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INTRODUCTION: The uptake of complex technologies and platforms has resulted in several challenges in the pricing and reimbursement of innovative pharmaceuticals. To address these challenges, plenty of concepts have already been described in the scientific literature about innovative value judgment or payment models, which are either (1) remaining theoretical; or (2) applied only in pilots with limited impact on patient access; or (3) applied so heterogeneously in many different countries that it prevents the health care industry from meeting expectations of HTA bodies and health care payers in the evidence requirements or offerings in different jurisdictions.AREAS COVERED: This paper provides perspectives on how to reduce the heterogeneity of pharmaceutical payment models across European countries in five areas, including 1) extended evaluation frameworks, 2) performance-based risk-sharing agreements, 3) pooled procurement for low volume or urgent technologies, 4) alternative access schemes, and 5) delayed payment models for technologies with high upfront costs.EXPERT OPINION: Whilst pricing and reimbursement decisions will remain a competence of EU member states, there is a need for alignment of European pharmaceutical payment model components in critical areas with the ultimate objective of improving the equitable access of European patients to increasingly complex pharmaceutical technologies.

Outcome-based reimbursement models are gaining attention for managing the clinical uncertainties and financial impact of gene and cell therapies. Little guidance exists on how such models can create win-win-win situations, benefiting health-care payers, health-technology developers and patients. Our innovative approach prospectively prioritizes therapies for which a 'window of opportunity' might occur through the analysis of health-technology assessments and product characteristics. Within this window, one size does not fit all, and depending on the extent of clinical uncertainty and potential added benefit levels, different win-win-win situations exist in the United States, the United Kingdom and the Netherlands. Dutch Horizon scanning data prioritized etranacogene dezaparvovec (Hemgenix) and mozafancogene autotemcel for their potential to benefit from outcome-based reimbursement models. These insights extend beyond gene and cell therapies, and could help to provide sustainable health care and patient access to innovative therapies.

Clinicians and patients often try a treatment for an initial period to inform longer-term therapeutic decisions. A more rigorous approach involves N-of-1 trials. In these single-patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double-blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N-of-1 trial design as type 1, there also are new and evolving uses of N-of-1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N-of-1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual-patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N-of-1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value-based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N-of-1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N-of-1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N-of-1 trials.

This review can inform gene therapy developers on challenges that can be encountered when seeking market access. Moreover, it provides an overview of trends among challenges and potential solutions., SCOPUS: re.j, info:eu-repo/semantics/published

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., Ewing Marion Kauffman Foundation, Alfred P. Sloan Foundation, Massachusetts Technology Collaborative, Robert Wood Johnson Foundation

Recent studies have highlighted a reduction in projected financial returns associated with biopharmaceutical R&D, owing to decreased productivity, increases in costs and flattening revenue per new drug, prompting calls for dramatic revisions to R&D models. On the basis of previous financial modelling, the simplest hypothesis would be that new investment in such R&D should be minimal and focused on biologics in preference to small molecules, as the internal rate of return on investment for biologics projects has been reported to be higher (Nat. Rev. Drug Discov. 8, 609–610; 2009). We sought to discern how investors have been acting in recent years, and so examined investment trends in nascent public biopharmaceutical companies located in the United States by constructing a database of such companies that had US initial public offerings (IPOs) between 2010 and 2014 (see Supplementary information S1 (box) for details). We then analysed the characteristics of the 113 companies that met our inclusion criteria, including their corporate strategy and therapeutic modality focus. Here, we present the key findings from this analysis and discuss its implications based on our own financial modelling., United States. National Institutes of Health (NIANIH/R01AG043560)

A central question in the assessment of benefit/harm of new treatments is: how does the average outcome on the new treatment (the factual) compare to the average outcome had patients received no treatment or a different treatment known to be effective (the counterfactual)? Randomized controlled trials (RCTs) are the standard for comparing the factual with the counterfactual. Recent developments necessitate and enable a new way of determining the counterfactual for some new medicines. For select situations, we propose a new framework for evidence generation, which we call “threshold-crossing.” This framework leverages the wealth of information that is becoming available from completed RCTs and from real world data sources. Relying on formalized procedures, information gleaned from these data is used to estimate the counterfactual, enabling efficacy assessment of new drugs. We propose future (research) activities to enable “threshold-crossing” for carefully selected products and indications in which RCTs are not feasible.