Estimating the Clinical Pipeline of Cell and Gene Therapies and Their Potential Economic Impact on the US Healthcare System.

OBJECTIVES: To estimate, at the indication level, durable gene and cellular therapy new product launches in the United States through 2030, and the number of treated patients. METHODS: A statistical analysis of clinical trials pipeline data and disease incidence and prevalence was conducted to estimate the impact of new cell and gene therapies. We used Citeline's® Pharmaprojects® database to estimate the rates and timing of new product launches, on the basis of the phase of development, duration in phase, and probability of progression. Disease incidence and prevalence data were combined with estimates of market adoption to project the size of reimbursed patient populations. RESULTS: We project that about 350 000 patients will have been treated with 30 to 60 products by 2030. About half the launches are expected to be in B-cell (CD-19) lymphomas and leukemias. CONCLUSIONS: Cell and gene therapies promise durable clinical benefit from a single treatment course. High upfront reimbursement for these products means that the total costs could exceed what the healthcare system can manage. This creates a need for precision financing solutions and new reimbursement models that can ensure appropriate patient access to needed treatments, increase affordability for payers, and sustain private investment in innovation.

Characterization of annual disease progression of multiple sclerosis patients: A population-based study.

BACKGROUND: Previous research characterizing factors influencing multiple sclerosis (MS) disease progression has typically been based on time to disease milestones (Kaplan-Meier, Cox hazard regression, etc.). A limitation of these methods is the handling of the often large groups of patients not reaching the milestone. OBJECTIVE: To characterize clinical factors influencing MS disease progression as annual transitions from each Expanded Disability Status Scale (EDSS). METHOD: The annual progression of 11,964 patients from the Swedish MS Registry was analysed with 10 multinomial logistic regressions, that is, one for transition from each full EDSS with explanatory variables age, sex, age at onset, time in current EDSS, highest prior EDSS, MS course and treatment. RESULTS: All factors (except sex) investigated had statistically significant impacts on transitions from at least one EDSS. However, significance and size of the effect are dependent on the EDSS state of the patient. Greater age, longer time in a state, highest prior EDSS, having progressive MS and treatment had significant impacts, whereas age at onset had minor impact. CONCLUSION: Our study confirms that established factors associated with MS disease worsening in time to disease milestones also have impacts on annual progression. This approach adds granularity to what EDSS these factors have an influence.

DECISION-COMPONENTS OF NICE'S TECHNOLOGY APPRAISALS ASSESSMENT FRAMEWORK.

OBJECTIVES: Value assessment frameworks have gained prominence recently in the context of U.S. healthcare. Such frameworks set out a series of factors that are considered in funding decisions. The UK's National Institute of Health and Care Excellence (NICE) is an established health technology assessment (HTA) agency. We present a novel application of text analysis that characterizes NICE's Technology Appraisals in the context of the newer assessment frameworks and present the results in a visual way. METHODS: A total of 243 documents of NICE's medicines guidance from 2007 to 2016 were analyzed. Text analysis was used to identify a hierarchical set of decision factors considered in the assessments. The frequency of decision factors stated in the documents was determined and their association with terms related to uncertainty. The results were incorporated into visual representations of hierarchical factors. RESULTS: We identified 125 decision factors, and hierarchically grouped these into eight domains: Clinical Effectiveness, Cost Effectiveness, Condition, Current Practice, Clinical Need, New Treatment, Studies, and Other Factors. Textual analysis showed all domains appeared consistently in the guidance documents. Many factors were commonly associated with terms relating to uncertainty. A series of visual representations was created. CONCLUSIONS: This study reveals the complexity and consistency of NICE's decision-making processes and demonstrates that cost effectiveness is not the only decision-criteria. The study highlights the importance of processes and methodology that can take both quantitative and qualitative information into account. Visualizations can help effectively communicate this complex information during the decision-making process and subsequently to stakeholders.

Payer and Developer perspectives on alternative payment models.

