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16 BioPharm International Quality and Regulatory Sourcebook eBook March 2022 www.biopharminternational.com Development and manufacturing processes throughout drug produc- tion have become increasingly reliant on heavily automated equipment and computerized systems. As a result, an abundance of data will be created for a single project. Ensuring DI—mak ing sure data are complete, consistent, and accurate throughout its lifecycle—is essential to data quality and reliability. Using unreliable data in decision-making can negatively impact product quality and patient safety and ultimately lead to disastrous consequences. These include safety risks, recalls, delays, denied drug approvals, remediation costs, and dam- age to the company's reputation. THE NEED FOR REGULATIONS The potential risk to patients when u n rel iable d at a is us ed i n dec i- sion-making spurred the introduction of DI-related regulations in the early 1960s by FDA, as mentioned previously. Additional regulations were introduced in the following years as technological advancements progressed. In 1997, FDA published 21 CFR (Code of Federal Regulations) Part 11. This provides the regulatory require- ments surrounding electronic records and signat ures, including DI con- trols and computerized system val- idation. In 2011, the latest revision to EudraLex (the collection of rules and regulations governing medicinal products in the EU) Vol. 4, Annex 11 Computerised Systems was pub- lished as the European equivalent of 21 CFR Part 11. These are the major regulations currently governing elec- tronic records and DI controls that have helped shape various local regu- lations around the world. Nu merous reg u lator y g u ida nce from regulatory bodies, including the Medicines and Healthcare products Regulator y Agency, FDA, and the World Health Organization, have been produced over the years to reiterate and emphasize the message of the require- ments outlined in Part 11 and Annex 11. In particular, FDA and other reg- ulatory agencies have highlighted that complete, consistent, and accurate data need to be A LCOA—attributable, legible, contemporaneous, original, and accurate. The ALCOA+ princi- ples have an additional emphasis on ensuring data are complete, consistent, enduring, and available. The release of further g uidance has predominantly been prompted in response to def iciencies identif ied during regulatory inspections, espe- cially in the case of CDMOs. These deficiencies have included the absence of audit trails or inadequate control over laboratory computer systems (1). However, understanding and imple- menting the regulatory requirements of DI and the ALCOA+ principles in computerized systems remain a chal- lenge to many CDMOs today. DOWNFALLS OF A 'TECHNOLOGY-FIRST' APPROACH Despite the availability of advanced technologies, the number of obser- vations made regarding DI in docu- mentation and record management pr ac t ic e s du r i n g i ns p e c t ions h a s increased in recent years (2). In the span of f ive years 2014 –2018, 79% of FDA's globa l dr ug manufact ur- ing warning letters cited DI, and the number of these warning letters citing DI increased more than times (2). Technologies used to record, man- age, and store data that are well-im- plemented with robust DI controls can minimize human error and sim- plif y conformance w ith reg ulator y requirements and guidance. For exam- ple, validated laboratory information management system platforms can enhance the quality and efficiency of sample and associated data f low man- agement by harmonizing and stan- dardizing relevant workf lows, tests, and procedures. As a result, the use of digitized solutions, where processes are converted from paper-based to paperless, is often mistakenly equated with enhanced DI. T h e c o m m o n c a u s e o f m a n y challenges surrounding digitized solu- tion implementation by CDMOs is not the technology itself. Rather, it's a lack of a clear understanding and establ ishment of intended use by streamlined and optimized processes prior to their application. Quality and Regulatory Sourcebook Regulations: Data Integrity Technology is not the predominant challenge to achieving regulatory compliance, but the lack of critical thinking skills when designing a quality system. Technologies used to record, manage, and store data that are well- implemented with robust DI controls can minimize human error and simplify conformance with regulatory requirements.