The healthcare industry is no stranger to workforce shortages, and the pharmaceutical industry may be next to experience disruptions brought on by labor challenges. According to the U.S. Bureau of Labor Statistics, it is estimated that occupations across life, physical and social sciences are expected to grow 7% by 2028. However, statistics also indicate that about 136,800 openings in these fields will remain unfilled annually through 2032, as employment growth and worker resignations are expected to increase. This loss of labor and expertise will significantly impact the pharmacovigilance (PV) space – especially as the field traditionally incorporates many manual processes to facilitate regulatory compliance and ensure patient safety. Life sciences companies will need to navigate the anticipated workforce shortage in the PV sector, including monitoring substantial amounts of data for potential drug adverse events (AEs). One proposed solution to the projected labor shortage in PV and drug safety is digital transformation through automation.
The Challenging PV Landscape
The complexity and volume of data increase with the intake of information from a variety of sources around the globe. Patients and consumers now represent the majority of those reporting potential AEs, with outlets such as social media providing new paths for even more complex reporting. This increase in access to data creates a need for more experts who can review and evaluate reports as well as stay up to date with ever-shifting drug safety regulations. Without these industry experts, there are a plethora of consequences. The workforce shortage may negatively impact the PV and drug safety processes; potential AEs could be overlooked, resulting in missed signals, leading to patient harm or even possible fatalities.
Automation to the Rescue
Pharmaceutical companies may struggle to manage the reduction of teams and the increase in data complexity. The answer to this challenge is to turn to automation. Major waves of digital transformation have resulted in artificial intelligence (AI) and machine learning (ML), which are excellent resources to review and manage potential AEs. Automation provides benefits at many stages to ease the load for pharmacovigilance teams. This technology captures, translates and analyzes AE data from different channels to identify safety trends. These stages include AE detection, processing and reporting and involve real-time signal detection, case ingestion, case validation, case collection, literature searches, full data entry, medical assessment and case follow-up.
Other forms of automation, such as conversational AI, AI-based search engines and natural language processing (NLP) can be combined to increase the efficiency of the drug safety process. Conversational AI can detect and report AEs via multi-channel text and/or voice-based conversations. AI search engines can detect potential AEs across large and diverse datasets that may otherwise go undetected if manually reviewed. When teams are short-staffed, NLP technologies provide effective handling of large volumes of data, allowing for real-time critical AE alerts, providing much needed efficiency to the PV process. The benefits of automation are exponential, and as technology continues to advance, opportunities for automation to assist in the pharmacovigilance process will expand, transferring the weight away from PV teams and shifting it to technology.
A Complement, not a Supplement
It is important to note that automation should be a complement to human review. Not all safety data sources are completely amenable to automation, but technology, when applied appropriately and responsibly, has proven to be a critical component of drug safety monitoring. Especially with workforce reductions, technology and automation can empower better, more efficient AE monitoring and reporting.
The projected workforce shortage and talent gap will impact the life sciences field, potentially altering scientific discovery and patient outcomes. PV teams can turn to automation to manage the impact of workforce shortages. Automation-based technologies such as AI, ML or NLP provide a solution to the challenges posed by workforce shortages in the pharmaceutical industry. Automation is a critical tool for PV teams to manage the impact of workforce shortages and ensure the safety of patients.
About Axel Hagel
Axel Hagel is the Practice Leader of PV & RM services at IQVIA. Hagel has over 28 years of experience in the life sciences industry, specializing in the deployment of drug safety applications in North America, Europe, and Japan. He has experience and implementation skills for the Argus Safety Suite, including Argus J, and is recognized in the drug safety sector as a pharmacovigilance industry leader.
