By Claudia Dall’Osso, Ph.D., and Akash Saini, Ph.D., Decision Resources Group (DRG)
In Part 1 of this two-part article, we introduced, at a high level, the burgeoning gene therapy pipeline, and we covered key clinical development challenges facing companies in this arena. Here, we review lessons from Spark Therapeutics’ pivotal program for Luxturna, a gene therapy approved for the treatment of patients with retinal dystrophy associated with confirmed biallelic mutation in the RPE65 gene, and summarize key considerations for the clinical development and commercialization of gene therapies.
Lessons From The Clinical Development Of Spark Therapeutics’ Luxturna
Luxturna’s pivotal clinical program highlights several successful solutions to key clinical development challenges facing gene therapy developers working on monogenic rare diseases. To bring the agent to market, Spark and academic collaborators developed and validated a novel outcome metric measuring functional vision and conducted a study to collect natural history data in Luxturna’s target patient population, and the company included control patients in the small, open-label Phase 3 study.
The multi-luminescence mobility test (MLMT) evaluates the ability of a subject to navigate an obstacle course at varying light levels. The end point was validated in a one-year prospective trial conducted with 26 enrollees with normal vision and 28 participants diagnosed with an inherited retinal dystrophy. The MLMT reliably distinguished between subjects with normal vision and those with vision impairment, and was able to measure decline in visual function in patients across repeat visits over the course one year.1 Although interviewed ophthalmologists and payers generally hold a positive perception of Luxturna’s efficacy based on the MLMT data, the impact of treatment on real-world activities of daily living remains uncertain (e.g., ability to read, work).
To supplement their data package and contextualize the treatment benefit conferred by Luxturna, Spark also conducted a retrospective chart review of 70 patients in Luxturna’s target population — patients with confirmed biallelic RPE65 mutations. The data highlights the sizable and progressive decline in visual acuity and visual field size as a function of age, with the threshold for legal blindness generally crossed by age 20.2
Importantly, the pivotal Phase 3 trial for Luxturna, although small in size, included a control arm to establish the statistical significance of the agent’s impact on the MLMT primary end point. After one year, the nine control patients were able to cross over into the active treatment arm. According to Spark, the pstudy was the first successful Phase 3 randomized controlled trial of a gene therapy.3
Commercialization And Market Access Challenges For Gene Therapies In Rare Diseases
As incentive to invest in the development of an innovative gene therapy for a small rare disease population, marketers desire and seek a high price point. But, they must present a compelling case for the value of their novel medication and must operate within the confines of payer budgets. Numerous factors can influence the value discussion for a gene therapy, including the durability of the treatment effect and the reduction in medical costs associated with the management of the disease in question. Furthermore, although many monogenic rare diseases have a pediatric onset and may confer a tremendous burden on parents and caregivers — financial and otherwise — these indirect costs are not normally absorbed by payers, and their integration into the value discussion remains a topic of debate.
In our research, U.S. payers stress two key factors influencing the decision to reimburse a gene therapy: budget impact and cost-effectiveness. Budget impact is usually determined at the plan level; a payer’s goal is to estimate how the added expense of reimbursing the gene therapy will impact their members’ premiums for the following year. Although cost-offsets may be realized as a result of a decrease in medical expenses that accompany the use of the gene therapy, some U.S. payers contend such offsets are most compelling when realized within the same year they incur the cost of the gene therapy. In single-payer systems (e.g., national health authorities in European markets), where organizations are responsible for the health coverage of a patient over the long-term, interviewed payers reported cost-offsets play a larger role, as cost savings can more comfortably be integrated over time.
The key goal of a cost-effectiveness analysis is to ensure novel therapies deliver utility — the total benefit patients gain from therapy, often measured in quality-adjusted life-years (QALYs) — commensurate with their price, which should meet a market-specific cost per QALY threshold. These evaluations are challenging to conduct, even in non-rare diseases, and payers may rely on assessments from a third party such as the Boston-based Institute for Clinical and Economic Review (ICER) in the U.S. and the National Institute for Health and Care Excellence (NICE) in the United Kingdom. In ultra-rare diseases, the discussion around the fairest means to assess value continues to evolve.
