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Data integrity is a global mandatory requirement for the regulated healthcare industry. It is more than a mere expectation-it's a basic element of good documentation practices, one of the most fundamental pillars of a quality management system. Robustness and accuracy of the data submitted by manufacturers to regulatory authorities when bringing a medical product to market are crucial.
The purpose of this book is to consolidate existing data integrity principles and expectations from several regulatory sources-including the U.S. Food and Drug Administration, World Health Organization, and European Medicines Agency-into a single and handy document that provides detailed, illustrative implementation guidance. It serves as a means of understanding regulatory agencies' position on good data management and the minimum expectation for how medical product manufacturers can achieve compliance.

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Business

Qualité, hygiène, sécurité, environnement

Total Quality Management

Gestion et management

Economics

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Publié par	ASQ Quality Press
Date de parution	08 mai 2019
Nombre de lectures	0
EAN13	9781951058487
Langue	English

Informations légales : prix de location à la page 0,3000€. Cette information est donnée uniquement à titre indicatif conformément à la législation en vigueur.

Extrait

Data Integrity and Compliance
A Primer for Medical Product Manufacturers
José Rodr í guez-P é rez, PhD
ASQ Quality Press
Milwaukee, Wisconsin

American Society for Quality, Quality Press, Milwaukee 53203
© 2019 by ASQ. Printed in 2019.
All rights reserved.
Library of Congress Cataloging-in-Publication Data
Names: Rodr í guez P é rez, Jos é , 1961– author. | American Society for Quality, issuing body.
Title: Data integrity and compliance : a primer for medical product manufacturers / by Jose Rodriguez-Perez.
Description: Milwaukee, Wisconsin : ASQ Quality Press, [2019] | Includes bibliographical references and index.
Identifiers: LCCN 2019003748 | ISBN 9780873899871 (hardcover : alk. paper)
Subjects: | MESH: Pharmaceutical Preparations—standards | Computer Security— standards | Equipment and Supplies—standards | Quality Control | Drug Industry—standards | Data Accuracy | United States
Classification: LCC RS122.2 | NLM QV 771 | DDC 615.10285—dc23 LC record available at https://lccn.loc.gov/2019003748
No part of this book may be reproduced in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.
Publisher: Seiche Sanders
Sr. Creative Services Specialist: Randy L. Benson
ASQ Mission: The American Society for Quality advances individual, organizational, and community excellence worldwide through learning, quality improvement, and knowledge exchange.
Attention Bookstores, Wholesalers, Schools, and Corporations: ASQ Quality Press books, video, audio, and software are available at quantity discounts with bulk purchases for business, educational, or instructional use. For information, please contact ASQ Quality Press at 800-248-1946, or write to ASQ Quality Press, P.O. Box 3005, Milwaukee, WI 53201–3005.
To place orders or to request a free copy of the ASQ Quality Press Publications Catalog, visit our website at http://www.asq.org/quality-press .

This book is dedicated to my parents.
In loving memory of my mother, Josefa, who is no longer with us but whose love and guidance are such a big part of me.
And to my father, Ginés, for your endurance and perseverance.
The work ethics and strength both of you taught me are my guide today.

Acronyms
AIP
Application Integrity Policy
ALCOA
Attributable, Legible, Contemporaneous, Original, and Accurate
ANDA
Abbreviated New Drug Application
API
Active Pharmaceutical Ingredient
CFR
Code of Federal Regulations
CDER
Center for Drug Evaluation and Research
CMC
Chemistry, Manufacturing, and Controls
CoA
Certificates of Analysis
CRF
Case Report Form
CRO
Contract Research Organization
DMF
Drug Master File
DQ
Design Qualification
EBR
Electronic Batch Record
ECG
Electrocardiogram
eCRF
Electronic Case Report Form
EMA
European Medicines Agency
FAT
Factory Acceptance Testing
FDA
Food and Drug Administration
FDASIA
Food and Drug Administration Safety and Innovation Act
FD&C
Food, Drug, and Cosmetic Act
FT-IR
Fourier-Transform Infrared Spectroscopy
GC
Gas Chromatograph
GCP
Good Clinical Practice
GDEA
Generic Drug Enforcement Act
GDP
Good Distribution Practice
GDocP
Good Documentation Practice
GLP
Good Laboratory Practice
GMP
Good Manufacturing Practice, also cited as cGMP (Current Good Manufacturing Practice)
GXP
Good Practice
HPLC
High-Performance Liquid Chromatography
ICH
International Conference on Harmonization
IQ
Installation Qualification
IRB
Institutional Review Board
ISO
International Standardization Organization
IT
Information Technology
LIMS
Laboratory Information Management System
MHRA
Medicines and Healthcare Products Regulatory Agency
OOS
Out of Specification
OQ
Operational Qualification
ORA
Office of Regulatory Affairs
PAI
Preapproval Inspection
PDF
Portable Document Format
PIC/S
Pharmaceutical Inspection Co-operation Scheme
PLC
Programmable Logic Controller
PQ
Performance Qualification
QA
Quality Assurance
QC
Quality Control
QMS
Quality Management System
QRM
Quality Risk Management
SAT
Site Acceptance Testing
SOP
Standard Operating Procedure
URS
User Requirement Specification
USP
United States Pharmacopeia
UV/Vis
Ultraviolet/Visible Spectrophotometry
WHO
World Health Organization

