Patients, payers and developers of Orphan Medicinal Products: lessons learned from 10 years' multi-stakeholder dialogue on improving access in Europe via MoCA.

BACKGROUND: The Mechanism of Coordinated Access to Orphan Medicinal Products (MoCA) was established in 2013 with the intention of developing a coordinated mechanism between volunteering EU stakeholders and developers of Orphan Medicinal Products (OMPs) to support the exchange of information aimed at enabling informed decisions on pricing and reimbursement at Member State level and to evaluate the value of an OMP based on a Transparent Value Framework. The objective of the collaborative approach was to support more equitable access to authorised therapies for people living with rare diseases, rational prices for payers and more predictable market conditions for OMP developers. Over the past 10 years, the MoCA has conducted a series of pilot projects, examining a variety of different products and technologies at different stages of development; and with contributions from a variety of patient representatives, participation from EU payers from a range of Member States and, recently, with EUnetHTA members and the European Medicines Agency participating in the meetings as observers. RESULTS: 10 years on from the establishment of the MoCA, the European landscape has significantly evolved, not only in the field of drug development with increasingly transformative therapies based on novel technologies, but also in terms of larger numbers of approved treatments, increased budget impact and the resulting associated uncertainties; as well as in terms of stakeholder collaboration and interactions. The value of early dialogue with OMP developers, including the EU payer community via their national decision-making authorities, is a key element within this early interaction and contributes to identifying, managing and reducing uncertainties allowing a prospectively planned approach earlier in development and, consequently, to support more timely, sustainable and equitable access to new OMPs, particularly where there is a high unmet medical need. CONCLUSIONS: The voluntary, informal nature of the MoCA interactions creates a flexible framework for non-binding dialogue. A forum for such interactions is needed to achieve the aims of the MoCA and both to support healthcare systems in planning as well as to underpin timely, equitable and sustainable access to new therapies for patients with rare diseases within the EU.

Uncertainty management in regulatory and health technology assessment decision-making on drugs: guidance of the HTAi-DIA Working Group.

OBJECTIVES: Uncertainty is a fundamental component of decision making regarding access to and pricing and reimbursement of drugs. The context-specific interpretation and mitigation of uncertainty remain major challenges for decision makers. Following the 2021 HTAi Global Policy Forum, a cross-sectoral, interdisciplinary HTAi-DIA Working Group (WG) was initiated to develop guidance to support stakeholder deliberation on the systematic identification and mitigation of uncertainties in the regulatory-HTA interface. METHODS: Six online discussions among WG members (Dec 2021-Sep 2022) who examined the output of a scoping review, two literature-based case studies and a survey; application of the initial guidance to a real-world case study; and two international conference panel discussions. RESULTS: The WG identified key concepts, clustered into twelve building blocks that were collectively perceived to define uncertainty: "unavailable," "inaccurate," "conflicting," "not understandable," "random variation," "information," "prediction," "impact," "risk," "relevance," "context," and "judgment." These were converted into a checklist to explain and define whether any issue constitutes a decision-relevant uncertainty. A taxonomy of domains in which uncertainty may exist within the regulatory-HTA interface was developed to facilitate categorization. The real-world case study was used to demonstrate how the guidance may facilitate deliberation between stakeholders and where additional guidance development may be needed. CONCLUSIONS: The systematic approach taken for the identification of uncertainties in this guidance has the potential to facilitate understanding of uncertainty and its management across different stakeholders involved in drug development and evaluation. This can improve consistency and transparency throughout decision processes. To further support uncertainty management, linkage to suitable mitigation strategies is necessary.

Orphan drugs' clinical uncertainty and prices: Addressing allocative and technical inefficiencies in orphan drug reimbursement.

