With the continued implementation of artificial intelligence (AI) and automated systems into the clinical process, automated data management systems have helped to alleviate manual burdens on safety teams to focus on more critical tasks. The goal at present is to enhance data quality, eliminate bias, and maintain compliance with regulatory requirements. Trends indicate a movement toward cognitive automation, including automating the case processing and signaling elements to improve cost efficiencies and capture larger volumes of meaningful data.
Global Challenges for Pharmacovigilance Teams
Industry challenges are catalyzing the implementation of automation in pharmacovigilance (PV) and safety processes. With a global shift in healthcare, safety reporting is growing more complex due to increasing volumes of adverse effects (AE) reporting across different channels and continually evolving regulatory requirements. Key concerns for pharmaceutical companies include triaging, analyzing, and reporting on dense volumes of data as well as time constraints and concerns surrounding regulatory compliance. This places immense pressure on pharmaceutical companies to assess their PV and safety workflows, prompting an investment into automation and centralization to optimize their PV processes.
Outcomes of Automating the Pharmacovigilance Process
1. Accelerated Reporting Timelines
Automated Case Triage, Analysis, and Reporting
Automated case intake workflows provide your teams with real-time notifications to seamlessly and appropriately triage cases. Natural language processing streamlines data extraction, while AI, such as optical character recognition (OCR), converts unstructured content via Docx, XML, PDFs, etc., to prioritize cases based on severity and relevance. This process reduces cycle times for case processing, affording more resources to assess the accuracy and quality of reporting.
In lieu of manual safety case monitoring, automated workflows are designed to identify relevant articles and translate them into local languages while highlighting and flagging any relevant information. Through recent automation programs, evidence shows pharmaceutical organizations could reduce the time to identify relevant articles by 85%.
Centralized Team Communication
Onboarding your safety teams into a centralized safety database and workflow provides elevated insight and visibility for all team members into each stage of the safety process. This facilitates effective lines of communication between safety teams, sponsors, CROs, etc., and ensures that notifications are received and managed accordingly by relevant personnel.
Expedited AI Translation and Redaction
Integrating safety-specific AI engines alongside human post-editors into your centralized PV solution can cut down translation timelines and accelerate time to regulatory submissions. AI automation technology also enables advanced OCR for handling PDF content, real-time translation for case triage, accelerated translation leveraging machine translation (MT) post-editing workflows, and automated literature monitoring.
2. Enhanced Patient Safety
Local Literature Monitoring
Centralized content solutions, including AI and MT processes, empower pharma companies to mitigate compliance risks and customize their workflows depending on local marketing requirements. This means all publications can be crawled, either at the local or international level, in any language, and reported back into a database for human review. By accurately capturing and centralizing specific safety information at all levels, you are assured of enhanced data quality and patient feedback while reducing manual effort.
Media Monitoring
As a source of potentially valid individual case safety reports (ICSRs), various media platforms, including social media, have become a channel through which pharmaceutical organizations can monitor reports of suspected AEs. With high volumes of data to filter through and analyze, centralizing your media monitoring solutions enables teams to establish customized workflows from case triage to reporting, leveraging AI to reduce manual revision of extracted data. Additionally, with specialized tools, metrics and processes, micro-task management, and quality assurance features, teams can rapidly create high-quality labeled datasets to optimize media monitoring.
This AI-based approach can accelerate the time to identify relevant safety cases by up to 90% and provide the ability to better understand and develop products that meet patients’ needs. Ultimately, this empowers patient-centric focus due to perceived patient behaviors and feedback.
3. Reduced Timelines and Cost Reduced Processing Time Through Workflow Automation
AI enablement and automation in PV processes facilitate high volumes of data processing to reduce manual burdens. Pharma organizations have an opportunity to leverage AI engines to automate their workflows and immediately route priority content for human review. In addition to integration with backend safety databases, teams can accelerate their reporting timelines by up to 50%, reducing the manual effort required for efficient and compliant case processing.
Cost Savings
In addition to accelerating the reporting process, pharma organizations can slash costs by leveraging robust automated workflows. As well as reducing the number of FTEs required for a typical case processing load, implementing automation tools introduces scalability, maintaining steady cost savings per case processing regardless of volume.
Our PV and Safety Solutions
If you’d like to learn more about our centralization technology platform for pharmacovigilance and safety, contact us today!