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

A Systematic Review of Challenges and Opportunities in the Implementation of Managed Entry Agreements for Advanced Therapy Medicinal Products

PURPOSE

Managed Entry Agreements (MEAs) are agreements between firms and competent authorities for pricing and reimbursement, designed to enable coverage of new medicines while managing uncertainties around their financial impact or performance. Although these agreements can facilitate patient access, their complexity and costs seem to dampen enthusiasm for implementation. Nevertheless, MEAs remain a potential route, particularly for high-cost drugs with uncertain value claims. Given their pivotal role in bridging Advanced Therapy Medicinal Products (ATMPs) to patients, their foreseeable future implementation calls for a specific investigation of their associated challenges and opportunities. Therefore, this work aims to identify challenges and opportunities in implementing MEAs specifically for ATMPs.

METHODS

A systematic literature review was conducted on PubMed, MEDLINE, Scopus, and Google Scholar, based on the updated Preferred Reporting Items for Systematic Review and Meta-Analysis. This has been supplemented by a snowball search. Through the thematic content analysis, opportunities and challenges were identified and grouped into themes and subthemes. Afterward, the subgroup analysis was performed to investigate challenges and opportunities with outcome-based agreements (OBAs) versus financial-based agreements (FBAs), jurisdiction, and ATMP type.

FINDINGS

Of the 787 peer-reviewed articles, 42 met the inclusion criteria. Challenges and opportunities were clustered into the mentioned themes: evidence generation and data management, financial and reimbursement, administration and resources, negotiation, and governance, law, and regulations. Of note, no specific challenges or opportunities were found to be cell- or gene-therapy-specific, but certain challenges seem amplified for ATMPs. Several differences emerged per MEA type and jurisdiction. OBAs are described to reward innovative and effective treatments and boost research and development (R&D) returns. FBAs improve cost-effectiveness ratios but can negatively affect curative ATMP's revenues. Still, their versatility facilitates payer engagement in MEA combinations (eg, OBA with spread payments). The US decentralized health care system reported additional implementation challenges to OBAs. Each payer internally decides on reimbursement, and coordination among private payers is hindered by antitrust law. Yet, a new Cell and Gene Therapy Access model has been proposed. This would allow manufacturers to negotiate OBAs directly with the Centers for Medicare & Medicaid Services avoiding individual negotiation with each state. In Europe, there is an evident interest in implementing spread payments, yet accounting rules currently hamper their implementation.

IMPLICATIONS

This work offers insights into challenges and opportunities in MEAs implementation for ATMPs by investigating differences in MEA types and jurisdictions. Our findings provide significant insights that may help move successful MEA implementation forward, improving patient access to ATMPs.

Drivers of innovation value: simulation for new drug pricing evaluation based on system dynamics modelling

Objectives

Paying for the innovative value of drugs is an important means of mitigating healthcare system duplication and enhancing patient health. Assessing and exploiting the factors influencing innovation premium to forecast trends and shortcomings within the pharmaceutical innovation ecosystem.

Methods

Utilizing system dynamics, this research constructs a decision evaluation system for new drug pricing in Japan. It integrates various decision-making factors across dimensions such as value premium, marketability premium, pediatric premium, and SAKIGAKE premium, employing Vensim PLE software for simulation purposes.

Results

Under the current policy framework, pharmaceutical innovation is on the rise, with significant policy effects observable after 5 years. The most substantial growth in value occurs in medications for rare diseases and niche markets, with effects varying in the short to medium term and stabilizing over the long term. Sensitivity analysis highlights that factors like combination therapies, faster mechanisms of action, and novel therapeutic parts notably influence the value dimension. Other significant factors include obtaining national certifications, addressing indications lacking standard treatments, and demonstrating superior efficacy. The study also identifies underexploited opportunities related to the use of evidence in pricing decisions.

Conclusion

Clinical outcomes are pivotal in shaping drug pricing, influencing both patient and healthcare provider preferences, and thereby affecting market uptake and competitive dynamics. Regulatory frameworks that prioritize unmet medical needs or superior drug efficacy are essential. Future enhancements to the model should incorporate more real-world evidence and expand regulatory considerations to better reflect the dynamic nature of the healthcare sector and support equitable, outcome-based drug pricing.

