ROI and Rare Disease: Retooling the ‘Gene’ Value Machine

Marc Blaustein, CFA, Senior Fellow

Kenneth Getz, MBA, Executive Director

Both with Tufts Center for the Study of Drug Development (CSDD)

The biopharmaceutical industry has a remarkable track record of innovation. The industry has made great strides addressing chronic medical needs, particularly for large patient populations. At the same time, powerful new insights into genetic causes of disease and new tools to impact these underlying causes present the opportunity to address previously untreatable diseases and deliver a new wave of transformative, potentially curative therapies.

Biopharma companies have delivered innovative medicines to address medical needs in such leading causes of morbidity and mortality as cardiovascular disease and cancer—which we now understand to be many different diseases, but where innovations such as checkpoint inhibitors have revolutionized treatment and outcomes for many different cancers. Two of the remaining large disease frontiers are central nervous system (CNS) and metabolic disease, but innovation with GLP-1 therapies appears to be changing the trajectory in metabolic disease.

As a result of previous biopharma innovation, an increasing proportion of unmet need and, therefore, industry focus is on rare and orphan diseases. Three factors, however, challenge the viability of traditional drug development and commercialization in these disease areas:

• Since many of the new rare disease treatments are genetic therapies, they are inherently restricted to a single indication with very limited opportunity for label expansion.
• The potential return on investment to develop new therapies for small patient populations runs counter to the increasing cost and risk of drug development and commercialization.
• Societal efforts to rein in rapidly rising healthcare costs, and particularly drug costs, limit the ability to recoup development investments.

As shown in Table 1 below, these pressures have already created a challenging economic environment for investments in innovative new therapies. There is a clear trend toward longer development times, lower peak sales as newer medicines target smaller patient populations, and a corresponding decrease in return on R&D investment in new drugs. To ensure continued investment in drug development, the industry needs solutions that address this challenge.

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This report focuses on the rapidly growing pipeline of gene therapies and the unprecedented challenges this will place on the traditional drug development paradigm. Importantly, the growing prominence of gene therapies provides a clear example of a broader industry trend: rising development and product costs for medicines targeting ever smaller patient populations.

In this article, we propose a framework to realign the relationship between risk and return in biopharma R&D for these innovative genetic medicines. This framework presents promising, emerging strategies designed to mitigate the risk and inefficiencies associated with protracted drug development timelines, increasing scientific and operating risk, high drug development and manufacturing costs, capacity constraints, and operational inefficiencies.

RARE DISEASE DRUGS: GROWING PIPELINE, GROWING CHALLENGES

Rare disease therapeutic development that was once the domain of small biotech and specialty pharma companies is now the domain of the broader biopharma industry. Accelerated regulatory pathways, significant areas of unmet medical need, and advances in genetic treatments have contributed to the attractiveness of this domain. Indeed, more than one-third of all drugs in global drug development now target rare diseases. Rare diseases now dominate the pipelines of many of the largest pharma companies

About one in 10 Americans, or more than 30 million people, suffer from a rare disease. Historically, there were therapies for only a limited number of rare diseases targeting only a limited total patient population. But as the industry increases its focus on rare diseases and applies new genetic insights and therapeutic modalities, addressing just a portion of these diseases could result in novel therapies for millions of new patients.

With few exceptions, genetic therapies intrinsically and uniquely target a single disease and are not tractable to label expansion in other, larger disease indications. Historically, label expansion to additional patient populations is a primary mechanism that generates the commercial returns required to support the high cost and risk of new drug development.

Genetic therapies by their nature often have a high fixed cost of goods, and this characteristic is exacerbated when they are targeted to a small patient population.The result is an increasing number of drugs that cost millions of dollars per patient (see Table 2).