Legislations incentivising orphan drug development and scientific advances have made orphan drugs pharma's high-end favourite for the past two decades. Currently, around 50% of new marketing authorizations are for orphan drugs. For third-party healthcare payers ("payers") the rise of orphan drugs presents new challenges, including a high degree of uncertainty around clinical benefits and harms, a moderate effect size (for many orphan drugs), and a high price tag. The association of high clinical uncertainty and moderate effect sizes is not surprising in small target populations but in combination with high prices creates the risk of allocative and technical inefficiencies for payers. We here discuss and illustrate these risks. A combination of policies is needed for mitigation of allocative inefficiency: while there may be a rationale for higher prices for orphan than non-orphan drugs, a focus of pricing and reimbursement negotiations should include considerations of product profitability and of the consequences of orphan drug costs on the distribution inequality of medication costs for individual insured persons, coupled to knowledge generation from reimbursement contracts covering high-price orphan drugs that would benefit the wider patient community. Performance-based managed entry agreements could help to de-risk the economic consequences of clinical uncertainty and to mitigate technical inefficiency.

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.

A Useful and Sustainable Role for N-of-1 Trials in the Healthcare Ecosystem.

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.

Exploring the opportunities for alignment of regulatory postauthorization requirements and data required for performance-based managed entry agreements.

Performance-based managed entry agreements (PB-MEAs) might allow patient access to new medicines, but practical hurdles make competent authorities for pricing and reimbursement (CAPR) reluctant to implement PB-MEAs. We explored if the feasibility of PB-MEAs might improve by better aligning regulatory postauthorization requirements with the data generation of PB-MEAs and by active collaboration and data sharing. Reviewers from seven CAPRs provided structured assessments of the information available at the European Medicines Agency (EMA) Web site on regulatory postauthorization requirements for fifteen recently authorized products. The reviewers judged to what extent regulatory postauthorization studies could help implement PB-MEAs by addressing uncertainty gaps. Study domains assessed were: patient population, intervention, comparators, outcomes, time horizon, anticipated data quality, and anticipated robustness of analysis. Reviewers shared general comments about PB-MEAs for each product and on cooperation with other CAPRs. Reviewers rated regulatory postauthorization requirements at least partly helpful for most products and across domains except the comparator domain. One quarter of responses indicated that public information provided by the EMA was insufficient to support the implementation of PB-MEAs. Few PB-MEAs were in place for these products, but the potential for implementation of PB-MEAs or collaboration across CAPRs was seen as more favorable. Responses helped delineate a set of conditions where PB-MEAs may help reduce uncertainty. In conclusion, PB-MEAs are not a preferred option for CAPRs, but we identified conditions where PB-MEAs might be worth considering. The complexities of implementing PB-MEAs remain a hurdle, but collaboration across silos and more transparency on postauthorization studies could help overcome some barriers.

Organized structure of real-world evidence best practices: moving from fragmented recommendations to comprehensive guidance.

Decision-makers have become increasingly interested in incorporating real-world evidence (RWE) into their decision-making process. Due to concerns regarding the reliability and quality of RWE, stakeholders have issued numerous recommendation documents to assist in setting RWE standards. The fragmented nature of these documents poses a challenge to researchers and decision-makers looking for guidance on what is 'high-quality' RWE and how it can be used in decision-making. We offer researchers and decision-makers a structure to organize the landscape of RWE recommendations and identify consensus and gaps in the current recommendations. To provide researchers with a much needed pathway for generating RWE, we discuss how decision-makers can move from fragmented recommendations to comprehensive guidance.

Randomized Controlled Trials Versus Real World Evidence: Neither Magic Nor Myth.

Compared with drugs from the blockbuster era, recently authorized drugs and those expected in the future present a heterogenous mix of chemicals, biologicals, and cell and gene therapies, a sizable fraction being for rare diseases, and even individualized treatments or individualized combinations. The shift in the nature of products entails secular trends for the definitions of "drugs" and "target population" and for clinical use and evidence generation. We discuss that the lessons learned from evidence generation for 20th century medicines may have limited relevance for 21st century medicines. We explain why the future is not about randomized controlled trials (RCTs) vs. real-world evidence (RWE) but RCTs and RWE-not just for the assessment of safety but also of effectiveness. Finally, we highlight that, in the era of precision medicine, we may not be able to reliably describe some small treatment effects-either by way of RCTs or RWE.

