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22 Pharmaceutical Technology ® Quality and Regulatory Sourcebook March eBook 2023 PharmTech.com Qualit y Control Algorithms can analyze large amounts of data and iden- tify patterns that might not be immediately apparent to humans, helping to identify potential safety issues before a product reaches the market. Because labora- tories generate massive amounts of data, just finding those errors can take a lot of time, sometimes requiring days or weeks before the root cause is identified. That could have significant implications if a product was re- leased during that time, potentially causing the need for a recall or other costly remediations. Real-time error information. Many human errors are simply mistakes that technicians don't necessar- ily know they are making at the time. Currently, QC technicians rely heavily on oversight from other col- leagues physically present in the lab—an aspect that has been particularly challenging with the increase in hybrid and remote work during the pandemic. Coupled with high turnover rates and onboarding challenges in the current employment market, many pharmaceutical companies would benefit from AI al- gorithms that could report errors as they are made, giving the analyst a chance to learn from their mis- take, as well as take steps to fix the error immediately. Training. I ntel l igent i n for m at ics ca n prov ide user training to tutor new technicians as they are completing tasks. Training may include visual in- structions for completing tasks, as well as guided workf lows that would traditionally be the responsi- bility of a lab manager or supervisor. This capability could work in combination with health checks and real-time error information to get new users up to speed as quickly as possible. Audit trails. Intelligent informatics can provide support for the necessar y audit trails that include i n st a l lat ion, h a rdwa re mod i f icat ion s, sof t wa re modifications, and instrument events. Pharmaceu- tical companies face substantial financial impacts if they are unable to quickly provide regulators with the required data, including documented evidence of compliance. Outdated technolog y and insuf f i- cient support can put data and compliance at risk, resulting in disruption, unplanned downtime, and other consequences. Conclusion While the benefits are numerous, adoption of intelli- gent innovations in a laboratory setting can be chal- lenging due to the lack of familiarity with the tech- nology, as well as hesitancy to adopt new technologies, particularly in regulated environments like a pharma- ceutical QC laboratory. These innovations will need to be integrated with existing laboratory systems and processes, which can be time-consuming. Lab manag- ers and analysts may be cautious to change because they are comfortable with the status quo and hesitant to embrace new ideas or approaches, or because they do not fully understand the proposed change or its benefits. Barriers to change include factors such as SOPs, which are often written specifically to existing instruments and technologies and may require ex- tensive rewriting when upgrading to newer systems. Analysts may also be uncertain about the outcome of the change or how it will affect them personally. Many of these barriers can be overcome with change management, which identifies the need for change, assesses the impact, develops an execution plan, and ensures that the change is effectively and successfully implemented. Change management is particularly im- portant in the QC laboratory because it helps to ensure that changes are made in a controlled and systematic manner, minimizing the risk of errors or disruptions to laboratory processes. Effective change management requires the active participation of all stakeholders, including management, employees, and other stake- holders, to ensure that the change is fully understood and supported. It may also involve the development of new policies and procedures to guide the change pro- cess, as well as training and support to help employees adapt to the change. Overall, pharmaceutical companies are carefully considering the costs and benefits of intelligent infor- matics, and planning and implementing automated systems in a way that maximizes their benefits while minimizing disruption to business continuity. References 1. US Bureau of Labor Statistics. Life, Physical, and Socia l Science Occ upat ion s. w w w.bls.gov/ooh/ life-physical-and-social-science/home, Sep. 14, 2022 (accessed Feb. 20, 2023). 2. D u k a r t, H; La noue, L .; Rezende, M.; Rut ten, P. Emerging from Disruption: The Future of Pharma O p e r a t i o n s S t r a t e g y. M c K i n s e y & C o m p a n y, Oct. 10, 2022. 3. Dekker, S. Field Guide to Understanding Human Error. 3rd Ed; Ashgate, Farnham, UK; 2014. 4. Bodmann, K.; Reinhard, C.; Mödler, M.; Tinson, K.; Johnson, M. Lonza Error Prevention System (EPS)— Changing Human Performance in Pharmaceutical Operations. Chimia, 2016, 70 (9), 610–615. ■ Effective change management requires the active participation of all stakeholders.