Lessons From The Value Discussion Around Luxturna
Luxturna launched in the U.S. at a cost of $850,000 ($425,000 per eye)—below the expectations of some analysts but in excess of the price necessary to meet standard cost-effectiveness thresholds ($100,000 to $150,000/QALY) in most iterations of an ICER analysis.4
ICER’s review of Luxturna underscored the key data gaps that may impact cost-effectiveness analyses of a trailblazing gene therapy. For instance, although the clinical trials featured MLMT as the primary outcome metric, the same is not true for ICER’s cost-effectiveness analysis. Owing to the novelty of the MLMT metric, there was no available data to correlate the MLMT results with the benefit/utility patients are expected to derive from the therapy. As a result, visual acuity and visual field, on which Luxturna delivered more modest clinical gains, had to be used in place of MLMT. Furthermore, the utility curve used to correlate visual acuity with a given utility was derived, of necessity, using data based on other patient populations, owing to the lack of data specifically in Luxturna’s target patient population.
One key unanswered question in the analysis relates to onset of treatment; owing to the progressive nature of the disease, younger patients (i.e., age 3) would gain a larger health benefit and, thus, support a higher price point for Luxturna. However, it is unclear if patients could be reliably diagnosed as toddlers, especially considering that a segment of patients presents with late onset. As such, payers may be unwilling to accept the analysis assuming treatment at age 3.
The durability of treatment benefit was another point of contention in the evaluation of Luxturna’s cost-effectiveness; Spark has follow-up data from a Phase 1 trial supporting an efficacy duration of four years but believes Luxturna’s benefits could persist much longer, possibly over a lifetime. However, ICER’s health economists rely only on published data and therefore assumed a duration of 10 years, followed by another 10 years of progressive loss of function. Only time will tell whether the durability assumption used in the analysis reflects reality.
Key Considerations For Developers
More than 100 gene therapy programs are now advancing in the pipeline, and more than half of these programs have yet to establish clinical proof-of-concept. As developers chart a course to market for their innovative medications, key decisions are necessary across the product life cycle.
Target disease: If the target population size does not enable recruitment of enough patients for a control arm or a robust statistical analysis, take steps to collect natural history data in line with FDA recommendations. Developers should also consider features such as accessibility of target tissue and the need for systemic administration. The burden of proof for the safety of systemically-administered gene therapies may require a more extensive safety characterization in the preclinical or early-clinical stages of development.
Trial design: Data from pivotal clinical trials of a gene therapy ideally secures buy-in from regulators, payers, and treating physicians. If a novel end point is necessary, get input from key stakeholders as early as possible and design a study to validate the new metric appropriately. When the efficacy gains expected in a trial are more modest, developers should strive to have as large a clinical trial as possible and include a control arm; in situations where this is less feasible, objective outcome metrics should be used that, ideally, align with available historical control data.
Market access: The conversation on appropriate market access coverage in rare diseases is still evolving. However, developers should be prepared to demonstrate how performance on clinical trial end points translates to clinically meaningful outcomes and, ultimately, utility to patients (i.e., QALYs). Key sticking points include the onset and durability of treatment benefits in cost-effectiveness analyses. As we’ve seen for Luxturna, the intuitive appeal of a potential one-time cure must be backed by clinical data supporting long-lasting efficacy — otherwise, pricing and reimbursement may suffer.
About The Authors:
Claudia Dall’Osso, Ph.D., is a principal business insights analyst on the Infectious, Niche, and Rare Diseases team at Decision Resources Group, specializing in niche and rare indications. Before joining DRG, she held a management and strategy consultant position at Precision Medicine Group, where she worked for clients in the biopharmaceutical, medical, device and diagnostic industries. Dall’Osso completed her master’s in management at Harvard University; she also holds a Ph.D. in medical genetics from Brescia University in Italy and a B.S./M.S. degree in medical biotechnology from the University of Milano in Italy. You can reach her at firstname.lastname@example.org or connect with her on LinkedIn.
Akash Saini, Ph.D., is a lead analyst with the Infectious, Niche, and Rare Diseases team at Decision Resources Group, where he specializes in a diverse group of rare diseases. He received his Ph.D. in biochemistry and biotechnology from the International Centre for Genetic Engineering and Biotechnology (ICGEB) New Delhi in India and his M.Sc. in biotechnology from Jawaharlal Nehru University, also in India. Prior to joining Decision Resources Group, Saini was a postdoctoral fellow at the University of Massachusetts Medical School, where he studied mitochondrial dysfunction in amyotrophic lateral sclerosis (ALS). You can reach him at email@example.com or connect with him on LinkedIn.