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Approaches to Risk -Based Quality Management
Quality by Design/Quality Systems
F-Crin Workshop on Risk Management in Clinical Trials
Peter Schiemann, PhD Clinical Quality & Risk Management Expert
Widler & Schiemann Ltd., Zug – Switzerland
24 September 2013, Paris
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WS QMS Agenda
�Two Principles of QRM (Quality Risk Management) and QbD (Quality by Design)
�A Glimpse at what FDA and EMA say
�QbD as a Condition of QRM and Study Management
�Common Errors in applying QRM and QbD to Risk-Based Monitoring
�Change Management Aspects
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Two Principles of QRM and QbD
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Ultimate Goals of Quality Management Principles and Goals in the World of
Health Care
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Patient Safety, Rights and Integrityin all clinical trials and post-marketing activities
Data Integrity
of data created in these clinical trials and post-marketing activities
The Focus
WS QMS The Concept of the Design Space applied
to Clinical Trials and Pharmacovigilance
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WS QMS Manage the Design Space
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WS QMS Manage the Design Space
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Manage the Design Space
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Two Principles of QRM & QbD and a Corollary
�Isolated Errors do not matter!
�Errors that are “understood” do not matter!
�Systematic and Process Errors DO matter!
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A Glimpse at What FDA and EMA say
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• Build quality in from outset• Borrow on concepts from manufacturing sector
(e.g. ICH Q9, Q10)• Cycle of Plan-Do-Check-Act• Detect and correct problems in real(or close to
real) time• Leveraging existing data and information in a
systemic way• Allow for prioritization of limited resources
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QbD in Clinical Trials
Protocol* is the blueprint for quality
*Associated implementation plans (e.g., monitoring plan, communication plan, data handling plan, etc.) are also key
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WS QMS GDP – Good Decision -making Practice
The EMA Reflection Paper on QbD and QRM
�Clinical research is about generating information to support decision making
�All steps of a clinical trial are contributing to the decision making, some are formalized by legislation & GCP
– Protocol design– Submission to IRBs and CAs (competent authorities)– Initiation of trial– Informed consent– Oversight of risk benefit of the trial– Trial reporting– Finalization of CSR– Submission or publication
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WS QMS The EMA Reflection Paper on
QbD and QRM
�Decisions are made at various levels on the basis of knowledge founded on the data
�Each decision will only be as good as the processes used to collect, analyze, interpret and report it.
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Risk Control/Mitigation
• What can be done to reduce or eliminate risks?• What are the tolerance limits for identified risks?
� What is the appropriate balance among benefits, risks, and resources?• Have pre-defined risk mitigation strategies for control of risk
when trending suggests tolerance limits may be exceeded, or are exceeded, been developed and have individuals/groups that own each process been identified?
• Is new risk introduced as a consequence of control/mitigation strategies that are put in place?
• Has flexibility needed to deal with unexpected risks that may be encountered?
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Risk Review
• How will risks be tracked - system for detection of significant problems in real time� Centralized monitoring, on site monitoring, quality auditing,
other?� Metrics?� Frequency of review?
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WS QMS Quality Tolerance Limits
�Establish the acceptable variation or tolerance limits for the clinical trial procedures involved
�Bearing in mind the statistical design of the trial and the potential impact of the different levels of variability on the power of the trial– Trial data– Trial protocol procedures and GCP– Trial management procedures
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WS QMS Reporting Quality
�Clear qualitative and quantitative report
�Extent the trial has operated within the tolerance limits
�Conducted to an acceptable level of quality
�Prospective communication with the regulators
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QbD as a Condition of QRM and Study Management
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WS QMS Risk -based Quality Management
�What question is the protocol seeking to answer?
�What does really matter?
�What might go wrong?
�What is the probability it will go wrong?
�How easy is it to identify if it does?
�What are the consequences if it does?
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WS QMS APPROACHES
Prioritization and risk mitigation approaches across several dimensions:– Protection of trials subjects - Rights and Integrity, Safety– Credibility of data and results
Stratified according to knowledge of product (MA status).
Customized approach depending on:– Protocol complexity
• Therapeutic indication and nature of endpoints, including population and co-medications• Administration of the product, dose, formulation• Complexity of study procedures and measurement, including the nature of the
intervention• Vulnerability of the study population
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Trial Conduct
Data Evalution and Writing of Clinical Trial
Report
Trial Design and Trial Initiation
Regulatory Submissions
and/or Publications
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WS QMS Quality by Design: Study set-up
� Objectives
�Support Senior Management and study teams with information on study design-based risk levels
– Prior to study start– During study conduct
�Provide standard approach to assess study quality risk level – allowing comparison across studies
�Offer guidance to study teams to mitigate high and medium risk levels
� Scope
� Conducts risk assessments in first step of study value chain: ‘Study Set-up ’
� Can be applied to all studies:
– Countries, Marketing, early and late Development
– Phase I-IV (global and local)
– Sponsored and supported
– Interventional and non-interventional
How does this help?