Managed Entry Agreements for High-Cost, One-Off Potentially Curative Therapies: A Framework and Calculation Tool to Determine Their Suitability

OBJECTIVE

To construct a framework and calculation tool to compare the consequences of implementing different payment models for high-cost, one-off potentially curative therapies and enable decision making to ultimately enhance timely patient access to innovative health interventions.

METHODS

A framework outlining steps to determine potentially suitable payment models was developed. Based on the framework, a supporting calculation tool operationalised as an Excel-based model was constructed to quantify the associated costs for an average patient during the timeframe of the intended payment agreement, the total budget impact and associated benefits expressed in quality-adjusted life-years for the total expected lifetime of the patient population. To demonstrate the potential of the framework, three case studies were used: onasemnogene abeparvovec (Zolgensma®), brexucabtagene autoleucel (Tecartus®) and etranacogene dezaparvovec (Hemgenix®). A hypothetical case study was used to illustrate the output of the calculation tool.

RESULTS

Part 1 of the framework presents steps for matching a suitable reimbursement and payment model with the disease and treatment characteristics. The reimbursement and payment models are further specified in Part 2. Part 3 guides end users through the setup of a calculation tool with which the financial impact can be calculated of two payment models: a price discount model and an outcome-based spread payment model with a discount. Part 4 concerns the output of the calculation tool, showing how different payment models lead to different financial consequences under three assumptions of longer term effectiveness.

CONCLUSIONS

The presented framework provides decision makers with insight into the financial consequences of their chosen payment model under different assumptions. This can aid reimbursement negotiations by clarifying the optimal choice given a therapy's characteristics.

Illustrating the Financial Consequences of Outcome-Based Payment Models From a Payers Perspective: The Case of Autologous Gene Therapy Atidarsagene Autotemcel (Libmeldy®)

OBJECTIVES

To illustrate the financial consequences of implementing different managed entry agreements (managed entry agreements for the Dutch healthcare system for autologous gene therapy atidarsagene autotemcel [Libmeldy]), while also providing a first systematic guidance on how to construct managed entry agreements to aid future reimbursement decision making and create patient access to high-cost, one-off potentially curative therapies.

METHODS

Three payment models were compared: (1) an arbitrary 60% price discount, (2) an outcome-based spread payment with discounts, and (3) an outcome-based spread payment linked to a willingness to pay model with discounts. Financial consequences were estimated for full responders (A), patients responding according to the predicted clinical pathway presented in health technology assessment reports (B), and unstable responders (C). The associated costs for an average patient during the time frame of the payment agreement, the total budget impact, and associated benefits expressed in quality-adjusted life-years of the patient population were calculated.

RESULTS

When patients responded according to the predicted clinical pathway presented in health technology assessment reports (scenario B), implementing outcome-based reimbursement models (models 2 and 3) had lower associated budget impacts while gaining similar benefits compared with the discount (scenario 1, €8.9 million to €6.6 million vs €9.2 million). In the case of unstable responders (scenario C), costs for payers are lower in the outcome-based scenarios (€4.1 million and €3.0 million, scenario 2C and 3C, respectively) compared with implementing the discount (€9.2 million, scenario 1C).

CONCLUSIONS

Outcome-based models can mitigate the financial risk of reimbursing atidarsagene autotemcel. This can be considerably beneficial over simple discounts when clinical performance was similar to or worse than predicted.

[Personalized medicine in oncology]

Due to the considerable technological progress in molecular and genetic diagnostics as well as increasing insights into the molecular pathogenesis of diseases, there has been a fundamental paradigm shift in the past two decades from a "one-size-fits-all approach" to personalized, molecularly informed treatment strategies. Personalized medicine or precision medicine focuses on the genetic, physiological, molecular, and biochemical differences between individuals and considers their effects on the development, prevention, and treatment of diseases. As a pioneer of personalized medicine, the field of oncology is particularly noteworthy, where personalized diagnostics and treatment have led to lasting change in the treatment of cancer patients in recent years. In this article, the significant change towards personalized treatment concepts, especially in the field of personalized oncology, will be discussed and examined in more detail.

