Clinical QA Data Audits A GCP Point of View Linda Del Paggio GCP Compliance BioBridges, LLC.
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Transcript of Clinical QA Data Audits A GCP Point of View Linda Del Paggio GCP Compliance BioBridges, LLC.
Clinical QA Data Audits
A GCP Point of View
Linda Del Paggio GCP ComplianceBioBridges, LLC
Agenda
Introduction
ICH and GCP
GCP and Data Integrity
Investigator Site Audits
Data Vendor Audits
The ICH E6 Good Clinical Practice Consolidate Guideline:
Good Clinical Practice is an international ethical and scientific quality standard for designing, conducting, recording and reporting trials that involve the participation of human subjects.
The ICH E6 Good Clinical Practice Consolidate Guideline:
Compliance with the standard provides public assurance that the rights, safety and well-being of subjects are protected, consistent with principles that have their origin in the Declaration of Helsinki and that the clinical trial data are credible.
GCP & Data Integrity
What is GCP?
A standard for the design, conduct, performance, monitoring, auditing, recording, analyses and reporting of clinical trials that provide assurance that the data and reported results are credible and accurate and that the rights, integrity and confidentiality of trial subjects are protected.
GCP & Data Integrity
Selected Principles of the ICH GCPAll clinical trial information should be recorded, handled and stored in a way that allows its accurate reporting, interpretation, and verification.Systems with procedures that assure the quality of every aspect of the trial should be implemented.
GCP & Data Integrity
Specific ICH RegulationsICH 5.1.1 – the sponsor is responsible for maintaining quality assurance and quality control systems with written SOPs to ensure trials are conducted and data are generated, recorded, and reported in compliance with the protocol, GCP, and applicable regulatory requirements.
GCP & Data Integrity
Specific ICH Regulations
ICH 5.1.3 – Quality control should be applied to each stage of data handling to ensure that all data are reliable and have been processed correctly.
Investigator Site Audits
First line of data retrieval
ALCOA
Attributable
Legible
Contemporaneous
Original
Accurate
Investigator Site Audits
Processes
Protocol Adherence
Investigator supervision
Protocol Deviations/waivers
Monitoring
Safety Monitoring
Data Vendor Audits
Types Of Vendors
Standard Data Management
Data VendorsClinical Laboratories
ECG Vendors
PK Analysis Vendor
Phase I Facility
Data Vendor Audits
Types Of Audits
Qualification Audits
Ongoing Study Audits
Data Audits
Data Vendor Audits
Qualification/Ongoing Audits
Evaluation of:
Organization
Facilities
Systems
Processes
Data Vendor Audits
OrganizationOrganizational Chart
Number of facilities
Who, What ,Where
Number of employees, FTE
Departmental Structures
Turn over rates
Average length of employment
Data Vendor Audits
Facilities
Adequate to support functions
Work Flow
Adequate security
Adequately protected
Adequate back-up of data
Data Vendor Audits
SystemsQuality Function
Standard Operating Procedures
Work Instructions
EmployeesJob Descriptions
CVs
Training
Data Vendor Audits
Processes
How is the data received
How is the data verified
How is the data transferred
How is the data stored
How is the data secured
How is the data saved
Data Vendor Audits
Ongoing Study Audits
Systems
Processes
Data Audits
Data Vendor Audits
Ongoing Study Audits Systems
Standard Operating ProceduresWork InstructionsEmployees
Job DescriptionsCVsTraining
Data Vendor Audits
Ongoing Study Audits
Processes
Study Set Up
Data Flow
Data Analysis
Data Vendor Audits
Study Set Up
Contracted Functions
Transfer of Obligations
Personnel Training
Project Management
Project Oversight
Data Vendor Audits
Data Flow
Documentation of Data/Samples:Receipt &Condition
Verification & Problem Resolution
System Entry/Tracking
Transfer
Storage
Analysis
Data Vendor Audits
Data Verification
Was the data generated per protocol and internal procedures?
Does the raw data generated match the final data set?
Data Vendor Audits
Data Verification
Vendor TypesData Management Vendor
Clinical Laboratory
ECG Vendor
Data Vendor Audits
Data Verification Methods
Data ManagementDatabase Audit
CRF Data to Database
Audit Trails
Data Management Plan
Data Vendor Audits
Clinical Laboratory
Raw data to CRF, eCRF or database
Audit Trails
Comparison with normal ranges
Turn around time to site
Data Vendor Audits
ECG Vendor
Transfer of Data
Reading of Data
Reporting of Data
Over read of Data
Data matches CRF/Database
Audit Trails
Data Vendor Audits
Conclusion