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