John Cogan- COO, Qinecsa
Adverse event case processing is an enormous cost center and compliance issue for life sciences. As revenues stagnate for many pharma companies and profits come under new pressures, the expectation to improve its operational efficiency is substantial. But that cannot be at the expense of quality, or patient safety – the very purpose of pharmacovigilance. Organizations and their PV service providers have no choice but to take a smarter approach, underpinned by artificial intelligence and advanced automation. The cost and risk management benefits are clear, while the wider gains will include a more proactive PV operation, says Qinecsa’s John Cogan.
Adverse event (AE) case processing, the primary focus of pharmacovigilance (PV) functions, is a high-volume, resource-intensive activity. For the major pharma brands, where PV chiefly involves monitoring the safety of well-established blockbuster drugs, PV is seen largely as a compliance activity and substantial cost center. It ties up a great deal of scientists’ time and drains their enthusiasm, adding little perceived value beyond PV’s immediate purpose (fulfilling regulatory expectations, managing risk).
All of this is why the heavy lifting of PV is so often outsourced – to alleviate pressure, free up internal resources, and drive down cost. In the optimal scenario, the service provider will harness the latest technology to streamline processes, deploying advanced solutions that employ artificial intelligence to hone workflows - making it possible to handle ever higher volumes of AE cases for their budget. In an increasingly difficult market, such productivity gains are a chance to offset stagnant revenue performance and protect profits.
Back to Basics: Remembering Why We Do This
As brands diversify, adding more novel and ambitious therapy areas to their portfolios, another driver for sharper PV practices presents itself. New modalities and treatments with a higher-risk safety profile (e.g., new approaches to cancer, diabetes, and weight loss, and/ or degenerative diseases including Alzheimer’s) require additional vigilance and detection sensitivity.
Pharmacovigilance exists to minimize and prevent harm associated with a medicinal product, ensuring that target patients derive the fullest benefits. The World Health Organization defines pharmacovigilance as “the science and activities relating to the detection, assessment, understanding, and prevention of adverse effects or any other medicine/vaccine-related problem.”1
Amid the considerable potential of both established and ambitious new treatments is the chance that unforeseen side effects could emerge once used outside of a controlled environment. Optimized AE reporting is one of the best proactive protections against this, keeping patients safe as important new drugs move from the lab and clinical trials into the real world. (WHO estimates that adverse drug reactions account for 5% of hospital admissions globally, translating to millions of affected individuals annually.2)
There are numerous important new therapies and drug applications entering the market at the moment. These include glucagon-like peptide 1 (GLP-1) receptor agonist application for diabetes and weight management (take-up continues to rise sharply, and now the WHO plans to officially back the use of weight-loss drugs to treat obesity in adults3). Other examples include the use of messenger ribonucleic acid (mRNA) technology in approaches to cancer. Meanwhile, pioneering COVID-19 vaccines - developed at speed five years ago, subject to accelerated approvals, and given to huge swaths of the global population (tens of billions of doses have been administered4) - still need to be closely monitored for potential AEs that may emerge over time.
Meticulous monitoring and continuous analysis of safety information will be critical in surfacing any such issues. Presenting greater potential for unknown impact over time, surveillance of new drugs (or new applications of existing drugs) requires both broad parameters and scrutiny. It must be possible to swiftly pick up possible new safety signals, identify emerging patterns, and trigger a response in near real-time. In the context of trailblazing products, the implications from findings are starker: beyond the core remit of meeting regulatory expectations, PV is key to staying ahead of emerging issues and proactively optimizing patient safety. (In the case of weight-loss injections, in England, reports of pancreatic issues have triggered a new study into this and other potential side effects of the treatments 5)
AI’s Promise
As the pharma industry grapples with all of this additional pressure on PV (which further includes difficulty attracting and retaining optimal skills and experience), AI is starting to make its mark as a mature and viable solution to high-volume AE case processing. It is this convergence of conditions that is triggering an important inflexion point in PV’s longer-term role and pathway.
