Best Practices: Centralized Monitoring

Best Prac*ces: Centralized Monitoring

Presented by: Lorraine D. Ellis, MS, MBA

President/CEO Research Dynamics ConsulAng Group, Ltd.

and William Gluck, Ph.D.

VP, DATATRAK Clinical and ConsulAng Services DATATRAK InternaAonal, Inc.

Speakers Lorraine D. Ellis, MS, MBA, Research Dynamics ConsulAng Group, Ltd. @resdyn

Lorraine D. Ellis, is the founder/CEO of Research Dynamics, a full service CRO. Most of her 35 years’ experience in the industry has been in clinical research. Her experAse includes integraAng technology with clinical research processes over the past 20 years and developing state-‐of-‐the-‐art training programs for clinical research professionals.

William Gluck, Ph.D, DATATRAK InternaAonal, Inc. @DATATRAKinc

Bill Gluck joined DATATRAK InternaAonal in October 2010 as VP of DATATRAK’s Clinical and ConsulAng Services. Dr. Gluck has more than 25 years of experience in the pharmaceuAcal and biotechnology industries and has diversified experience in clinical trial management systems and electronic data capture.

Agenda

•  Why Centralized Monitoring? •  Best PracAces in Clinical OperaAons •  Best PracAces in Clinical Data Management •  Summary and Conclusions

Centralized Monitoring

“Remote monitoring of trial acAviAes and CRF data”

(i.e. not at InvesAgator Site)

Why Centralized Monitoring?

•  EDC and other technology makes it possible •  FDA “recommends” using centralized monitoring •  Improves ability to ensure the quality and integrity of data

•  Real Ame review of real Ame data entry •  Earlier monitoring of data to prevent further errors

•  Decreased reliance on on-‐site visits •  Decreased costs

Data flow & Monitoring: the past

Pa*ent Data

Database

OR

Data Flow & Monitoring: The Future

Centralized Database

CRC CRA

CDM

Centralized Monitoring

•  Improves ability to ensure the quality and integrity of data – Some data anomalies found quicker

•  E.g., Fraud – Non-‐random data distribuAons – More frequent monitoring – Earlier findings of protocol violaAons

EDC capabiliAes facilitate centralized monitoring

•  Access to source and CRF data •  Data analysis and review to idenAfy key data issues or site issues (poor vs good sites)

•  Greater focus on key data •  Tools and funcAonality of EDC systems

Maximize technology change processes

•  Need changes in processes of: –  CollecAon, monitoring, tracking, cleaning

•  Real Ame data processing requires real Ame interacAon between Clin Ops and CDM

•  CRF design including protocol deviaAons and edit checks require both Clin Ops and CDM

•  Query process is more real Ame and interacAve between Clin Ops and CDM for real Ame changes.

Centralized Monitoring AcAviAes (page 1)

•  Some same as on-‐site monitoring – Data consistency – Range checks – Data completeness – Data checks within and between sites – Determine need for on-‐site monitoring frequency and duraAon based on quality of eCRF data

– Decrease Ame on-‐site •  Collect and review regulatory documentaAon


•  IdenAfy •  Missing data •  Incomplete data •  Inconsistent data •  Errors in data collecAon and reporAng

•  Data trend analysis •  IdenAfy protocol deviaAons or protocol issues •  IdenAfy eCRF misinterpretaAons of quesAons. •  When possible, verify source data remotely


•  Analyze – Site characterisAcs in comparison with others – Assess site compliance – Assess performance metrics per site and across sites •  Protocol violaAons •  Screen failure rates (and possibly reasons) •  Entry criteria violaAons and paferns •  Time to enter data ager visit •  Time to answer queries

Centralized Monitoring Changes

•  Centralized monitoring will need site processes well-‐defined and opera*onal

•  On-‐site visits will have a different focus: %SDV and site performance evaluaAon

•  More CRF data review in real Ame so real Ame data entry is expected

•  ExpectaAons that query resoluAon is in real Ame and an ongoing process (& not just before next monitoring visit)

