Mireille Zerola – Clinical Data Management Expert

Risk Based Monitoring in Mega Trials

- a case study

Objectives

• Share practical experience of applying Risk

Based Monitoring within a Mega Trial

• Recognise that Boehringer Ingelheim is a

member of TransCelerate Biopharma Inc.

and our experiences have fed into this

initiative

• Acknowledge that a mixture of slides will

be presented within the context of the

TransCelerate Biopharma Inc. RBM

Methodology Position Paper*

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*http://www.transceleratebiopharmainc.org/content/risk-based-monitoring-methodology-position-paper

Topics

• TransCelerate BioPharma Inc

• Mega Trial Case Study

• Build quality by design

• Early and ongoing risk assessment

• Focus on Critical processes and data in study plans

• Use of risk indicators

• Adjustment of monitoring

• Achievements

• Implementation Success Factors

• Questions

• References and Acknowledgements

3

• Non-profit organization (Incorporated 2012)

• Dalvir Gill, Ph.D, CEO

• Combined financial resources and personnel

• Solving industry-wide challenges collaboratively

TransCelerate Biopharma, Inc.

4

Comparator Drugs

Shared Site Qualification & Training

Common Investigator Site Portal

Clinical Data Standards

Risk Based Monitoring

…and TransCelerate continues to evaluate what other initiatives we can work

collaboratively on to improve the way we plan and execute clinical trials

TransCelerate – Active Work Streams

5

Risk Based Monitoring (RBM) Application

Asses risk level

of trial - based

on program,

trial, IP & sites

Identify critical data

points and risk

indicators with

thresholds for action

Monitoring approach

and plan developed

based on risk of trial &

critical data points

Monitoring adjusted as

required

• An adaptive approach to clinical trial monitoring that directs monitoring focus and

activities to the evolving areas of greatest need which have the most potential to impact

patient safety and data quality.

6

The Climate has Changed

7

“Monitoring” – The Shift

Current

100%

SDV/sampling

On-site

Proposed

Risk-based

critical data focus

Off-site +

triggered on-site

Vision

Analytics

Centralised

8

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

9

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

10

Case Study - The Challenge

Phase III

Study Duration

36 months

Remote Data Capture17,000+ patients

1,000+ investigators

6 continents

Trial Team

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Case Study – The Impact

Planning

Conduct

Reporting

12

Case Study – Preparation

Infrastructure

And

Planning

Documentation

Communication

• Infrastructure— Steering and Data Monitoring Committees

• Site Feasibility— Global

— Investigator

• Trial Protocol and Amendments

• Trial Training Plan

• Monitoring Plan— Onsite Monitoring Guideline

— Overall Operation Plan

— Communication Plan

— Data Quality document

• Data Collection Tool/CRF

• ISF Review

13

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

14

Case Study - Risk Assessment

Consider Risks:

- Centrally

- Site

What could go

wrong?

How can we

measure?

How can we

mitigate?

What is the

impact?

15

Risk Assessment - Indicators

Safety Investigational Product

Subject Recruitment and Discontinuation Data Quality

On-site Workload-Based Triggers Essential Documents

Staffing, Facilities, and Supplies Issue Management

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Risk Assessment - Tools

1. Determine risks which could affect patient safety, data integrity or regulatory compliance

2. Determine how risks will be managed

3. Categorize the risk level for each category (high, medium, low)

4. Determine overall study risk level to establish baseline monitoring

- Risk Assessment Categorisation Tool (RACT)

15 categories to consider: Safety, Study Phase, Complexity, Technology, Patient Population, Data Collection, CRF

Source, Endpoints, Organisational Experience, IP/Study Medication, IP Logistics/Supply Chain, Blinding, Operational

Complexity, Geography, Budget

17

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

18

*ALCOA – FDA Guidance for GCP Housekeeping (Attributable-Legible-Contemporaneous-Original-Accurate)

Components Considerations

Source Data Verification (SDV) —Make clear that this is only the verification of transcription

from source to eCRF

Source Data Review (SDR) —Do the site staff understand the protocol (is it being

followed)?

—Does the P.I. have oversight?