AI solutions specifically designed for PV are entering the market in earnest now, and top-tier pharma organizations are testing them with encouraging results. Current solutions have been shown to reliably handle large volumes of data, extract key information from various sources, and even detect subtle patterns that might be missed by human reviewers. (Implementing AI in PV has improved the detection of potential drug risks by over 25% since its introduction, according to the FDA.6)
Given all of the converging pressures on PV, pharma organizations have accepted that they have no real choice but to embrace next-generation, AI-driven process automation. Especially given that the technology’s accuracy and efficiency improve exponentially with exposure and training. Inspired by the potential, PV leaders are keenly tracking AI developments specific to their field at conferences, in forums, and in their general networking.
Embracing AI in practice isn’t quite so easy, however. Much depends on the respective company’s current PV ecosystem, the volumes of work it underpins, and the existing technology infrastructure. PV technology vendors might be selling the latest functionality and promising the earth in terms of the efficiencies it represents, but internal teams and their PV service providers must determine how well this will fit with what they have and how they work now. They also need to understand how this will translate into tangible benefits, including cost reduction and improved productivity.
Determining the Best Way Forward
Unfortunately, there isn’t a one-size-fits-all route to AI adoption and process transformation within PV. Large pharma organizations, processing many hundreds of thousands of spontaneous AE cases each year across extensive and diverse portfolios, stand to gain most from intelligent automation and letting technology take the strain – whether they do this themselves, or via a service partner.
Yet, even here, it isn’t just the scale of the operation that will determine the optimum path to AI use. The prospect of turning off legacy safety databases can be daunting; in which case, embracing AI may need to involve sophisticated workarounds and wrap-around software. This is likely to involve giving users a single, simple, intuitive interface or portal, and providing a layer where the ‘magic’ happens while preserving the core safety database’s integrity and investment.
Mid-size pharma organizations - with more modest portfolios yet concerns about resources, PV scalability, and responsiveness - may want to progress to a digital-first capability yet be unsure of the most cost-effective way to go about this. To prepare the ground, their best bet may be to start with the inbound AE case capture process, ensuring that this is digitized across all supported channels. The more that cases can be captured digitally at source, the greater the potential impact of AI in their assessment and processing. As well as creating a substantial efficiency gain in its own right, by doing away with manual data entry, it also sets up the PV operation for all of the downstream processing to be digital.
Devising Next Steps
As always, the priority for any organization should be to make decent progress, whichever route they choose. Expected cost efficiencies will help cement the business case, but it’s important not to overlook the strategic benefits on offer. As more pharma companies look to novel and advanced products and therapies to bolster their revenue and profit performance, and drive new value for patients, parallel advances in technology can help not only to streamline the pharmacovigilance function, but also to deliver in important new ways.
PV’s profile as an operation needs to evolve. Already, the function is becoming more strategically important to companies if all the enablers are there. It is poised to become a key partner in drug development and product lifecycle management, for instance, a role that would involve integrating risk management and leveraging technology to improve processes and decision-making. The building blocks companies put in place now - harnessing advanced technologies to sharpen everyday practices or establishing an optimal service strategy with a partner – will help underpin that future.
References
- https://www.who.int/teams/regulation-prequalification/regulation-and-safety/ pharmacovigilance
- Pharmacovigilance market, Market Research Future, June 2025: https://www. marketresearchfuture.com/reports/pharmacovigilance-market-8451
- WHO to back use of weight-loss drugs for adults globally, raises cost issue, Reuters, May 2025: https://www.reuters.com/business/healthcare-pharmaceuticals/ who-set-back-use-weight-loss-drugs-adults-globally-raises-cost-issue-2025-05-01/
- World Health Organization COVID dashboard: https://data.who.int/dashboards/covid19/ vaccines
- Weight loss jab study begins after reports of pancreas issues, BBC News, June 2025: https:// www.bbc.co.uk/news/articles/c4ged0r1n3wo
- Pharmacovigilance market, Market Research Future, June 2025: https://www. marketresearchfuture.com/reports/pharmacovigilance-market-8451
John Cogan, COO of Qinecsa, is a life sciences industry veteran with over 30 years’ experience in transforming strategy, organizations, processes, and systems across R&D. www.qinecsa.com