OBJECTIVE: To understand the use of alternative payment models to address the reimbursement challenges of cell and gene therapies (CGT) in the U.S.A.. METHODS: A literature search focused on CGT reimbursement in the U.S. market was conducted to identify information gaps and inform survey development. U.S. developers (n = 100) and payers (n = 195) were invited to complete an online survey between June and August 2022. RESULTS: The overall response rate was 16%; payer respondents represented 98 plans covering 338 million lives. Most developers (81%) and payers (84%) had implemented or were planning to implement at least one alternative payment model. Payers pursued these models to 'reduce product performance uncertainties' (81%), 'align therapy costs with benefits' (58%), and 'manage actuarial uncertainty' (54%). Developers aimed to 'streamline patient access' (92%) and 'mitigate budget impact' (77%). Common perceived barriers included increased administrative burden (developers 79% and payers 67%), defining performance measures (developers 71%, payers 83%) and addressing patient mobility (developers 71% and payers 63%). Both parties expressed a willingness to use real-world evidence for contract adjudication. CONCLUSION: Although limited by the number of participants, this survey indicates early discussions coupled with understanding motivations are essential for developing contracts that appeal to both parties and ensure patient access.

Creating win-win-win situations with managed entry agreements? Prioritizing gene and cell therapies within the window of opportunity.

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.

Importance of aligning the implementation of new payment models for innovative pharmaceuticals in European countries.

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.

Medicaid best price reforms to enable innovative payment models for cell and gene therapies.

BACKGROUND: Cell and gene therapies promise durable benefits but face financial challenges from the uncertainty in their performance. Value-based purchasing arrangements (VBPAs) can address uncertainty but have been inhibited in the US by the Medicaid Drug Rebate Program (MDRP) approach to determining Medicaid Best Price (MBP) rebates. The likely effectiveness of MDRP reform proposals enabling VBPAs is examined in this study for durable cell and gene therapies. METHODS: Monte Carlo simulations examined three potential reforms (Multiple Best Prices, Bundled Sales, and National Pooling) to determine the impact on payment misalignment, the required payer size to participate, and the percentage of total lives covered by a VBPA. RESULTS: Simulation results suggest that 11% to 54% of commercial US lives would be feasibly covered by a VBPA depending on reform type and condition size. MPB reform achieved the highest commercial contracted percentage and lowest misalignment for commercial payers compared to National Pooling and Bundled Sales. State Medicaid plan results suggest lower extreme misalignment across all successfully contracted instances than commercial payers. CONCLUSIONS: The Multiple Best Prices will likely enable VBPAs for many durable cell and gene therapies and larger payers. Further reforms may be needed to extend VBPAs to ultra-orphan conditions.

Value-based performance arrangements for chronic conditions: an economic simulation of Medicaid Drug Rebate Program reforms.

OBJECTIVE: Changes to the Medicaid Drug Rebate Program (MDRP) determination of Medicaid Best Price (MBP) enables Value-based purchasing arrangements (VBPAs) to address financial uncertainty. This study estimates the likely effectiveness of MDRP-enabled VBPAs for chronically dosed medicines. METHODS: Monte Carlo simulations examined: Multiple Best Prices and Bundled Sales MBP approaches authorized under MDRP and a third National Pooling approach using payment misalignment; needed payer size for practical participation; and the resulting potential number of covered lives under a VBPA as evaluation metrics. RESULTS: Both Multiple Best Prices and National Pooling enable VBPAs for 95% of scenarios (including all 5i chronic products with ≥1,000 treated patients per year), with 75% of those with payment misalignment ≤9%. National pooling for retail drugs has less participation and worse misalignment (5i: 95% contracted, 75% ≤9% misalignment; retail: 71%, 66%). Bundled Sales performed worst (5i: 40%, 75% ≤9%; retail: 31%, 88%) due to rebate volatility risk of breaking best price and Average Manufacturer Price impact. Medicaid sees worse misalignment for the 60% drug performance scenarios because of comparison to the statutory rebate (23.1%). CONCLUSION: The Multiple Best Prices approach has the lowest misalignment and could be applied to most chronic therapies, even rare ones.

