Leveraging technology to transform patient safety
The challenges of maintaining complex pharmacovigilance (PV) systems in a global, ever-evolving regulatory environment are increasing daily. With growing public awareness, social media connectivity and media scrutiny, pharmaceutical companies need to manage PV activities diligently. Cost-reduction pressures on one hand and the challenges of hiring safety talent, on the other hand, require us to rethink traditional PV strategies. While technology solutions such as safety databases are already vital to pharmaceutical safety operations, applying innovative PV automation tools such as artificial intelligence (AI) is now key to success.
The regulatory environment
Regulatory authorities are already using modern technologies to collect and evaluate adverse events (AE) for therapies. The U.S. FDA Sentinel system is an electronic system used to monitor the medical safety of products on the market, complementing the FDA Adverse Event Reporting System (FAERS). The European Medicines Agency (EMA) continuously monitors adverse drug reaction (ADR) data through the EudraVigilance database. Another initiative is the WEB-RADR (Recognizing Adverse Drug Reactions), an EU-wide mobile phone app enabling users to report ADRs directly to their national competent authority (NCA).
The power of technology
Many of the issues surrounding PV systems are not IT-related, but rather inefficiencies in the processes or people managing the systems. To ensure optimal and proactive PV, the industry needs process improvements across the safety and risk management continuum; this includes solutions to receive and manage data from global sources while delivering automation efficiencies. The first step towards PV transformation is process mapping to drive improvements, making end-to-end safety processes leaner and eliminating redundancies.

Achieving full PV transformation involves multiple levels of automation. Basic automation of a process workflow involves tracking and monitoring tasks with continuous metrics collection. Robotic process automation (RPA) helps reduce manual tasks and results in automatic entry, processing and analysis in a safety database. Cognitive automation leverages natural language processing (NLP) to help humans make decisions and is often combined with RPA. Cognitive computing involves human interaction to provide the required outcome, with humans driving final decisions, whereas AI involves very minimal or no human interaction.
Machine learning (ML), a subset of AI, enables data scientists and analysts to construct algorithms that can learn from and make predictions based on data. These algorithms are trained to spot patterns in large amounts of data, improving over time. Deep learning takes this idea further, processing information in layers where the result/output from one layer becomes the input for the next one.
Automation holds the promise of multiple benefits:
- Nearly 100% regulatory compliance due to faster turnaround, improved quality and accuracy
- Expected efficiency gains of 20-50% through standardized inputs, automated case intake and processing plus enhanced productivity
Strategies for today and the future
Three critical areas of safety can be transformed through the effective use of technology:
- Standardization and automation of PV processes and safety data management improve efficiencies, quality and compliance.
- Proactive PV identifies and predicts emerging safety signals through data mining techniques.
- Advanced cognitive solutions extract, code and process AE data while AI enables clear views of safety issues, providing transparency to build trust.
A roadmap for success
Strong technical and PV knowledge is needed to navigate the highly regulated space while delivering comprehensive, end-to-end PV automation solutions. Pharmaceutical companies must begin by defining a clear vision, building strategies and initiatives with specified milestones and selecting a strong partner with a proven track record in PV delivery, safety technology and regulatory reporting.
Leveraging technologies – including cloud-based solutions, mobile applications and technology for big data analytics – will help companies move toward end-to-end automation across the PV spectrum. Embracing advanced technology solutions and next-generation automation will position companies to meet the PV challenges of the future and stay ahead of the curve.
For more information on how automation can help transform your PV operations click here.