Improvement Opportunities in Aggregate Reporting Process by Applying DataOps and AIOps Framework

Rajashekhar Jayasheela, Udit Mathur, Md Tauseef Raza

Abstract: The world of pharmacovigilance is at a pivotal turning point, with aggregate reporting no longer being a back-office compliance task but an essential driver of patient safety and regulatory precision. This article provides a layered exploration of how modern pharmacovigilance is evolving through intelligent integration of AI, automation, and data science. It is evident that emerging technologies-particularly when anchored by robust DataOps and AIOps frameworks-are not just streamlining reporting processes but fundamentally reshaping them. Companies are moving beyond manual, time-intensive systems toward agile platforms that support real-time analytics, predictive modeling, and tailored reporting across diverse regulatory landscapes. That said, adopting these innovations is not without challenges: data silos, legacy system integration, and regulatory variability remain persistent hurdles. Still, the narrative here is optimistic-through scalable infrastructure, process standardization, and intelligent automation, pharmaceutical organizations can now drive meaningful reductions in manual workload, improve accuracy, and achieve audit-readiness with consistency. The detailed case examples suggest that when operational frameworks align with cutting-edge technologies, they unlock measurable gains in speed, transparency, and compliance. Ultimately, this signals a shift toward a more proactive, resilient, and insight-driven pharmacovigilance future-one where patient safety is not just preserved but elevated through digital precision.

Keywords: pharmacovigilance automation, aggregate reporting, DataOps and AIOps, AI in safety monitoring, regulatory compliance

How to Cite?: Rajashekhar Jayasheela, Udit Mathur, Md Tauseef Raza, "Improvement Opportunities in Aggregate Reporting Process by Applying DataOps and AIOps Framework", Volume 14 Issue 4, April 2025, International Journal of Science and Research (IJSR), Pages: 1286-1290, https://www.ijsr.net/getabstract.php?paperid=SR25416132308, DOI: https://dx.doi.org/10.21275/SR25416132308