Preface
In recent years, there has been a dramatic increase in the number of U.S. Food and Drug Administration (FDA) warning letters, World Health Organization (WHO) notices of concern, and European Medicines Agency (EMA) statements of noncompliance in which false or misleading information has been identified during regulatory inspections. Failure to properly manage data integrity in regulated healthcare industries applies equally to paper and electronic data. It can arise either from poor systematic control of the data management systems due to a lack of knowledge, careless work, or intentionally hidden, falsified, or misleading data. This is troubling because ensuring data integrity is a critical component of the industry’s responsibility to ensure the safety, efficacy, and quality of medical products, and of regulators’ ability to protect the public health. In the case of the U.S. FDA, these data integrity–related current good manufacturing practice (cGMP) violations have led to numerous regulatory actions, including warning letters, import alerts, and consent decrees.
In the medical product manufacturing field, data integrity lapses are not limited to fraud or falsification. They can be totally unintentional and still pose risk. Therefore, any potential for compromising the reliability of data is a risk that must be identified and understood in order to place appropriate controls to manage them.
Data integrity is a global mandatory requirement for the regulated healthcare industry. It is more than a mere expectation. It is also a basic element of good documentation practices, one of the most fundamental pillars of quality management systems (QMSs), including cGMP. Developing and bringing a medical product to market involves different players and activities; therefore, robustness and accuracy of the data submitted by manufacturers to regulatory authorities is crucial. The data must be comprehensive, complete, accurate, and true to ensure the quality of studies supporting applications for medical products to be placed on the market.
The purpose of this book is to consolidate existing principles and expectations from several regulatory sources into a single and handy document providing detailed illustrative implementation guidance. It must be considered as a means of understanding comprehensive regulatory agencies’ position on good data management/data integrity and the minimum expectation on how medical product’s manufacturers can achieve compliance.
Sources of principles and expectations for data integrity used in this book were the following: EMA Questions and Answers: Good Manufacturing Practice-Data Integrity (2016), WHO Guidance on Good Data Management and Record Management Practices (2016), U.S. FDA Guidance for Industry on Data Integrity and Compliance with cGMP (2018), Pharmaceutical Inspection Co-operation Scheme (PIC/S) Draft Guidance Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments (2018), and the UK Medicines and Healthcare Products Regulatory Agency (MHRA) GXP Data Integrity Definitions and Guidance (2018).
I would like to acknowledge the tremendous job performed by authors and reviewers from above-mentioned FDA, EMA, MHRA, PIC/S, and WHO guidance documents. All of you are doing a terrific job developing meaningful expectations and requirements that contributes to the availability of safer medical products.
Although above-mentioned guidance documents used the word “should” (as they contain mostly nonbinding recommendations rather than regulations) when referring to good data management and data integrity expectations, I used the much stronger word “must” to denote the obligation to perform such activity in order to establish effective data management controls and to avoid problems during regulatory inspections.
Regulatory expectations are that all data be reliable and accurate and good data management practices apply to all elements of the medical product manufacturing quality systems. Table 4.1 depicts the U.S. FDA § 21 Code of Federal Regulations (CFR) part 211cGMP requirements for attributable, legible, contemporaneous, original, and accurate (ALCOA) data. While some of the requirements are fully explicit (for example, § 211.110 or § 211.160 requirements for contemporaneous recording of data), others are more implicit. But all of them are requirements. Table 4.2 includes similar EU EudraLex Volume 4 cGMP requirements.
This book focuses on the application of data management principles and procedures to the manufacturing of medical products, covering the whole supply chain, from suppliers of raw materials and components to the distribution of finished products and pharmacovigilance activities. The focus is on those principles that are implicit in existing guidance documents and regulations and that, if not robustly implemented, can impact reliability and completeness of data and undermine the robustness of decision making based upon those data. Illustrative examples are provided as to how these principles may be applied to current situations. Additionally, it gives explanations as to what these high-level requirements mean in practice and what must be demonstrably implemented to achieve compliance.
The scope of this book is designated as “GXP” in that everything contained here is good practice (GXP) unless stated otherwise. The same good documentation practices (GDocPs) apply to manufacturing (GMP), clinical (GCP), laboratory (GLP), distribution (GDP), pharmacovigilance, and so on.
The recommendations contained in this book apply equally to all type of data (p