to DM process audit! DM knows the CRO and can support QA staff performing audit -have the described processes been really followed? -is the documentation fine? -have the queries been issued always with a rational approach?.. COMMON GOAL : data quality TOOL: collaboration IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 20
TAKE HOME MESSAGE Sponsor Data Manager role: internal guarantor of data quality who provides study team appropriate tools to monitor data NOT A REPLACEMENT OF DM CRO IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 21
Data Quality in Clinical Trials: a Sponsor's view Thank you! Elena Carzana Data Manager Chiesi Farmaceutici email: e.carzana@chiesi.com IV BIAS ANNUAL CONGRESS Data Quality in Clinical Trials 22