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While there are many laws and regulations effecting the complex use and control of data in the Life Sciences industry, there are distinct patterns that emerge that transcend many of the laws and regulations. We believe that creating a data architecture that utilize patterns will provide significant benefits to your organization.  Although regulations tend to treat data as a risk, it is also your most important asset and these patterns can provide significant value to your organization. This blog provides a few data patterns that emerge from Life Sciences laws and regulations. Within Life Sciences, there are a myriad of regulatory requirements and standards that you will encounter. A few are listed below with a summary of their intent: 1. 21 CFR Part 11 (ALCOA+) – All data related to patient and product safety must always be in a state of control. 2. HIPAA – All patient data is protected

As the FDA finalizes and publishes the Computer Software Assurance (CSA) guidance later this year, companies that have not already started the transformation process to CSA can get started now – don’t wait! The medical device industry can benefit greatly by implementing CSA. In a recent European study1 on medical devices, AI application categories and types were researched and cited as producing data that can be collected and analyzed throughout the life cycle of the patient. Based on our understanding, the CSA guidance will, in many cases, require continuous validation of medical devices that use intelligent technology for patient and product safety to comply with the CSA guidance. The following includes examples of data collection and medical device scenarios that could benefit from the use of a “CSA approach” or “CSA methods”: Medical devices that collect clinical data Healthcare delivered remotely by medical personnel via txt, video, or phone Laboratory information

Overview This article takes a closer look at AI and intelligent technologies and what we can expect to tackle in 2022 and beyond. With current use cases across three categories: people, technology, and business, we discuss how AI and intelligent technologies are being used in the Life Sciences, identify some of the new concerns and challenges with disruptive technologies and risk management, and review a technology and generation timeline. AI and intelligent technologies are not to be feared and avoided; rather, they should be embraced and included in the disruptive technologies and internet of things (IoT) strategy and framework. You can read the full article here. About The Author: Kathleen Warner, Ph.D., VP of Consulting Services for RCM Technologies, Life Sciences, is an executive consultant with 25+ years of experience in information technology (IT) and the life sciences. She has served as a chief information officer, subject matter expert, and domain expert in regulated environments. As a management consultant, Warner has provided oversight for hundreds

In 2011, the Center for Devices and Radiological Health (CDRH) initiated the Case for Quality, which provided guidance on how software validation processes can be improved and streamlined for the medical device, pharmaceutical, and biotech industries. By refocusing on patient and product safety, quality assurance, and data integrity, some suggest that validation documentation can be reduced (between 20% and 40%, in my experience) by applying automated testing and deployment. The benefits are accurate code, faster development processes, and reduced validation documentation. This article is part one of a three-part series and continues the discussion on computer software assurance (CSA), introduces new technologies and methods to achieve continuous software development, provides insight into new standards (e.g., ISO 9001 and ISO 13485-2016), and concludes with a few good reasons to join the growing number of medical device, pharma, and biotech companies with software specialists (or companies that work with software development organizations) who are

The FDA regulation 21 CFR Part 11 in 1997 and the related guidance of 2003 paved the road to implementation of computer system validation (CSV) by life sciences companies. As pharmaceutical companies perfected their business processes and became more efficient in validating computer systems, the piles of documentation continued to grow without significant quality benefits. The focus was on speed, documentation accuracy and completeness, inspections, audits, and complying with the regulation. In 2011 the Center for Devices and Radiological Health (CDRH) initiated the Case for Quality, a new program that identified barriers in the current validation of software in medical devices guidance (released in 2002). Now, CDRH — in cooperation with the Center for Biologics Evaluation and Research (CBER) and the Center for Drug Evaluation and Research (CDER) — is preparing to release new guidance, Computer Software Assurance for Manufacturing, Operations and Quality Systems Software, in late 2020. This new guidance will provide