How to future-proof your pharmacovigilance delivery model
Using artificial intelligence and smart machines for scalability and cost-effectiveness
White Paper
Feb 14, 2018

Pharmacovigilance is becoming ever more complex. With growing numbers of safety data sources and adverse event reports, there is a need to leverage new innovations to scale operations and maintain cost-effectiveness. IQVIA is leading the charge in leveraging artificial intelligence (AI) and smart machines in identifying, ingesting and reporting out safety signals in structured and unstructured data. This insight brief, authored by IQVIA experts, explains how pharmaceutical companies can leverage these innovative approaches and address the growing volumes of adverse event data without sacrificing quality or compliance.

Pharmacovigilance is becoming ever more complex. With growing numbers of safety data sources and adverse event reports, there is a need to leverage new innovations to scale operations and maintain cost-effectiveness. IQVIA is leading the charge in leveraging artificial intelligence (AI) and smart machines in identifying, ingesting and reporting out safety signals in structured and unstructured data. This insight brief, authored by IQVIA experts, explains how pharmaceutical companies can leverage these innovative approaches and address the growing volumes of adverse event data without sacrificing quality or compliance.

Introduction: Going beyond manual processes

Pharmacovigilance – the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem1 – faces an increasingly complex environment. With increasing numbers of safety data sources and adverse event (AE) reports, drug developers need to move beyond manual processes and find more efficient, cost-saving measures to manage pharmacovigilance. IQVIA sees six primary contributors to this increasing complexity.

  1. Disparate, emerging global regulations, and inconsistent adoption of international systems such as International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guidelines
  2. Increased emphasis on risk assessment, with module 9 of the EU Good Pharmacovigilance Practices (GVP) coming into effect late in 2017
  3. Increasing volume and complexity of AE data
  4. Increasing unstructured data from sources such as social media, requiring additional effort to extract safety information
  5. Transactional cost containment efforts inside pharmaceutical companies, which may jeopardize quality and compliance
  6. External pricing pressure from payers and government – coupled with increased regulatory demands for proof of safety

 

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