Key Takeaways

• We see continued advancement in improving and expediting evidence from a range of source data generated at different points in the healthcare product lifecycle, from clinical trials to electronic health records to patient/disease registries.
• We also see corresponding progress in ways to optimize regulatory review and analysis of these data.
• Collaboration and partnerships, especially public-private partnerships, have been fundamental in this progress. However, are industry and regulators ready to partner with new stakeholders– regulators partnering, for example, with technology companies?
• In all these changes, true collaboration requires trust, patience, and a common sense of purpose.

Why this is important: “The story of evidence generation really needs to be linked to how do we actually get that evidence to get approvals faster, and patient access faster?” explained João Duarte, Associate Director, Europe Regulatory Policy & Intelligence, Takeda (UK). “Global cooperation is fundamental in any aspect related to this. We cannot duplicate. We cannot lose time. We cannot lose patient confidence in the way we do development.”

Generation of Evidence for Regulatory Review

Different evidence is generated for different purposes at different stages of the healthcare product lifecycle:

• Evidence is developed from a range of source data: non-clinical, clinical, simulated, historical and current real world data, patient/disease registries, observational studies, and pragmatic and randomized controlled clinical trials.
• Before market launch evidence generation is undertaken solely by the developer, directly or indirectly; after launch, evidence generation can be undertaken by other stakeholders.
• If properly designed to clearly identify the benefits, risks, and value of a product in use, post-launch evidence generation will complement the initial body of clinical evidence upon which that product was approved.
• Different stakeholders throughout the healthcare ecosystem–regulators, health technology assessment bodies (HTAs), payers, clinicians, and patients–use this evidence for different purposes.

EMA’s Post-Licensing Evidence Generator (PLEG) Project

Data accumulated in this structured, unified format are envisioned to improve a variety of services in the healthcare ecosystem:

• Patients, caregivers, and clinicians: More effective clinical practice recommendations/guidelines, thus lightening the burden of care
• Regulatory
  • Relative effectiveness analysis
  • Safety monitoring
• Health Technology Assessment
  • Financial conditions of use, including performance based-payments
  • Cost effectiveness analysis
  • Safety monitoring

Regulatory Optimization Group

The Regulatory Optimisation Group (ROG), chaired by Heads of Medicines Agencies, was established in 2017 “to incorporate a modern style of work ethos; fostering effective teamwork by combining teambuilding with an in-depth, out-of-the-box and open dialogue between the regulators and industry partners in ROG, to fully elaborate the issues, problems and proposed solutions.”

One of the ROG’s first business cases has been to reassess the value of post-marketing Type 1A variations. Over the past five years, EMA has seen a 45% increase in these variations per MAH/per year. By definition, these variations have only minimal impact or no impact at all on the quality, safety, or efficacy of the medicinal product, or provide other administrative or minor changes (e.g., MAH name or address change, or manufacturers’ name or address change).

Addressing these variations removes resources from working on more critical variations (such as safety-related label changes) or process improvements, thereby delaying market access with little to any benefit to patients from these changes.

One vision of “optimized efficiency” in regulatory review through telematics:

• Capture data only once, in a form that encourages re-use and availability to other stakeholders.
• Provide the data set to regulatory authorities only once, and allow systems and databases to communicate with and disseminate data through each other.
• Assess the data set only once, either by worksharing with or relying on assessments performed by another Member State.

Better Free Your Mind Instead

Many characteristics of this future optimized regulatory system are already in place or will soon be here. “We have industry working with regulators, working with patients, working with other stakeholders. And we need to have that sense of trust. We need to have that sense of common purpose. Because only then will, eventually, patients benefit from what we do together,” Duarte concluded. “Sometimes, to really make a change, we don’t need to make a revolution. We need to actually look inside of us and see what we can change in our work and in the way we work together.”