—ALCOA* aspects of source data

Unreported Event Review (UER) —Review of source data to ensure that event are

documented in eCRF

Other —Any other aspects of on site GCP monitoring

Case Study –

On site Monitoring : Separate the components

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Routine monitoring activities: essential doc review, site qualification/training as applicable,

adequate facilities, study supplies

Enable Central

Monitoring Capability

Enable Central

Monitoring Capability

Emphasis on Critical

Data & Processes at Site

Emphasis on Critical

Data & Processes at Site

Targeted and Focused

SDV

Targeted and Focused

SDV

Integrated, Formal Risk

Assessment

Integrated, Formal Risk

Assessment

Sampling or 100% SDV

Understanding the Change –

Operating Differently

A Better

WayFrom RBM

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MV #1SIV MV #2 MV #3 MV #4 MV #5 MV #6 MV #7 COV

1st subject enrolled

On-site Monitoring visits scheduled at regular intervals:

Study Complexity

Study Duration / Phases

Site Risk Level (site experience, site issues)

What

about…

Understanding the Change -

Current Site Monitoring One Size Fits All

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MV #1SIV MV #2 MV #3 MV #4 MV #5 MV #6 MV #7 COV

MV #1SIV MV #2 MV #3 Triggered MV #4 COV

1st subject enrolled

Between Visits – Site Interactions

Understanding the Change - A Better Way (RBM)

Central Monitoring

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Case Study - Monitoring Activity : Sampling Approach Based on

Risk

Monitoring Activity High Risk Medium Risk Low Risk

Validation and Review of Data

(Central/Off-site)

100% 100% 100%

SDV of Critical Data for First Randomized Subject >75 - 100% >50 - 75% 0 - 50%

SDV of Critical Data for Subsequent Randomized

Subjects

>15 - 25% >5 - 15% 0 - 5%

SDR of Critical Data for First Randomized Subject >75 - 100% >25 - 75% 0 - 25%

SDR of Critical Data for Subsequent Randomized

Subjects

>25 - 40% >10 - 25% 0 - 10%

Informed Consent Review >75 - 100% >50 - 75% 20 - 50%

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Case Study – Develop an Integrated Quality & Risk

Management Plan (IQRMP)

Group SDR* SDV* DM Audit Error limits

Blood Pressure 10% - 100% Range

100% Consistency Sys>Dia

100% Check of duplicates

<2% <2%

Medication dispensing error 10% 10% 100% check eCRF vs IXRS <2% 0%

Medication Compliance 10% 10% 100% Range

100% Consistency

<2% <2%

• Develop with protocol

• Submit IQRMP with protocol

• Derive from trial quality plan and risk assessment analysis

• Address concerns from: Audits, Central Monitoring / Data Management, Statistics / Fraud

detection and SDV

* SDR Source Data Review (ALCOA)

SDV Source Data Verification (Verification of transcription)

24

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

25

SDV Web tool

RDC IVRS

Site Risk

Based Approach

Spreadsheet

Site data

Admin system (CTMA)

Other Site Risks

(Data Centre)

Manual PVs

(via Trial Team)

SDV allocation, SDV done and

dates, CRA site assessment

level, site staff changes

Country, Inv. Name,

# Patients randomised, discontinued,

Fatal, AEs, OEs, related AEs,

Adjudicated, In/Excl PVs

# Patients

Screened, etc

CRA, CRA Manager, Site

Manager, Planned POSV

Score and comment

PV comment, PV data

BASCOTrial

Tracking

Matrix

Case Study - Where does the data come from ? Site Risk

Spreadsheet

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Highlighted fields

I Screen failures>50% of randomised

J Discontinued patients >40% of randomised

P Number of SAE/OE below expectation for regional average for

reporting

Q Greater than one related SAE reported by site

S >90 days since patient death and Death not yet adjudicated

T Any patient indicated as LTFU (lost to follow-up in database)

U Manual PVs (these have all been reported and reviewed

by trial team as important)

W Number of patients with Incl/Exclusion criteria PVs

X Changes in site staff

V Patients with a PV at entry - This is a CRA risk factor as CRA may not be aware of these patients as they were not selected for Complete SDV

Case Study - How to use a Site Risk Spreadsheet?

Reviewing Site data

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Case Study – How to use a Site Risk Spreadsheet?

Central data assessment/Fraud/Misconduct

Patient # Actevent Visit Date Systolic Diastolic Pulse Rate20 VISIT 1 29/11/2010 110 70 64

05 VISIT 1 05/10/2010 110 70 64

08 VISIT 1 09/10/2010 110 70 68

24 VISIT 1 05/01/2011 110 70 68

01 VISIT 1 24/09/2010 130 80 70

22 VISIT 1 20/12/2010 130 80 70

10 VISIT 1 09/10/2010 140 90 62

15 VISIT 1 05/11/2010 140 90 62

11 VISIT 1 25/10/2010 140 90 70

21 VISIT 1 17/12/2010 140 90 70

• Central review identifies issues not seen during SDV or Audits

• How would you explain this site’s data to an inspector?