Site Processes •  Site will need well-‐defined standard processes that can be evaluated at the iniAaAon visit to ensure consistent procedures and data collecAon. –  Protocol procedures –  Record keeping –  Source documentaAon procedures. – Data entry – Data reporAng – Adherence to entry criteria –  ICF verificaAon –  Product accountability

Performance metrics

•  Performance metrics to be reviewed/discussed with site: – Higher frequency of data errors, violaAons etc. relaAve to other sites

–  Inconsistent data – Poor study performance – Late eCRF data entry – Slow query resoluAon – Enrollment speed

New Monitoring Focus with Centralized Monitoring

•  Focus on the site processes and correcAng processes and not just data –  ProtecAng subjects –  Data integrity –  GCP and protocol compliance

•  Focus on KEY data elements •  On-‐site monitoring frequency will depend on many

factors and be variable •  Focus on InvesAgator supervision and performance •  Data errors will be studied to determine systemic issues

at site

Clinical OperaAons: The Future! Monitoring process has changed.

•  Real Ame centralized monitoring (not just every 4-‐6 wks) •  Data reviewed off-‐site •  ConAnuous data flow to CDM •  CRF design with Clin Ops and CDM

–  Includes protocol compliance –  Edit checks to reduce queries –  Database designed early requiring earlier data decisions

•  SequenAal processes become simultaneous (Clin Ops and CDM) •  Silo monitoring processes become integrated with CDM •  Poor communicaAon is improved with interacAve communicaAon

tools in real Ame (from EDC system) •  Less data checking and focus on site performance conAnuously •  EDC metrics provide “window” to performance (Ame to eCRF compleAon, #

queries, # data errors, etc)

Data Flow & Monitoring: The Future

Centralized Database

CRC CRA

CDM

Clinical Data Management

Process Driven Technology Driven Cross-‐FuncAonally Driven

Suppor*ng Centralized Monitoring – Best Prac*ces in CDM

•  Define ‘risk’ within your company culture and comfort zone

•  Develop a risk-‐based plan •  Data Quality and Integrity Checks –  Increased checks –  Increased data collecAon

•  Technologically Few Challenges •  Process/Workflow – KEY!

Best Prac*ces in CDM: Preparing For a Risk Assessment

Approach •  IdenAfy criAcal study data and processes, e.g.

–  Endpoints –  Serious Adverse Events –  RandomizaAon/ Blinding –  Consent –  Eligibility Criteria –  Risks specific to protocol design and conduct

•  Perform and document a risk assessment to idenAfy risks to these criAcal data and processes

•  Design plans tailored to address important and likely risks idenAfied during risk assessment

Best Prac*ces in CDM: Development of a CDM Risk Plan

•  Define criAcal data – Safety – Efficacy

•  Work Backwards – The study team working closely with Biometrics/BiostaAsAcs determine tables, figures/graphs and lisAngs (TFL’s) for the clinical study report from the protocol – Collect only data included in the TFL’s or that will be reported

Best Prac*ces in CDM: Risk Assessment

•  Once criAcal data are idenAfied determine the data hierarchy

•  Develop a plan to review and ‘clean’ the most criAcal data using the most comprehensive approach possible

•  ParAal SDV is OK

Best Prac*ce: Risk-‐Based Plan on Cleaning Data

•  Primary Endpoint or CriAcal Data •  Edit Checked; Manual Review; SDV; Freeze; Data Lock

•  Secondary Endpoint Data – Level 1 •  Edit Checked; SDV; Freeze; Data Lock

•  Secondary/SupporAve – Level 2 •  Edit Checked; Freeze; Data Lock

Conclusions

•  The goal and focus of centralized monitoring is to improve our ability to ensure the quality and integrity of data

•  Assess and define criAcal data – create a plan to leverage technology to enhance centralized monitoring

•  Real Ame management of data requires real Ame interacAon of all involved in the study

QuesAons??

Contact InformaAon: Lorraine D. Ellis Bill Gluck 585-‐381-‐1350 x283 440-‐443-‐0082 x114 [email protected] [email protected]

@ResDyn @DATATRAKinc