Improving Transparency to Build Trust in Real-World Secondary Data Studies for Hypothesis Testing-Why, What, and How: Recommendations and a Road Map from the Real-World Evidence Transparency Initiative.

Real-world data (RWD) and the derivations of these data into real-world evidence (RWE) are rapidly expanding from informing healthcare decisions at the patient and health system level to influencing major health policy decisions, including regulatory approvals and coverage. Recent examples include the approval of palbociclib in combination with endocrine therapy for male breast cancer and the inclusion of RWE in the label of paliperidone palmitate for schizophrenia. This interest has created an urgency to develop processes that promote trust in the evidence-generation process. Key stakeholders and decision-makers include patients and their healthcare providers; learning health systems; health technology assessment bodies and payers; pharmacoepidemiologists and other clinical reseachers, and policy makers interested in bioethical and regulatory issues. A key to optimal uptake of RWE is transparency of the research process to enable decision-makers to evaluate the quality of the methods used and the applicability of the evidence that results from the RWE studies. Registration of RWE studies-particularly for hypothesis evaluating treatment effectiveness (HETE) studies-has been proposed to improve transparency, trust, and research replicability. Although registration would not guarantee better RWE studies would be conducted, it would encourage the prospective disclosure of study plans, timing, and rationale for modifications. A joint task force of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) recommended that investigators preregister their RWE studies and post their study protocols in a publicly available forum before starting studies to reduce publication bias and improve the transparency of research methods. Recognizing that published recommendations alone are insufficient, especially without accessible registration options and with no incentives, a group of experts gathered on February 25 and 26, 2019, in National Harbor, Maryland, to explore the structural and practical challenges to the successful implementation of the recommendations of the ISPOR/ISPE task force for preregistration. This positioning article describes a plan for making registration of HETE RWE studies routine. The plan includes specifying the rationale for registering HETE RWE studies, the studies that should be registered, where and when these studies should be registered, how and when analytic deviations from protocols should be reported, how and when to publish results, and incentives to encourage registration. Table 1 summarizes the rationale, goals, and potential solutions that increase transparency, in addition to unique concerns about secondary data studies. Definitions of terms used throughout this report are provided in Table 2.

Improving transparency to build trust in real-world secondary data studies for hypothesis testing-Why, what, and how: recommendations and a road map from the real-world evidence transparency initiative.

Real-world data (RWD) and the derivations of these data into real-world evidence (RWE) are rapidly expanding from informing healthcare decisions at the patient and health system level to influencing major health policy decisions, including regulatory approvals and coverage. Recent examples include the approval of palbociclib in combination with endocrine therapy for male breast cancer and the inclusion of RWE in the label of paliperidone palmitate for schizophrenia. This interest has created an urgency to develop processes that promote trust in the evidence-generation process. Key stakeholders and decision-makers include patients and their healthcare providers; learning health systems; health technology assessment bodies and payers; pharmacoepidemiologists and other clinical reseachers, and policy makers interested in bioethical and regulatory issues. A key to optimal uptake of RWE is transparency of the research process to enable decision-makers to evaluate the quality of the methods used and the applicability of the evidence that results from the RWE studies. Registration of RWE studies-particularly for hypothesis evaluating treatment effectiveness (HETE) studies-has been proposed to improve transparency, trust, and research replicability. Although registration would not guarantee better RWE studies would be conducted, it would encourage the prospective disclosure of study plans, timing, and rationale for modifications. A joint task force of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) recommended that investigators preregister their RWE studies and post their study protocols in a publicly available forum before starting studies to reduce publication bias and improve the transparency of research methods. Recognizing that published recommendations alone are insufficient, especially without accessible registration options and with no incentives, a group of experts gathered on February 25 and 26, 2019, in National Harbor, Maryland, to explore the structural and practical challenges to the successful implementation of the recommendations of the ISPOR/ISPE task force for preregistration. This positioning article describes a plan for making registration of HETE RWE studies routine. The plan includes specifying the rationale for registering HETE RWE studies, the studies that should be registered, where and when these studies should be registered, how and when analytic deviations from protocols should be reported, how and when to publish results, and incentives to encourage registration. Table 1 summarizes the rationale, goals, and potential solutions that increase transparency, in addition to unique concerns about secondary data studies. Definitions of terms used throughout this report are provided in Table 2.

