Transforming pharmacovigilance systems has been saved
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Transforming pharmacovigilance systems
Using technology, analytics, and automation to enable next-gen patient safety
Today, pharmacovigilance (PV) systems are being reshaped by health care trends that include complex global regulations, increasing adverse effect volume, and new sources of data. Automation, cognitive technologies, and analytics provide opportunities to shift the pharmacovigilance function from compiling and reporting data to helping to raise product quality, optimize treatment plans, reduce costs, and improve patient safety.
The evolving pharmacovigilance landscape
For the past several decades, the pharmacovigilance function has been responsible for collecting, processing, and reporting adverse events (AEs) and other product safety information to regulators. PV’s process-heavy nature often drove companies to select associated safety systems based on their ability to organize data and optimize efficiency, typically leaving limited system options.
Today’s PV function is being reshaped by numerous global health care trends. While many of these trends are delivering considerable benefits, they also are exerting pressure on biopharmaceutical companies’ existing safety systems.
As a result, many organizations are facing significant cost burdens to maintain and upgrade these systems, even though—under the current safety system paradigm—the same trends may cause the costs of traditional upgrade approaches to grow disproportionally versus benefits. This, in turn, is prompting many biopharma companies to consider how automation, cognitive technologies, and advanced analytics may help them get more from their PV systems—to progress from merely analyzing, formatting, and submitting reports on patient- and provider-supplied case processing and signaling data to creating a next-generation digital learning system that efficiently and cost-effectively increases product quality and patient safety.
Transformation of patient safety
Results of a 2018 Deloitte survey of mid- and large-cap global biopharma companies’ PV practices, costs, and plans show that a majority are investing in PV-related automation (or evaluating the business case) to gain process efficiencies, free up resources to perform value-added tasks (such as benefits-risk evaluation and management, signal investigation, and real-world evidence analysis); improve quality assurance consistency, accuracy, and reliability; and reduce their PV cost burden.
Companies’ plans for the next three to five years focus heavily on leveraging cognitive automation with current safety databases. Driving cost out of case processing is the primary goal for 90 percent of respondents; capturing data to improve signaling is also important.
Case processing: With PV budgets allocating 40 percent to 85 percent of spend on case processing, and case volumes growing at a rate of 10–15 percent per year, driving cost out of case processing is the primary goal for 90 percent of survey respondents. Low-cost leaders are outsourcing, taking advantage of scale, and moving aggressively to automate case processing. Survey respondents expect automation to produce an average annual cost savings of 30 percent per Individual Case Safety Report (ICSR).
Signaling: Most pharmaceutical companies continue to use traditional signal detection and investigation methods (such as medical assessment of individual spontaneous reports of adverse events, interventional clinical trials, database mining); a few are leveraging real-world evidence (RWE); almost none are progressing social media channels. This is consistent with current PV system capabilities.
Survey respondents see broad opportunities to improve their signal processing and investigation maturity; half say they plan to expand these capabilities. The ultimate goal is predictive signaling.
Lowering case processing costs, expanding signal processing capabilities, and expediting product safety reports are compelling reasons for biopharma companies to include automation, cognitive technologies, and advanced analytics in their PV budgets. Yet we anticipate even greater gains if biopharmas leverage digital technology to create a next-generation PV learning system for improved patient safety. Moving to a proactive and patient-centric approach can help enable a detailed understanding of product benefit risk profiles and a true, evidence-based center for safety intelligence across the entire product life cycle.
However, pharma companies’ current use of multiple, siloed information systems to process safety data may prevent many of them from reaching this desired future state. For example, various internal PV groups examine safety data coming from external sources in different ways and for different purposes; each group may pull and analyze data from as many as a dozen disparate systems and—unsurprisingly—draw multiple versions of the truth.
One approach to breaking the case processing cost curve while also enhancing the role of signaling is to institute an end-to-end, modular “learning loop” system that uses a unified data platform and automation to cognitively process upstream and downstream safety information and leverage continual learning to help mitigate risk, strengthen compliance, and improve patient outcomes.
All stakeholders in drug development share the responsibility of ensuring patient safety. Automation, cognitive technologies, and advanced analytics are providing opportunities to transform pharmacovigilance from the process of preparing AE reports for regulators to creating a learning system that emphasizes benefit and risk management and proactive surveillance throughout the product life cycle.
To begin, PV organizations should look at their vision of the future and decide whether getting there will require incremental or transformational change. Among questions to consider:
● What are the short-term “bare minimums” and our longer-term strategic objectives?
● What are the technology and business trends that may evolve to transform this space?
● What capabilities do we have today? What will we need for the future?
● How can we identify, develop, and implement "quick wins" that may create breathing room to invest in the future of safety?
● Have we looked at both operational transformation and technology solutions to continually improve our safety capabilities and internal efficiencies?
If you are interested in learning how Deloitte is helping our clients to achieve their vision of a transformed pharmacovigilance system, we should talk.
ConvergeHEALTH brings products and solutions to help organizations enable next generation patient safety.
Kevin Sullivan |
Aditya Kudumala |
Glenn Carroll |
Joe Montrosse |
