We can unlock massive potential through automating predictable tasks like formatting, metadata extraction, dossier building and basic quality checks. By limiting expert involvement in such activities, we increase capacity for strategic, complex tasks.
Creating interdisciplinary teams with new skills in data literacy
We need self-organising, interdisciplinary teams to address digital disruption, specifically the approval and licencing of algorithms and digital assets for precision and personalised medicine.
In addition, we need fresh perspectives on what this new way of organising teams means for regulation, product safety and how efficacy is evaluated. New, cross-functional teams will centre on therapeutic areas, bringing together disciplines in regulatory strategy, digital health, clinical, safety, medical affairs, data stewardship and local market expertise.
Proactive health authority exchanges, social listening and intelligence gathering
Continuous dialogue with regulators and policymakers, e.g. the FDA, MHRA, WHO etc., helps bridge industry, customer and regulatory needs.
Effective regulatory teams gather market and regulatory intelligence through “social listening” tools to better understand patients’ unmet needs, behaviour patterns and trends in health issues.
Social listening is about monitoring digital conversations amongst stakeholders (typically in the news and social media) to get insights into what people and groups are saying about their experiences with products.
Social listening provides relevant, voluminous high-velocity data. Therefore, it becomes imperative that we establish a “data-to-insights” process to filter, analyse and summarise the vast quantities of social data to avoid becoming overwhelmed.
Building a shared, insight-driven big picture
The ability to capture and mine data sources around product activity improves the overall regulatory strategy and innovation and will accelerate approvals.
We need to build a common, visual, easy-to-understand submission pipeline for stakeholders to see and thus enable insight-driven decision-making on product strategy.
This means accessing new data sources to support decision-making (e.g. real-world evidence, biomarkers and patient insights), forcing a change in how evidence is evaluated.
Effective forecasting, priority setting and flexible resource management
Accurate forecasting enabling dynamic priority setting and flexible central planning are at the heart of making regulatory affairs effective. This, in turn, helps direct R&D because it explores new modalities (as seen with RNAi in the COVID-19 vaccine design).