Clinical Trials for COVID-19: Can we Better Use the Short Window of Opportunity?

The scientific community has risen to the coronavirus disease 2019 (COVID-19) challenge, coming up with an impressive list of candidate drugs and vaccines targeting an array of pharmacological and immunological mechanisms. Yet, generating clinical evidence of efficacy and safety of these candidate treatments may be frustrated by the absence of comprehensive trial coordination mechanisms. Many small stand-alone trials and observational studies of single-agent interventions are currently running or in planning; many of these will likely not deliver robust results that could support regulatory and patient-level treatment decisions. In this paper, we discuss actions that all stakeholders in the clinical trial ecosystem need to take to ensure that the window of opportunity during this pandemic will not shut, both for patients in need of treatment and for researchers to conduct decision-relevant clinical trials.

Are Novel, Nonrandomized Analytic Methods Fit for Decision Making? The Need for Prospective, Controlled, and Transparent Validation.

Real-world data and patient-level data from completed randomized controlled trials are becoming available for secondary analysis on an unprecedented scale. A range of novel methodologies and study designs have been proposed for their analysis or combination. However, to make novel analytical methods acceptable for regulators and other decision makers will require their testing and validation in broadly the same way one would evaluate a new drug: prospectively, well-controlled, and according to a pre-agreed plan. From a European regulators' perspective, the established methods qualification advice procedure with active participation of patient groups and other decision makers is an efficient and transparent platform for the development and validation of novel study designs.

Efficacy and Effectiveness Too Trials: Clinical Trial Designs to Generate Evidence on Efficacy and on Effectiveness in Wide Practice.

Efficacy trials, designed to gain regulatory marketing approval, evaluate drugs in optimally selected patients under advantageous conditions for relatively short time periods. Effectiveness trials, designed to evaluate use in usual practice, assess treatments among more typical patients in real-world conditions with longer follow-up periods. In "efficacy-to-effectiveness (E2E) trials," if the initial efficacy trial component is positive, the trial seamlessly transitions to an effectiveness trial component to efficiently yield both types of evidence. Yet more time could be saved by simultaneously addressing efficacy and effectiveness in an "efficacy and effectiveness too (EE2) trial." Additionally, hybrids of the E2E and EE2 approaches with differing degrees of overlap of the two components could allow flexibility for specific drug development needs. In planning EE2 trials, each stakeholder's current and future needs, incentives, and perspective must be considered. Although challenging, the ultimate benefits to stakeholders, the health system, and the public should justify this effort.

Medicines Adaptive Pathways to Patients: Why, When, and How to Engage?

Medicines Adaptive Pathways to Patients (MAPPs) seeks to foster access to novel beneficial treatments for the right patient groups at the earliest appropriate time in the product life-span, in a sustainable fashion. We summarize the MAPPs engagement process and critical questions to be asked at each milestone of the product life-span. These considerations are of relevance for regulatory and access pathways that strive to address the "evidence vs. access" conundrum.

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.

Data Rich, Information Poor: Can We Use Electronic Health Records to Create a Learning Healthcare System for Pharmaceuticals?

Judicious use of real-world data (RWD) is expected to make all steps in the development and use of pharmaceuticals more effective and efficient, including research and development, regulatory decision making, health technology assessment, pricing, and reimbursement decisions and treatment. A "learning healthcare system" based on electronic health records and other routinely collected data will be required to harness the full potential of RWD to complement evidence based on randomized controlled trials. We describe and illustrate with examples the growing demand for a learning healthcare system; we contrast the exigencies of an efficient pharmaceutical ecosystem in the future with current deficiencies highlighted in recently published Organisation for Economic Co-operation and Development (OECD) reports; and we reflect on the steps necessary to enable the transition from healthcare data to actionable information. A coordinated effort from all stakeholders and international cooperation will be required to increase the speed of implementation of the learning healthcare system, to everybody's benefit.