Data for modelling US projections of product approvals, patients treated, and product revenues for durable cell and gene therapies.

The recent marketing approval of several durable gene and cell therapies (2017-2020), together with observations that 7,000 monogenic indications and many cancers were potential targets, led to concern about the potential economic impact of such therapies on the US healthcare system. Using a Markov chain Monte Carlo simulation model, driven stochastically by our estimates of the time in phase of clinical trials and each clinical trial phase probability of success, we forecast the pattern of future US regulatory approvals for such therapies currently undergoing clinical trials. Using parameters of those trials, such as inclusion and exclusion criteria, and other epidemiological data we estimate potential treatable patient populations and use these together with pricing estimates to forecast a range for the potential future list price product revenues associated with these therapies.

Durable cell and gene therapy potential patient and financial impact: US projections of product approvals, patients treated, and product revenues.

Durable cell and gene therapies potentially transform patient lives, but payers fear unsustainable costs arising from the more than 1000 therapies in the development pipeline. A novel multi-module Markov chain Monte Carlo-based model projects product-indication approvals, treated patients, and product revenues. We estimate a mean 63.5 (54-74 5th to 95th percentile range) cumulative US product-indication approvals through 2030, with a mean 93000 patients treated in 2030 generating a mean US$24.4 billion (US$17.0B-35.0B, US$73.0B extreme) list price product revenues not including ancillary medical costs or cost offsets. Thus, the likely dozens of durable cell and gene therapies developed through 2030 are unlikely to threaten US health system financial sustainability.

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.

Market access of gene therapies across Europe, USA, and Canada: challenges, trends, and solutions.

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.

Biosimilars And Follow-On Products In The United States: Adoption, Prices, And Users.

Biologic drugs account for a disproportionate share of the increase in pharmaceutical spending in the US and worldwide. Against this backdrop, many look to the expanding market for biosimilars-follow-on products to biologic drugs-as a vehicle for controlling pharmaceutical spending. This study explores the early years of entry of biosimilars and related follow-on products in the US. Using monthly sales data from the period 2005-19 for ten drug classes, we examine how quickly biosimilars/follow-on products gained market share and the subsequent trajectory of prevailing (national average invoice) prices. Our analysis suggests that although uptake has been slower than what is typically seen in generic drug markets, the most recent entrants have captured market share more rapidly than comparable earlier biosimilars/follow-on products. We also document that from biosimilar/follow-on products' time of entry, their lower prices help offset the overall trend in average annual reference-product price increases. Our findings can provide insight into future policy reforms aimed at increasing competition and use of biosimilars, leading to expanded patient access and significant cost savings.

Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers.

The potential to use biomarkers for identifying patients that are more likely to benefit or experience an adverse reaction in response to a given therapy, and thereby better match patients with therapies, is anticipated to have a major effect on both clinical practice and the development of new drugs and diagnostics. In this article, we consider current and emerging examples in which therapies are matched with specific patient population characteristics using clinical biomarkers - which we call stratified medicine - and discuss the implications of this approach to future product development strategies and market structures.

Translational Medicine Guide transforms drug development processes: the recent Merck experience.

Merck is implementing a question-based Translational Medicine Guide (TxM Guide) beginning as early as lead optimization into its stage-gate drug development process. Initial experiences with the TxM Guide, which is embedded into an integrated development plan tailored to each development program, demonstrated opportunities to improve target understanding, dose setting (i.e., therapeutic index), and patient subpopulation selection with more robust and relevant early human-based evidence, and increased use of biomarkers and simulations. The TxM Guide is also helping improve organizational learning, costs, and governance. It has also shown the need for stronger external resources for validating biomarkers, demonstrating clinical utility, tracking natural disease history, and biobanking.