《仪器与方法验证专著》（英文版） Analytical Method Validation and Instrument Performance veriticatig

CONTRIBUTORS Yoshiki Nishiyama, Eli Lilly Japan KK, 4-3-3 Takatsukadai, Nishi-ku, Kobe 651-2271, Japan eil Pearson, Eli Lilly Canada, Inc, 3650 Danforth Avenue, Toronto, Ontario min 2E8. Canada Anna Rebelo-Cameirao, Eli Lilly Canada, Inc, 3650 Danforth Avenue Toronto, Ontario MIN 2E8. Canada Yu-Hong Tse, Ph. D, GlaxoSmithKline Canada, Inc, 7333 Mississauga Road North, Mississauga, Ontario LSn 6L4, Canada Gilman Wong, GlaxoSmithKline Canada, Inc, 7333 Mississauga Road North Mississauga, Ontario L5N 6L4, Canada Xue-Ming Zhang, Ph. D, Novex Pharma, 380 Elgin Mills Road East, Richmond Hill, Ontario L4C 5H2, Canada

viii CONTRIBUTORS Yoshiki Nishiyama, Eli Lilly Japan KK, 4-3-3 Takatsukadai, Nishi-ku, Kobe 651-2271, Japan Neil Pearson, Eli Lilly Canada, Inc., 3650 Danforth Avenue, Toronto, Ontario M1N 2E8, Canada Anna Rebelo-Cameirao, Eli Lilly Canada, Inc., 3650 Danforth Avenue, Toronto, Ontario M1N 2E8, Canada Yu-Hong Tse, Ph.D., GlaxoSmithKline Canada, Inc., 7333 Mississauga Road North, Mississauga, Ontario L5N 6L4, Canada Gilman Wong, GlaxoSmithKline Canada, Inc., 7333 Mississauga Road North, Mississauga, Ontario L5N 6L4, Canada Xue-Ming Zhang, Ph.D., Novex Pharma, 380 Elgin Mills Road East, Richmond Hill, Ontario L4C 5H2, Canada

PREFACE For pharmaceutical manufacturers to achieve commercial production of safe and effective medications requires the generation of a vast amount of reliable data during the development of each product. To ensure that reliable data are generated in compliance with current Good Manufacturing Practices(cGMPS), all analy ical activities involved in the process need to follow Good Analytical Practices (GAPS). GAPs can be considered as the culmination of a three-pronged approach to data generation and management: method validation, calibrated instrument, and training. The requirement for the generation of reliable data is very clearly repre- sented in the front cover design, where the three strong pillars represent method validation, calibrated instrument, and training, respectively This book is designed to cover two of the three pillars of data generation. The chapters are written with a unique practical approach to method validation and instrument performance verification. Each chapter begins with general require- ments and is followed by the strategies and steps taken to perform these activities The chapter ends with the author sharing important practical problems and their solutions with the reader. I encourage you to share your experience with us, too cherou have observations or problem solutions, please do not hesitate to email to me at chung_ chow chan @cvg ca. with the support of the Calibration Validation Group(CVG)in Canada, I have set up a technical solution-sharing pageattheWebsitewww.cvg.ca.Thethirdpillartrainingisbestlefttoindi- vidual organizations, as it will be individualized according to each organization strategy and culture The method validation section of this book discusses and provides guidance for the validation of common and not-SO-common analytical methods that are used to support development and for product release. Chapter I gives an overview of the activities from the discovery of new molecules to the launch of new product

PREFACE For pharmaceutical manufacturers to achieve commercial production of safe and effective medications requires the generation of a vast amount of reliable data during the development of each product. To ensure that reliable data are generated in compliance with current Good Manufacturing Practices (cGMPs), all analyt￾ical activities involved in the process need to follow Good Analytical Practices (GAPs). GAPs can be considered as the culmination of a three-pronged approach to data generation and management: method validation, calibrated instrument, and training. The requirement for the generation of reliable data is very clearly repre￾sented in the front cover design, where the three strong pillars represent method validation, calibrated instrument, and training, respectively. This book is designed to cover two of the three pillars of data generation. The chapters are written with a unique practical approach to method validation and instrument performance verification. Each chapter begins with general require￾ments and is followed by the strategies and steps taken to perform these activities. The chapter ends with the author sharing important practical problems and their solutions with the reader. I encourage you to share your experience with us, too. If you have observations or problem solutions, please do not hesitate to email them to me at chung chow chan@cvg.ca. With the support of the Calibration & Validation Group (CVG) in Canada, I have set up a technical solution-sharing page at the Web site www.cvg.ca. The third pillar, training, is best left to indi￾vidual organizations, as it will be individualized according to each organization’s strategy and culture. The method validation section of this book discusses and provides guidance for the validation of common and not-so-common analytical methods that are used to support development and for product release. Chapter 1 gives an overview of the activities from the discovery of new molecules to the launch of new products in ix