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Study Conduct
Retrieval of data occurs along different risk assessment categories - selection of
categories based on study type requirements
Study Design Study Close-out
Risk Assessment Categories1
Tailored Questionnaires for� Sponsored Interventional Studies� Sponsored Non-Interventional Studies � Supported Interventional Studies � Supported Non-Interventional Studies
(in development)
Not all of the listedrisk assessment categories apply to all different study types
Study Environment
Medication
Regulatory
Budget
Process & Documents
Feasibility/ Recruitment
Sampling
Randomization/Data
Outsourcing/ Contracts
Pharmacovigilance/ Safety
Registry
Relationship to External Sponsor
applied
not applied
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WS QMS Risk Analysis for all Risk Universe Entities is
the central activity for cross functional teams
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Prioritizing an entity’s quality and risk data by assessing its
impact, likelihood and detectability along a
transparent set of criteria (scoring along “high”, “medium”, “low”)
Risk Identification & Data Gathering
Qualitative & Quantitative Risk
Assessment
Definition of Mitigating Actions
Defining the set of quality improving and risk mitigating actions in prioritized entities (using the full spectrum of available measures, e.g.
training, audits, etc.)
For each risk, description of chosen measures in terms of
priority, rationale, etc.
Gathering and integration of quality and risk data from
a multitude of databases and other sources (e.g.
Audit reports, CAPA reports, ongoing quality
initiatives, etc.) in order to identify focus areas and
entities
1 2 3
Increasing
interaction of Quality and Business Partners
Driven by Quality representatives
Supported by Business
Partners
ImpactX
LikelihoodX
Detectability
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Analysis of existing data for a Continuous Risk Evaluation
Trial info
Clinical data
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Safety data
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QRM Dashboard
Use the existing data… … to identify areas with increased quality risks
# S/AEs
Allowing for different views:
• Product/Project View
• Process View• Geographical
View
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WS QMS Risk Indicator: Monitoring Visits
delayed
Is monitoring sufficient and
on time?
Clinical TrialCenter
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Study: XYZ
First patient enrolled
Monitoring visit
Month
1 2 3 4 5 6
11 weeks
13 weeks
11 weeks
previous monitoring visit
Monitoring within 10 Weeks After first patient enrolled or
previous monitoring visit
Risk Indicator: Delayed MonitoringIllustrative
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WS QMS Risk Indicator: Premature Terminations
above Protocol Average
Is there an unusual high rate
of early unexpected
patient drop-outs at any site?
Illustrative
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0.15
0.20
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Threshold � 1.3 x Protocol Average
Protocol Average
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Clinical Trial Centers
Study: XYZ Risk Indicator: Premature terminations of patients
1) excl. death, illness,..
Measures average drop-out per patient for a site against the protocol average
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Common Errors in applying QRM & QbD to Risk based Monitoring
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WS QMS Common Pitfalls
�No data driven decision matrix
�No upfront acceptance and rejection criteria
�No upfront decision algorithm, e.g.On site monitoring evidences deviations– Deviations < x% � no action indicated– Deviations > x% but < y% � phone contact– Deviations > y% � root cause analysis & systemic
CAPA
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WS QMS Common Pitfalls
�Decision about conclusions from “risk based monitoring” activities left to the monitor
�Inconsistencies in decision making between studies without rationale for differences
�No clear strategy about centralized monitoring
�Centralized monitoring based on “available” data and not “essential” data
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Change Management Aspects
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WS QMS Change Management Tasks
�Re-invent study design and planning
�Re-invent study management
�Re-invent monitoring
�Re-invent auditing
�Senior Management buy in
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WS QMS Change Management Tasks
�Re-invent study design & planning, e.g.– Verify study Rationale, Objectives & Procedures– Assess risks before activating any sites– Learn from past experience � sites AND processes
as cause of non-compliance– Chose only those service providers who do actually
promote a risk based approach
�Re-invent study management– Use all “tools” effectively– Deploy monitors & project staff where it is really
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WS QMS Change Management Tasks
�Re-invent monitoring– Train monitors to accept and deal with “residual”
errors– Re-invent site monitoring– Re-invent source document verification
• SDV no longer a QC but a “QA” tool– On-site monitoring to “enrich” data from centralized
monitoring– On-site monitoring visits to “confirm” or “reject”
conclusions from centralized monitoring
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WS QMS Change Management Tasks
�Re-invent auditing– Audits as a root cause analysis tool when Study
Monitoring reveals systemic deficiencies– Structured routine audits to assess plausibility of
“error levels”– “Stress Test Audits” to verify robustness of QMS
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WS QMS Change Management Tasks
�Senior Management buy-in– Funding– Resources– Support
�Win the “hearts and minds” of those “in the trenches”
�Change Management starts when Risk based Study Management is being considered!
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WS QMS Contact Details
Peter Schiemann, PhD
Managing PartnerWidler & Schiemann Ltd.
Weinberghöhe 10 BCH 6300 ZugSwitzerland
Mobile: +41 76 378 59 30
e-mail: [email protected]
www.wsqms.com
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