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10 Pharmaceutical Technology ® Quality and Regulatory Sourcebook March eBook 2023 PharmTech.com Pharmacovigil ance companies no longer able to simply outsource their problems and cost increases away. Companies world- wide are looking for new ways to optimize PV pro- cesses and achieve scalability and efficiency through innovation. Knowing this, where should companies begin and achieve the journey of rolling out automa- tion in their PV processes? What does success look like, and what factors must be considered from start- ing the business case to measuring the outputs and, finally, achieving a successful outcome? How automation in PV environments work Automation includes ever y thing from basic, rule- ba sed processes to more adva nced le vel s of A I, machine learning (ML), deep learning, and nat u- ra l lang uage processing. In shor t, it is cogn itive computing, and it is changing PV as the industr y knows it. This form of "intelligent" automation en- ables predictive analysis and the capture and transla- tion of adverse event (AE) data to determine significant safety trends. It also gives PV professionals a stronger abi lit y to manage f ut ure AEs and a bet ter under- standing of safety issues. An advanced PV platform automates intake via web and mobile apps, sending results directly to the safet y system. It contains sophisticated AE track- ing tools that analyze both structured and unstruc- tured data in real time. The data are gleaned from multiple channels, including social media and chat- bots. PV quer y tools can automate the completion of case management documentation and repor ts, while natural language processing (NLP) tools an- alyze complex narratives, including patient charts, social media posts, articles, and other unstructured data. Analytics tools identif y safety trends across populations to educate hea lt hcare professiona ls, regulators, and payers. Factors to consider in adopting automation Orga n i z at ion s a re look i ng for a s a fe t y s u r vei l- lance strateg y to achieve transformation without disrupting compliance. For companies about to em- bark on their PV journey, factors to consider include the ease of deployment, the use of technology, the value of that deployment, and the risk. For exam- ple, some of the challenges involved in this process include t he avai labi lit y of data, t he resources to oversee the transformation project, the impact on current operations, and the changes it will have on company culture. When organizations implement advanced PV plat- forms successfully, they can generate far more value from PV tasks than was previously possible. Solutions conduct deep analyses of integrated data sets to iden- tify meaningful safety trends, resulting in reduced er- rors related to manual data entry, strict patient data privacy controls, and minimized pharmacovigilance risks to the business. Safety surveillance automation There are actions companies need to take at an en- terprise level to be successful and accelerate their journey to automation. It is not unusual for compa- nies to set unrealistic expectations around AI, choose the wrong vendors, launch projects without linking them to measurable performance outcomes, and fail to support change management initiatives. While these are common mistakes on the path to PV automation, they can be avoided by utilizing a tool that can help benchmark the automation adoption process and its results, such as IQVIA's Safety Sur- veillance Automation Maturity Matrix (1). The tool wa lks users through the four phases required to achieve automation and become an automation-first organization. It outlines specific criteria for progress, giving decision-makers clear guidance on how to vet their readiness for automation, choose the best pilot projects, and identify potential obstacles. The phases ensure companies stay on a consistent path, continu- ously monitor benefits, and avoid pursuing projects that will not deliver value. Phase 1: reaching readiness T h is f i rst phase to reach automat ion focuses on education about current technology and what it can achieve. Companies can take steps to prepare the orga n izat ion for t ra nsfor mat ion, such as h i r i ng people who understand the technology, consulting multiple AI vendors to explore a diverse range of solutions, and finding partners who align with their culture and technology needs. Investing time toward attending demos can help an organization determine whether a prospective solution could be viable. Defining the business case for their move to automation requires determining use cases and setting achievable targets. The tech- nology is not as critical a factor as the benefits it can achieve, and unless those align with the business case, the solution chosen will not be appropriate. When these steps have been completed, companies are ready to engage with vendors who will validate their ideas and targets. They can then embark on a request for proposal (RFP) process and select a vendor. Quality vendors will raise questions to help define achievable targets and work in unison with the com- pany to develop a request for quotation (RFQ). Phase 2: investment initiatives This phase of the process contains no shortcuts. Com- panies looking to automate PV will have to invest in data, regardless of the technology they choose. Most data vendors will not be able to supply data in the