Validation Of Computerized Systems Research Articles

Simple Spectrometer System, Simple Validation?

Computerized System Validation (CSV) is usually associated with great mountains of paper (GMP). Why should this be the case? Ask yourself, am I lazy? Why write multiple documents if only one is required to validate a spectrometer with a simple intended use? Interested? Read on…

A quality management system aiming to ensure regulatory-grade data quality in a glaucoma registry.

Disease/patient registries are underutilized despite their multiple advantages over clinical trials in the clinical evaluation of drugs, such as the capacity for long-term curation, provision of patient outcome data in routine clinical practice, and provision of benchmark data for comparison. Ensuring the fit-for-purpose quality of data generated from such registries is important to informing regulatory decision making. Here, we report the construction of a quality management system aiming to ensure regulatory-grade data quality for a registry of Japanese patients with glaucoma to evaluate long-term patient outcomes. The quality management system was established by reference to the risk-based approach in the ICH-E6 (R2) recommendations. The following three-component approach was taken: establishment of governance, computerized system validation (CSV), and implementation of risk assessment and control. Compliance of the system with the recommendations of regulatory guidelines relevant to use of the registry was assessed. Governance by academic collaboration was established. This was followed by the development of a total of 15 standard operating procedures, including CSV, data management, monitoring, audit, and management of imaging data. The data management system was constructed based on a data management plan, which specified data/paper flow and data management procedures. The electronic data capture (EDC) system was audited by an external vendor, and configured and validated using the V-model framework as recommended in the GAMP5 guideline. Informed consent, eligibility assessment and major ophthalmology measurements were determined as Critical to Quality (CTQ) factors. A total of 22 risk items were identified and classified into three categories, and operationalized in the form of a risk control plan, which included training sessions and risk-based monitoring. The glaucoma registry addressed most quality recommendations in official guidelines issued by multiple health authorities, although two recommendations were not met. We established and configured a quality management system for a glaucoma registry to ensure fit-for-purpose data quality for regulatory use, and to curate long-term follow-up data of glaucoma patients in a prospective manner.

CSA: Much Ado About Nothing?

Computerized system validation (CSV) in good practice (GxP)-regulated laboratories is alleged to take ages and generate piles of paper to keep inspectors and auditors quiet. To the rescue is the draft FDA guidance on computer software assurance (CSA). But...is this really the case?

Does CSA Mean “Complete Stupidity Assured?”

The U.S. Food and Drug Administration (FDA) has a new approach to computerized system validation (CSV) called computer system assurance (CSA). Without a draft guidance issued, are we entering an era of regulation by presentation and publication? As a result, does CSA risk becoming “complete stupidity assured?”

A Good Practice-Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study.

BackgroundWith the rapid increase in utilization of imaging endpoints in multicenter clinical trials, the amount of data and workflow complexity have also increased. A Clinical Trial Imaging Management System (CTIMS) is required to comprehensively support imaging processes in clinical trials. The US Food and Drug Administration (FDA) issued a guidance protocol in 2018 for appropriate use of medical imaging in accordance with many regulations including the Good Clinical Practice (GCP) guidelines. Existing research on CTIMS, however, has mainly focused on functions and structures of systems rather than regulation and compliance.ObjectiveWe aimed to develop a comprehensive CTIMS to meet the current regulatory guidelines and various required functions. We also aimed to perform computerized system validation focusing on the regulatory compliance of our CTIMS.MethodsKey regulatory requirements of CTIMS were extracted thorough review of many related regulations and guidelines including International Conference on Harmonization-GCP E6, FDA 21 Code of Federal Regulations parts 11 and 820, Good Automated Manufacturing Practice, and Clinical Data Interchange Standards Consortium. The system architecture was designed in accordance with these regulations by a multidisciplinary team including radiologists, engineers, clinical trial specialists, and regulatory medicine professionals. Computerized system validation of the developed CTIMS was performed internally and externally.ResultsOur CTIMS (AiCRO) was developed based on a two-layer design composed of the server system and the client system, which is efficient at meeting the regulatory and functional requirements. The server system manages system security, data archive, backup, and audit trail. The client system provides various functions including deidentification, image transfer, image viewer, image quality control, and electronic record. Computerized system validation was performed internally using a V-model and externally by a global quality assurance company to demonstrate that AiCRO meets all regulatory and functional requirements.ConclusionsWe developed a Good Practice–compliant CTIMS—AiCRO system—to manage large amounts of image data and complexity of imaging management processes in clinical trials. Our CTIMS adopts and adheres to all regulatory and functional requirements and has been thoroughly validated.

Cost-Effective and Business-Beneficial Computer Validation for Bioanalytical Laboratories

Computerized system validation is often viewed as a burden and a waste of time to meet regulatory requirements. This article presents a different approach by looking at validation in a bioanalytical laboratory from the business benefits that computer validation can bring. Ask yourself the question, have you ever bought a computerized system that did not meet your initial expectations? This article will look at understanding the process to be automated, the paper to be eliminated and the records to be signed to meet the requirements of the GLP or GCP and Part 11 regulations. This paper will only consider commercial nonconfigurable and configurable software such as plate readers and LC-MS/MS data systems rather than LIMS or custom applications. Two streamlined life cycle models are presented. The first one consists of a single document for validation of nonconfigurable software. The second is for configurable software and is a five-stage model that avoids the need to write functional and design specifications. Both models are aimed at managing the risk each type of software poses whist reducing the amount of documented evidence required for validation.

A Method of Retrospective Computerized System Validation for Drug Manufacturing Software Considering Modifications

A Method of Retrospective Computerized System Validation for Drug Manufacturing Software Considering Modifications

New current of Computerized System Validation

New current of Computerized System Validation