Harness the power of global human expertise combined with automation, artificial intelligence (AI) and machine learning (ML) to design, build and execute end-to-end safety solutions.
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn more"We strive to help improve outcomes and create a healthier, more sustainable world for people everywhere.
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SEE LATEST REPORTSBy making intelligent connections between your needs, our capabilities, and the healthcare ecosystem, we can help you be more agile, accelerate results, and improve patient outcomes.
LEARN MOREBuilding on a rich history of developing AI for healthcare, IQVIA AI connects the right data, technology, and expertise to address the unique needs of healthcare. It's what we call Healthcare-grade AI.
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VIEW ROLESAs a leader in enhancing pharmacovigilance efficiencies through AI/ML-enhanced safety services, IQVIA is always at the forefront of leveraging cutting-edge methodologies for clinical research.
In line with this commitment, we are pleased to share our latest contribution to the field: a chapter titled “Causality Assessment in Pharmacovigilance,” co-authored by IQVIA’s Anand Harugeri M. Pharm, Ph.D., in the textbook “Principles and Practice of Pharmacovigilance and Drug Safety,” published by Springer Nature.
This comprehensive textbook, containing 23 chapters, offers a broad perspective on pharmacovigilance and drug safety, making it an invaluable resource for students and professionals in clinical, industry, and regulatory settings. Each chapter is designed as a self-contained learning module, complete with learning objectives, key points, and worked cases.
The chapter on Causality Assessment in Pharmacovigilance provides insights from clinical, industry, and regulatory perspectives, including the application of artificial intelligence and machine learning in causality assessment. This chapter is particularly significant as it addresses the complex process of establishing a causal relationship between a suspected drug and an adverse event, considering both patient- and medication-related factors.
The chapter highlights three broad approaches to causality assessment, emphasizing the importance of these methods in benefit–harm analysis, identification of new adverse drug reactions, and regulatory decision-making. The continuous nature of causality assessment and its applications across various fields, including academic research, clinical practice, and regulatory activity, underscore its critical role in improving patient safety.
For more detailed insights, you can read the chapter abstract here and purchase the full textbook here.
At IQVIA, we remain dedicated to advancing the field of pharmacovigilance and ensuring the highest standards of drug safety through continuous research and innovation.
Harness the power of global human expertise combined with automation, artificial intelligence (AI) and machine learning (ML) to design, build and execute end-to-end safety solutions.
End-to-end safety-focused local Qualified Person for Pharmacovigilance (QPPV) services and latest PV/MI technologies, ensure global consistency at a local country level and compliance with all local safety requirements. Expand your global pharmacovigilance, Medical Information, and safety capabilities with confidence - and without additional capital investment.