The Janus initiative: A multi-stakeholder process and tool set for facilitating and quantifying Adaptive Licensing discussions

Precision Reimbursement for Precision Medicine: Using Real-World Evidence to Evolve From Trial-and-Project to Track-and-Pay to Learn-and-Predict

Basic scientists and drug developers are accelerating innovations toward the goal of precision medicine. Regulators create pathways for timely patient access to precision medicines, including individualized therapies. Healthcare payors acknowledge the need for change but downstream innovation for coverage and reimbursement is only haltingly occurring. Performance uncertainty, high price‐tags, payment timing, and actuarial risk issues associated with precision medicines present novel financial challenges for payors. With traditional drug reimbursement frameworks, payment is based on an assumed randomized controlled trial (RCT) projection of real‐world effectiveness, a “trial‐and‐project” strategy; the clinical benefit realized for patients is not usually ascertained ex post by collection of real‐world data (RWD). To mitigate financial risks resulting from clinical performance uncertainty, manufacturers and payors devised “track‐and‐pay” frameworks (i.e., the tracking of a pre‐agreed treatment outcome which is linked to financial consequences). Whereas some track‐and‐pay arrangements have been successful, inherent weaknesses include the potential for misalignment of incentives, the risk of channeling of patients, and a failure to use the RWD generated to enable continuous learning about treatments. “Precision reimbursement” (PR) intends to overcome inherent weaknesses of simple track‐and‐pay schemes. In combining the collection of RWD with advanced analytics (e.g., artificial intelligence and machine learning) to generate actionable real‐world evidence, with prospective alignment of incentives across all stakeholders (including providers and patients), and with pre‐agreed use and dissemination of information generated, PR becomes a “learn‐and‐predict” model of payment for performance. We here describe in detail the concept of PR and lay out the next steps to make it a reality.

Dynamic Dossier in the Cloud: A Sociotechnical Architecture for a Real-Time and Metrics-Based Data Tracking System with Gene and Cell Therapies as a Case Study

Background

Data sharing among stakeholders in the development, access, and use of drug therapies is critical but the current system and process are inefficient.

Methods

We take a Systems Engineering approach with a realistic use case to propose a scalable design for multi-stakeholder data sharing.

Results

We make three major contributions to the drug development and healthcare communities: first, a methodology for developing a multi-stakeholder data sharing system, with its focus on high-level requirements that influence the design of the system architecture and technology choice; second, the development of a realistic use case for long-term patient and therapy data tracking and sharing in the use of potentially curative and durable gene and cell therapies. Further, a bridge for the ‘awareness gap’ was found between the payer (Payer is organization which takes care of financial and operational aspects (which include insurance plans, provider network) of providing health care to US citizens. Or refer to health care insurers.) and the regulator communities by illustrating the common data tracking needs, which highlights the need for coordinated data activities; and third, a proposed system architecture for scalable, multi-stakeholder data sharing. Next steps are briefly discussed.

Conclusion

We present a system design for multiple stakeholders such as the payer, the regulator, the developer (drug manufacturer), and the healthcare provider to share data for their decision-making. The stakeholder community would benefit from collaboratively moving the system development proposal forward for efficient and cost-effective data sharing.

Recognizing that Evidence is Made, not Born

Therapeutic product development, licensing and reimbursement may seem a well-oiled machine, but continuing high attrition rates, regulatory refusals, and patients' access issues suggest otherwise; despite serious efforts, gaps persist between stakeholders' stated evidence requirements and actual evidence supplied. Evidentiary deficiencies and/or human tendencies resulting in avoidable inefficiencies might be further reduced with fresh institutional cultures/mindsets, combined with a context-adaptable practices framework that integrates emerging innovations. Here, Structured Evidence Planning, Production, and Evaluation (SEPPE) posits that evidence be treated as something produced, much like other manufactured goods, for which "built-in quality" (i.e., "people" and "process") approaches have been successfully implemented globally. Incorporating proactive, iterative feedback-and-adjust loops involving key decision-makers at critical points could curtail avoidable evidence quality and decision hazards-pulling needed therapeutic products with high quality evidence of beneficial performance through to approvals. Critical for success, however, is dedicated, long-term commitment to systemic transformation.

Medicines Adaptive Pathways to Patients (MAPPs): A Story of International Collaboration Leading to Implementation

After nearly a decade of discussion, analysis, and development, the Medicines Adaptive Pathways to Patients (MAPPs) initiative is beginning to see acceptance from regulators, industry, patients, and payers, with the first live pilot project initiated under the guidance of the European Medicines Agency in 2014. Although it is a significant achievement to see the first asset being placed into human trials under an adaptive pathway, there is much to be learned regarding the multinational and multi-stakeholder effort that has driven the growing acceptance of MAPPs as a methodology and concept, as well as the need for continued and increasing international collaboration to foster the wider adoption of MAPPs. Changes in available science and technology, as well as a number of challenges in the current system, outlined in this paper, are transforming approaches to medicines development and approval. It is these challenges that have led directly to the groundbreaking MAPPs collaboration between the Massachusetts Institute of Technology Center for Biomedical Innovation's New Drug Development Paradigms Initiative, the EMA, patient, payer and health technology assessment groups, the European Federation of Pharmaceutical Industries and Associations, and the Innovative Medicines Initiative-a European public-private partnership. This article examines the development of MAPPs, from inception of the concept, to the establishment of this trans-Atlantic initiative, and examines challenges for the future.

Adaptive Biomedical Innovation: Evolving Our Global System to Sustainably and Safely Bring New Medicines to Patients in Need

The current system of biomedical innovation is unable to keep pace with scientific advancements. We propose to address this gap by reengineering innovation processes to accelerate reliable delivery of products that address unmet medical needs. Adaptive biomedical innovation (ABI) provides an integrative, strategic approach for process innovation. Although the term "ABI" is new, it encompasses fragmented "tools" that have been developed across the global pharmaceutical industry, and could accelerate the evolution of the system through more coordinated application. ABI involves bringing stakeholders together to set shared objectives, foster trust, structure decision-making, and manage expectations through rapid-cycle feedback loops that maximize product knowledge and reduce uncertainty in a continuous, adaptive, and sustainable learning healthcare system. Adaptive decision-making, a core element of ABI, provides a framework for structuring decision-making designed to manage two types of uncertainty - the maturity of scientific and clinical knowledge, and the behaviors of other critical stakeholders.