PREFACE the pharmaceutical industry. It also provides an insight into quality systems that need to be built into the fundamental activities of the discovery and development processes. Chapters 2 to 5 provide guidance and share practical information for validation of common analytical methods(e.g, potency, related substances, and dissolution testing). Method validation for pharmaceutical excipients, heavy met als, and bioanalysis are discussed in Chapters 6 to 8 The instrument performance verification section of the book provides unbiased information on the principles involved in verifying the performance of instru- ments that are used for the generation of reliable data in compliance with cGMPs The reader is given different approaches to the successful verification of instru- ment performance. The choice hich approach to implement is left reader based on the needs of the laboratory. Chapters 9 to 15 provide infor- mation on common analytical instruments used in the development laboratory (e. g, HPLC, UV-Vis spectrophotometers, and pH meters). Chapter 13 provides a detailed discussion of the LC-Ms system, which is fast becoming a standard nalytical laboratory instrument. Since a great portion of analytical data from the drug development process comes from stability studies, Chapter 16 is included to provide guidance to ensure proper environmental chamber qualification Computers have become a central part of the analytical laboratory. Therefore, we have dedicated the last two chapters to an introduction to this field of computer system and software validation. Chapter 17 guides quality assurance managers, lab managers, information technology personnel, and users of equipment, hard ware, and software through the entire qualification and validation process, from writing specifications and vendor qualification to installation and to both initial and ongoing operations. Chapter 18 is an in-depth discussion of the approaches to validation of Excel spreadsheets, one of the most commonly used computer programs for automatic or semiautomatic calculation and visualization of data The authors of this book come from a broad cultural and geographical base of pharmaceutical companies, vendors and contract manufacturers and offer a broad perspective to the topics. I want to thank all the authors, co-editors, reviewers, and the management teams of Eli lilly Company, GlaxoSmithKline Canada, Inc, Patheon Canada, Inc, Novex Pharma, and Agilent Technologies who have contributed to the preparation of this book. In addition, I want to acknowledge Herman Lam for the design of the front cover, which clearly depicts the cGMP requirements for data generation CHUNG CHOW CHAN. PH D

x PREFACE the pharmaceutical industry. It also provides an insight into quality systems that need to be built into the fundamental activities of the discovery and development processes. Chapters 2 to 5 provide guidance and share practical information for validation of common analytical methods (e.g., potency, related substances, and dissolution testing). Method validation for pharmaceutical excipients, heavy met￾als, and bioanalysis are discussed in Chapters 6 to 8. The instrument performance verification section of the book provides unbiased information on the principles involved in verifying the performance of instru￾ments that are used for the generation of reliable data in compliance with cGMPs. The reader is given different approaches to the successful verification of instru￾ment performance. The choice of which approach to implement is left to the reader based on the needs of the laboratory. Chapters 9 to 15 provide infor￾mation on common analytical instruments used in the development laboratory (e.g., HPLC, UV–Vis spectrophotometers, and pH meters). Chapter 13 provides a detailed discussion of the LC-MS system, which is fast becoming a standard analytical laboratory instrument. Since a great portion of analytical data from the drug development process comes from stability studies, Chapter 16 is included to provide guidance to ensure proper environmental chamber qualification. Computers have become a central part of the analytical laboratory. Therefore, we have dedicated the last two chapters to an introduction to this field of computer system and software validation. Chapter 17 guides quality assurance managers, lab managers, information technology personnel, and users of equipment, hard￾ware, and software through the entire qualification and validation process, from writing specifications and vendor qualification to installation and to both initial and ongoing operations. Chapter 18 is an in-depth discussion of the approaches to validation of Excel spreadsheets, one of the most commonly used computer programs for automatic or semiautomatic calculation and visualization of data. The authors of this book come from a broad cultural and geographical base of pharmaceutical companies, vendors and contract manufacturers and offer a broad perspective to the topics. I want to thank all the authors, co-editors, reviewers, and the management teams of Eli Lilly & Company, GlaxoSmithKline Canada, Inc., Patheon Canada, Inc., Novex Pharma, and Agilent Technologies who have contributed to the preparation of this book. In addition, I want to acknowledge Herman Lam for the design of the front cover, which clearly depicts the cGMP requirements for data generation. CHUNG CHOW CHAN, PH.D

OVERVIEW OF PHARMACEUTICAL PRODUCT DEVELOPMENT AND ITS ASSOCIATED QUALITY SYSTEM CHUNG CHOW CHAN PH. D ERIC JENSEN PH. D Eli Lilly& Company, Indianapolis 1.1 INTRODUCTION Pharmaceutical product development consists of a series of logical and system- atic processes. When successful, the final outcome is a commercially available dosage form. However, this process can become a long and complicated pro- cess if any of ps lose their focus. The industry has undergone many changes over the years to increase focus on efficiency and efficacy of the devel opment process. The overall cycle of pharmaceutical product development summarized in Figure 1. 1. The clinical study of drug development is the most obvious and best known to laypersons and scientists. However, many associated behind-the-scene activities are also actively pursued in a parallel and timely man ner to ensure the success of pharmaceutical product development. Clinical and commercial success cannot be achieved without successful completion of these other activities. It is important to note that the clinical phase boxes in Figure 1.1 may not be aligned exactly chronologically with other development activities Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow IsBN 0-471-25953.5 Copyright o 2004 John Wiley Sons, Inc