It was both Audited and SDV’d!

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Case Study - Getting the Quality Right

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Quality

Local Manager

Trial Team

Define Quality• If there is a change in CRA

assessment CAPA• Introduce feedback process

Oversight• Strategic direction

• Trial level

• Country level

CRA Site Ownership• Responsibility

• Empower , can influence site

assessment

Adapt Monitoring• Site Level

• Trial Level – Centrally

Risk Management

Integrated

Functional Plans

Quality

Central

Monitoring

Clinical Data

Mngt

Vendor /

Partners

Site Operations

Smart Analytics

/ Information

Flow

Creating a New Culture for Operating Differently

30

TransCelerate Approach – Key Elements

Build QbD into

trials

Early and ongoing

risk assessment

Focus on

Critical

Processes and

Data in Study

Plans

Use of Risk

Indicators,

Thresholds &

Action Plans

Adjustment of

monitoring

activities

31

Case Study - Triggers

• The definition of triggers with associated

thresholds is essential for ensuring a consistent

quality

• Independent of reduced onsite monitoring

approach

• What is a trigger?— It is an automatic first stage in a ‘CAPA’ process to

ensure a correct sequence of actions to a ‘fault’ or a

surrogate measure of a ‘fault’

— Real risk

— Surrogate risk

— It should be specific

— It should be appropriate to the issue seen

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Case Study – Central Monitors and Triggers

• Trigger frequency— Protocol Violations / Protocol Deviations

— Duplicate values

— Misconduct / potential fraud

— High enrolment rates— Can site manage high volume of patients?

— Is the data current?

— Is the data plausible?

— Determine the inspection risk

— Events— Unreported SAEs

— Unreported AEs

— General under reporting of events

• Communication— Regular feedback by teleconference

— User friendly reports, colour coding

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Case Study – Action for Triggers

Trigger (internal) SDV SDR UER Monitoring

Interval

Other Risk

Low event reporting

(under reporting?)chi statistic*=((SiteAEact-SiteAEexp)**2)/SiteAEexp Expected number of

events at site - SiteAEexp=(RegionAE/RegionPat)*SitePat

Actual number of events at site – SiteAEact

RegionAE – Actual number of events in region / country

RegionPat – Actual number of patients in region / country

SitePat – Actual number of patients in Site

- -

20%

- Ensure sites

understand event

reporting

requirements (Chi>6)

S

Unreported SAEs

(CM / Event Monitor may identify events

from source documentation reviewed

centrally)

- -

100%

- Re-train site in

reporting

requirements

S

Unreported AEs

(CM / Event Monitor may identify events

from source documentation reviewed

centrally)

- -

40%

- Re-train site in

reporting

requirements

S

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Case Study – Triggers by CRA and SDV at Site

AG Last Onsite Visit outside of the monitoring manual

specification

AJ No Onsite Visit conducted yet for SDV

Highlighted fields

AB Site level has not been updated at any time

AC/AD Flagged SAEs in SDV Web site have not been

indicated as completed

AE/AF Patients flagged as “All CRF” no SDV in last 6

months

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Case Study – Mega Trial Achievements

• Trial initiated May 2010, concluded in June 2013

• LPO to Database Lock – 4.5 weeks

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Description Achievement

Entered patients > 17 000

Continents 6

Countries 50

Sites > 1 000

eCRF pages entered ~ 1 100 000

eCRF discrepancies generated > 300 000

Adjudicated deaths ~ 1 300

Adverse Events > 35 000

Serious Adverse Events ~ 13 000

Outcome Events ~ 23 500

Vital Status obtained 99.7%Improved quality as was

monitoring priority

Implementation Success Factors

People

Evolution of On- and Off-site

Monitoring• Evolve site monitoring competencies and critical thinking

New Central Monitoring• Early issue detection; data review and interpretation;

issue triage; direction & adaptation of site monitoring

ProcessTransCelerate RBM Methodology

(Risk Assessment / IQRMP)• Flexible execution of methodology

• Collaborative Learning through Pilots and FDA Feedback

Technology

Integrated, reliable, consumable data• Timely aggregation of all data sources

• Flexible, dynamic analytical capabilities

Smart analytics /

Issue Detection• Detection of potential issues impacting patient safety,

data integrity, and data reliability

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Questions

38

References and Acknowledgements

• TransCelerate Biopharma Inc.

• Andy Lawton, Global Head of Clinical Data Management Boehringer Ingelheim, UK Ltd

• Mary Mills, RN, CCRAMary Mills & Associated, LLC

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