Delivering the precision oncology paradigm: reduced R&D costs and greater return on investment through a companion diagnostic informed precision oncology medicines approach

BACKGROUND

Precision oncology medicines represent a paradigm shift compared to non-precision oncology medicines in cancer therapy, in some situations delivering more clinical benefit, and potentially lowering healthcare costs. We determined whether employing a companion diagnostic (CDx) approach during oncology medicines development delivers effective therapies that are within the cost constraints of current health systems. R&D costs of developing a medicine are subject to debate, with average estimates ranging from $765 million (m) to $4.6 billion (b). Our aim was to determine whether precision oncology medicines are cheaper to bring from R&D to market; a secondary goal was to determine whether precision oncology medicines have a greater return on investment (ROI).

METHOD

Data on oncology medicines approved between 1997 and 2020 by the US Food and Drug Administration (FDA) were analysed from the Securities and Exchange Commission (SEC) filings. Data were compiled from 10-K, 10-Q, and 20-F financial performance filings on medicines' development costs through their R&D lifetime. Clinical trial data were split into clinical trial phases 1-3 and probability of success (POS) of trials was calculated, along with preclinical costs. Cost-of-capital (CoC) approach was applied and, if appropriate, a tax rebate was subtracted from the total.

RESULTS

Data on 42 precision and 29 non-precision oncology medicines from 56 companies listed by the National Cancer Institute which had complete data available were analysed. Estimated mean cost to deliver a new oncology medicine was $4.4b (95% CI, $3.6-5.2b). Costs to bring a precision oncology medicine to market were $1.1b less ($3.5b; 95% CI, $2.7-4.5b) compared to non-precision oncology medicines ($4.6b; 95% CI, $3.5-6.1b). The key driver of costs was POS of clinical trials, accounting for a difference of $591.3 m. Additional data analysis illustrated that there was a 27% increase in return on investment (ROI) of precision oncology medicines over non-precision oncology medicines.

CONCLUSION

Our results provide an accurate estimate of the R&D spend required to bring an oncology medicine to market. Deployment of a CDx at the earliest stage substantially lowers the cost associated with oncology medicines development, potentially making them available to more patients, while staying within the cost constraints of cancer health systems.

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.

When Reality Does Not Meet Expectations-Experiences and Perceived Attitudes of Dutch Stakeholders Regarding Payment and Reimbursement Models for High-Priced Hospital Drugs

This study aimed to identify the current experiences with and future preferences for payment and reimbursement models for high-priced hospital therapies in the Netherlands, where the main barriers lie and assess how policy structures facilitate these models. A questionnaire was sent out to Dutch stakeholders (in)directly involved in payment and reimbursement agreements. The survey contained statements assessed with Likert scales, rankings and open questions. The results were analyzed using descriptive statistics. Thirty-nine stakeholders (out of 100) (in)directly involved with reimbursement decision-making completed the survey. Our inquiry showed that currently financial-based reimbursement models are applied most, especially discounts were perceived best due to their simplicity. For the future, outcome-based reimbursement models were preferred, particularly pay-for-outcome models. The main stated challenge for implementation was generating evidence in practice. According to the respondents, upfront payments are currently implemented most often, whereas delayed payment models are preferred to be applied more frequently in the future. Particularly payment-at-outcome-achieved models are preferred; however, they were stated as administratively challenging to arrange. The respondents were moderately satisfied with the payment and reimbursement system in the Netherlands, arguing that the transparency of the final agreements and mutual trust could be improved. These insights can provide stakeholders with future direction when negotiating and implementing innovative reimbursement and payment models. Attention should be paid to the main barriers that are currently perceived as hindering a more frequent implementation of the preferred models and how national policy structures can facilitate a successful implementation.

Prognostication in inflammatory bowel disease

Personalized care in inflammatory bowel diseases (IBD) hinges on parsing the heterogeneity of IBD patients through prognostication of their disease course and therapeutic response to allow for tailor-made treatment and monitoring strategies to optimize care. Herein we review the currently available predictors of outcomes in IBD and those on the both near and far horizons. We additionally discuss the importance of worldwide collaborative efforts and tools to support clinical use of these prognostication tools.