Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS

Richard C. Zink

Description

Improve efficiency while reducing costs in clinical trials with centralized monitoring techniques using JMP and SAS.
International guidelines recommend that clinical trial data should be actively reviewed or monitored; the well-being of trial participants and the validity and integrity of the final analysis results are at stake. Traditional interpretation of this guidance for pharmaceutical trials has led to extensive on-site monitoring, including 100% source data verification. On-site review is time consuming, expensive (estimated at up to a third of the cost of a clinical trial), prone to error, and limited in its ability to provide insight for data trends across time, patients, and clinical sites. In contrast, risk-based monitoring (RBM) makes use of central computerized review of clinical trial data and site metrics to determine if and when clinical sites should receive more extensive quality review or intervention.

Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS presents a practical implementation of methodologies within JMP Clinical for the centralized monitoring of clinical trials. Focused on intermediate users, this book describes analyses for RBM that incorporate and extend the recommendations of TransCelerate Biopharm Inc., methods to detect potential patient-or investigator misconduct, snapshot comparisons to more easily identify new or modified data, and other novel visual and analytical techniques to enhance safety and quality reviews. Further discussion highlights recent regulatory guidance documents on risk-based approaches, addresses the requirements for CDISC data, and describes methods to supplement analyses with data captured external to the study database.
Given the interactive, dynamic, and graphical nature of JMP Clinical, any individual from the clinical trial team - including clinicians, statisticians, data managers, programmers, regulatory associates, and monitors - can make use of this book and the numerous examples contained within to streamline, accelerate, and enrich their reviews of clinical trial data.
The analytical methods described in Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS enable the clinical trial team to take a proactive approach to data quality and safety to streamline clinical development activities and address shortcomings while the study is ongoing.
This book is part of the SAS Press

Sujets

• COMPUTERS
• Drug development
• Enterprise software
• Clinical trial
• Pharmaceutical drug
• General officer
• General

Informations

• Publié par: SAS Institute
• Date de parution: 01 juillet 2014
• Nombre de lectures: 0
• EAN13: 9781629592336
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

The correct bibliographic citation for this manual is as follows: Zink, Richard C. 2014. Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP® and SAS®. Cary, North Carolina: SAS Institute Inc.
Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP ® and SAS ®
Copyright © 2014, SAS Institute Inc., Cary, NC, USA
ISBN 978–1–62959–233–6
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About This Book

Purpose
There is increasing literature and discussion on the need of the pharmaceutical industry to improve efficiency and reduce costs through the use of centralized monitoring techniques. So-called risk-based monitoring (RBM) makes use of central computerized review of clinical trial data and site metrics to determine if and when clinical sites should receive more extensive quality review through on-site monitoring visits. There are many benefits to RBM beyond cost: Statistical and graphical checks can determine the presence of outliers or unusual patterns in the data, comparisons can be made between sites to assess performance and identify potentially fraudulent data or miscalibrated or faulty equipment, and issues can be identified and resolved while the trial is ongoing. As stated in the recent FDA guidance on the topic, RBM forces the sponsor to take a more proactive approach to quality through a well-defined protocol and sufficient training and communication, and by highlighting those data most important to patient safety and the integrity of the final study results. There is further emphasis on flexibility and adaptability: responding to issues as they arise to prevent further problems, with the willingness to put additional safeguards in place or refine procedures to address shortcomings as the trial is ongoing.
The primary goal of this book is to describe a practical implementation of JMP and SAS for the centralized monitoring of clinical trials. This includes RBM analyses by defining risk indicators and their corresponding thresholds, methods to identify patient- and investigator-perpetrated fraud, and other visual and analytical techniques to enhance safety and quality reviews. A second but equally important goal is to promote these methodologies and establish a dialogue with practitioners for continual improvement of analytical techniques and software. Controlling clinical trial costs through centralized monitoring is important, as these expenses are ultimately passed on to the consumer; reining in costs is one way to keep drugs affordable for the people who need them. Further, we’ll see repeatedly throughout the book that centralized monitoring meets the needs for Good Clinical Practice—protecting the well-being of trial participants, and maintaining a high level of data quality to ensure the validity and integrity of the final analysis results. While this book is written from the point of view of drug development, the methods described are equally applicable to clinical trials of biologics (i.e., vaccines) or medical devices.

Is This Book for You?
Any clinical trial is the result of the efforts of a diverse team. This team includes clinicians, statisticians, data managers, programmers, regulatory associates, and monitors, to name a few. Every team member has a role to play in the review of trial data, and each individual brings a unique skill set important for understanding patient safety, protocol adherence, or data insufficiencies that can affect the final analysis, clinical study report, and subsequent regulatory review and approval. Given the interactive, dynamic, and graphical nature of JMP Clinical, it is my sincere hope that any individual from the clinical trial team can make use of this book and the examples contained within to streamline, accelerate, and enrich their reviews of clinical trial data. Though JMP Clinical makes use of SAS, it is neither expected nor required that the user have any SAS programming experience.

Prerequisites
Users familiar with JMP can expect a similar experience with JMP Clinical; analyses and reports are available from a menu-driven, point-and-click interface. Basic knowledge of JMP is useful (though not required) and can be obtained through Tutorials in the Help menu, the PDF books Discovering JMP and Using JMP under Help > Books or by referring to JMP Essentials, Second Edition by Curt Hinrichs and Chuck Boiler. This book focuses heavily on the operational and data aspects of clinical trials. Familiarity in these areas will make for a more pleasant reading experience. Data standards from the Clinical Data Interchange Standards Consortium (CDISC) are a requirement to use JMP Clinical and are discussed throughout this book. Some familiarity with these standards is useful, though they are addressed at a basic level.

About the Examples
Software Used to Develop the Book's Content

JMP Clinical 5.0, the software version that is the focus of this book, is a combination product that includes JMP 11.1 and SAS 9.4 M1 for Base SAS, SAS/GRAPH , and SAS/ACCESS to PC files, and SAS analytics releases 12.3 for SAS/IML , SAS/STAT , and SAS/Genetics . Also included are macros written in SAS and the JMP Scripting Language (JSL) that generate the various analyses and reports that are specific to JMP Clinical.
The most straightforward answer, however, is simply JMP Clinical 5.0.
Example Code and Data
Data for the clinical trial of Nicardipine is included and shipped with JMP Clinical. Users should have immediate access to this data.
You can access additional supporting files for this book by linking to its author page at http://support.sas.com/publishing/authors. Select the name of the author. Then, look for the cover thumbnail of this book, and select Example Code and Data to display the SAS programs that are included in this book.
For an alphabetical listing of all books for which example code and data is available, see http://support.sas.com/bookcode. Select a title to display the book’s example code.
If you are unable to access the code through the Web site, send an e-mail to [e-mail].
Output and Graphics Used in This Book

All output was generated using JMP Clinical 5.0 and captured using FullShot 9.5 Professional.

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