How a Data-Driven Quality Management System Can Manage Compliance Risk in Clinical Trials
- PDF / 18,085,309 Bytes
- 15 Pages / 612 x 792 pts (letter) Page_size
- 0 Downloads / 219 Views
Sina D i d , MS Associate Director. Quality Monitoring, Global Clinical Development. Tibotec lnc. Stef Janssens, MS Program Manager, Information Technology Department, Tibotec BVBA Stefan Van Yper, MsBE Functional Genomics, Pharmaceutical Research and Development. Johnson S.Johnson Jon Van Pariis, PLD, MBA Senior Director, Quality Monitoring. Global Clinical Development. Tibotec BVBA
Key Words Quality management system; Risk management; GCP; Compliance; Text mining; Key performance indicator Correspondence Address Sina Djali (email: sdjaliQ its.jnj.com).
How a Data-Driven Quality Management System Can Manage Compliance Risk in Clinical Trials A majority of data presented to global regulatory agencies dtuing the approval stage of an investigational product is cdlected during its clinical devdopment. Any concern or doubt about the intcgn'ty or quality of clinical data, compliance with GCP, or ethical standards during regulatory review can l a d to castly delays in the granting of a mmketing authm'zation. This risk can be minimized if accurate metrics are used to continually monitor the quality of the contributing research operations. As highZy cost-effedivet d s , metrics can be
INTRODUCTION Clinical trial conduct is regulated by national legislation and international guidelines concerning the scientific merits of a trial, the accuracy and integrity of data, the handling of an investigational product, and ethical treatment of the study subjects. To determine whether an investigational product can be granted a marketing authorization, an application is subject to stringent regulatory review. This review focuses on the scientific merit of the application (the efficacy and safety of the new product) and the methods of collection, as well as the quality of the data. To determine the validity and quality of submission data, most regulatory agencies may also conduct inspections at investigator sites and at sponsors' premises. Depending on the number and severity of infractions noted, the outcome of such inspections can vary. In the most severe cases, the validity of the data from investigator sites or even the entire study may be questioned and excluded from the final analysis, impacting the outcome of the study (eg, claim of superiority), developmental timelines, and future income for the sponsor. Rejection of an application based on procedural and quality issues, rather than a lack of scientific and medical merits, can damage the reputation of a company's research and development divi-
used to monitor operations throughout this phase of development. With continuous moniton'ng, proactive measures can be implemented to prevent issues @m escalatinginto regulatory concerns. This article describes the devdopment of a quality management system based on a data- and metrics-driven compliance strategy. Combined with an dedronic infaation management system, the aim of this system is to monitor and manage cost and timdines while ensuring the quality of clinical research operations.
sion, leading to more frequent inspections an
Data Loading...