1 OVERVIEW OF PHARMACEUTICAL PRODUCT DEVELOPMENT AND ITS ASSOCIATED QUALITY SYSTEM CHUNG CHOW CHAN, PH.D. Eli Lilly Canada, Inc. ERIC JENSEN, PH.D. Eli Lilly & Company, Indianapolis 1.1 INTRODUCTION Pharmaceutical product development consists of a series of logical and system￾atic processes. When successful, the final outcome is a commercially available dosage form. However, this process can become a long and complicated pro￾cess if any of the steps lose their focus. The industry has undergone many changes over the years to increase focus on efficiency and efficacy of the devel￾opment process. The overall cycle of pharmaceutical product development is summarized in Figure 1.1. The clinical study of drug development is the most obvious and best known to laypersons and scientists. However, many associated behind-the-scene activities are also actively pursued in a parallel and timely man￾ner to ensure the success of pharmaceutical product development. Clinical and commercial success cannot be achieved without successful completion of these other activities. It is important to note that the clinical phase boxes in Figure 1.1 may not be aligned exactly chronologically with other development activities. Analytical Method Validation and Instrument Performance Verification, Edited by Chung Chow Chan, Herman Lam, Y. C. Lee, and Xue-Ming Zhang ISBN 0-471-25953-5 Copyright  2004 John Wiley & Sons, Inc. 1

PHARMACEUTICAL PRODUCT DEVELOPMENT AND QUALITY SYSTEM Discovery Product decision→ Phase→| Phase Il→| Phase Ill→ MArket 岩 心| formul Manufac validation alytical control method method method Figure 1. 1. Overview of the drug development process. istorically, the time period for pharmaceutical drug product development is usually on the order of 10 to 15 years. However, with the ever-increasing com- petition between pharmaceutical companies, it is of utmost important to reduce the time utilized to complete the development process In the discovery research phase of drug development, new compounds are created to meet targeted medical needs, hypotheses for model compounds are proposed, and various scientific leads are utilized to create and design new molecules. Thousands of molecules of similar structure are synthesized to develop a struc- ture-activity relationship(SAR) for the model. To reach this stage, large phar- maceutical companies rely on new technologies, such as combinatorial chemistry and high-throughput screening, which are cornerstones in drug discovery. The new technologies increase the choice of compounds that can be synthesized and screened.Various in vivo and in vitro models are used to determine the value of these new candidate compounds The sequencing of the complete human genome was completed in 2000 through the Human Genome Project, which was begun in 1995. Knowledge of the complete human genome will provide the basis for many possible targets for drug discovery through genomics, proteonomics, and bioinformatics 1. 1.2 Preclinical phase The most promising drug candidates would be worthless if they could not be devel- oped, marketed, or manufactured New therapeutic drugs from drug discovery wil

2 PHARMACEUTICAL PRODUCT DEVELOPMENT AND QUALITY SYSTEM Product decision Phase I Phase II Phase III Define formulation/ synthetic route Definitive stability manufac￾ture Manufacture process validation Develop early analytical method Support early development formulation/ synthesis Develop final method Final analytical method Optimize formula￾tion/ synthesis Quality control lab Manufac￾turing Market Discovery research Figure 1.1. Overview of the drug development process. Historically, the time period for pharmaceutical drug product development is usually on the order of 10 to 15 years. However, with the ever-increasing com￾petition between pharmaceutical companies, it is of utmost important to reduce the time utilized to complete the development process. 1.1.1 Discovery Research In the discovery research phase of drug development, new compounds are created to meet targeted medical needs, hypotheses for model compounds are proposed, and various scientific leads are utilized to create and design new molecules. Thousands of molecules of similar structure are synthesized to develop a struc￾ture–activity relationship (SAR) for the model. To reach this stage, large phar￾maceutical companies rely on new technologies, such as combinatorial chemistry and high-throughput screening, which are cornerstones in drug discovery. The new technologies increase the choice of compounds that can be synthesized and screened. Various in vivo and in vitro models are used to determine the value of these new candidate compounds. The sequencing of the complete human genome was completed in 2000 through the Human Genome Project, which was begun in 1995. Knowledge of the complete human genome will provide the basis for many possible targets for drug discovery through genomics, proteonomics, and bioinformatics. 1.1.2 Preclinical Phase The most promising drug candidates would be worthless if they could not be devel￾oped, marketed, or manufactured. New therapeutic drugs from drug discovery will