Advances in Pharmacology and Pharmacy Vol. 14(2), pp. 214 - 222
DOI: 10.13189/app.2026.140208
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From Manual to Automated: A Technological Advancement in Adverse Drug Reaction Causality Assessment for Pharmacovigilance

Mandati Santhosh Reddy ^1,*, Shweta A. Redekar ¹, M. S. Ganachari ¹, Pradnya Rajmane ¹, Sachin Vastrad ^2
1 Department of Pharmacy Practice, KLE College of Pharmacy, Belagavi-590010, Karnataka, India
² KLE Academy of Higher Education & Research, Belagavi, Karnataka, India

ABSTRACT

Pharmacovigilance involves detecting, assessing, understanding, and preventing adverse drug reactions (ADRs). Causality assessment, crucial in this process, determines the likelihood of a drug causing an adverse event (AE), influencing clinical decisions. The WHO-UMC system is the most widely used causality assessment tool. Automated methods enhance efficiency and accuracy but require high-quality data and expert validation. The objectives of the study were to develop and validate an automated ADR causality assessment algorithm and improve pharmacovigilance by reducing manual workload and enhancing data accuracy. In 2024, web-based software was developed to automate ADR causality assessment using the WHO-UMC system. It recorded patient data, temporal relationships, and dechallenge/rechallenge outcomes. The database included user roles, ADR assessments, and acknowledgment tracking to enhance pharmacovigilance training. Pharmacists, the largest participant group, played a key role in ADR assessment due to their pharmacological expertise. Nurses, as frontline caregivers, provided insights into real-time usability, while doctors, though fewer, evaluated clinical relevance. The tool received positive feedback for its intuitive interface, with a mean System Usability Scale (SUS). It achieved 90% concordance with expert assessments, demonstrating high validity. Sensitivity (92%), specificity (88%), and Positive Predictive Value (91%) confirmed accuracy. Automation significantly reduced assessment time from 11 to 3 minutes. The automated ADR assessment tool showed strong usability, validity, and time-saving benefits.

KEYWORDS
Pharmacovigilance, Causality Assessment, Adverse Drug Reactions (ADRs), WHO-UMC Method, Automation

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Mandati Santhosh Reddy , Shweta A. Redekar , M. S. Ganachari , Pradnya Rajmane , Sachin Vastrad , "From Manual to Automated: A Technological Advancement in Adverse Drug Reaction Causality Assessment for Pharmacovigilance," Advances in Pharmacology and Pharmacy, Vol. 14, No. 2, pp. 214 - 222, 2026. DOI: 10.13189/app.2026.140208.

(b). APA Format:
Mandati Santhosh Reddy , Shweta A. Redekar , M. S. Ganachari , Pradnya Rajmane , Sachin Vastrad (2026). From Manual to Automated: A Technological Advancement in Adverse Drug Reaction Causality Assessment for Pharmacovigilance. Advances in Pharmacology and Pharmacy, 14(2), 214 - 222. DOI: 10.13189/app.2026.140208.