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Sales of rare disease therapies are growing at twice the rate of those for non-rare diseases—12% annually vs. 6%. By 2026, rare and ultra rare disease treatments will make up an estimated 20% of all prescription sales as a large, robust pipeline of new drug approvals with orphan designations enter the marketplace (more than half of novel FDA drug and biologic approvals in 2023 received orphan designation).³

Small, targeted patient populations, coupled with substantial and growing costs for drug development are driving alarmingly higher per patient costs that will greatly tax our healthcare system. According to a 2023 analysis, rare disease treatments for an estimated 8.4 million people will cost our healthcare system $2.2 trillion dollars annually, approximately two-thirds of the $3.4 trillion pharmaceutical budget for 133 million people living with chronic diseases.⁴

Genetic therapies are the most visible example of this accelerating trend. Prescription drug sales for cell and gene therapies (CGTs), which disproportionately treat rare diseases, are expected to grow dramatically during the current decade. One recent estimate from Evaluate Pharma notes that whereas CGTs represented about 1% of prescription drug sales in 2022, CGTs will approach 15% of prescription drug sales by 2030. This represents a largely new, incremental cost to the healthcare system pharmaceutical budget.

The current trajectory for incremental drug costs from gene therapies for rare diseases is unsustainable. Yet it is vital to have a path forward for this new generation of drugs that can change health outcomes meaningfully in the subset of largely monogenic diseases amenable to these therapies.

Future generations of these therapies that have both an improved therapeutic index and are more cost-effective will attract investment only if at least some of this first-generation of therapies are commercially viable.

A FRAMEWORK FOR STRATEGIES TO CHANGE THE DRUG DEVELOPMENT PARADIGM

We propose here a set of solutions for the industry, regulators, patients, and payers that could contribute to an economically viable path forward for groundbreaking new drugs, particularly for rare diseases. These proposals aim to improve the economics of drug development and mitigate the financial burden on the healthcare system and society more broadly, while allowing development of transformative therapies to treat currently un- and under-treated rare diseases.

The framework seeks to identify emerging opportunities that hold promise for reducing risk and driving efficiency. Three broad strategic areas to optimize risk and efficiency are presented:

1. Strategies to reduce time-based risk (long cycle times).
2. Strategies to lower the cost of drug development (economic burden) for a single sponsor.
3. Strategies to reduce capacity constraints and labor-intensive development activity.

Table 3 (see below) provides a summary of strategies that we have identified, drawn from some of the most promising approaches now being applied and adopted. Each of these strategies holds promise in reducing the cost and risk of genetic therapies for rare diseases by one or more of these mechanisms: reducing time to market, reducing development and/or manufacturing cost, prioritizing the most promising drug candidates, allocating costs more equitably, and increasing probability of successful licensure and commercial return.

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Promising strategies to reduce timelines

Despite several decades of intense efforts to decrease the time, cost and risk of drug development, the biopharma industry has been unsuccessful. According to the Tufts Center for the Study of Drug Development, between 2005 and 2020, mean drug development durations increased by a full year to almost 92 months.

Effective existing therapies, increased pricing pressure, and greater competition mean that even drugs that receive regulatory approval may not be commercially successful, let alone recoup the investments made to bring them to market and allow the providers of risk capital to earn a reasonable return on an industry portfolio that will include many drugs that fail to reach the market.

Examples of individual company strategies

Simultaneous related-product approvals in different indications using aggregated clinical data. We propose allowing a sponsor developing multiple targeted drugs using a single technology backbone (e.g., a CRISPR technology with a common delivery platform and chemistry backbone but unique therapeutic cassettes targeted to different genes) to combine these drugs in a single, multi-disease trial. Relevant endpoints would be defined for each disease population, and a trial participant would be defined as a success if they met the predefined endpoint for their disease. Successes (and failures) as well as relevant adverse events across the entire population would be combined to determine whether the trial achieved statistical success. If yes, each of the products (for different diseases) would receive approval, with stringent requirements for post-approval market surveillance, which tends to be more feasible in rare diseases and with advanced therapies.

Enhanced reliance on post-marketing data and real-world experience/pragmatic trials. The post-approval market surveillance described could take the form of traditional Phase IV studies or else real-world experience/pragmatic trials. Companies would need to commit to withdraw drugs from the market that did not demonstrate efficacy with longer-term data.

Simultaneous related product approvals in different indications using aggregated manufacturing data. A similar approach as described for clinical data could accelerate manufacturing process approval and lower the cost of goods. One challenge with personalized medicine and genetic therapies particularly is the high cost of goods, which translates to high product prices. Not only must a company recoup the significant drug development costs from a small pool of treated patients once the product is marketed, but each dose—especially with current ex vivo approaches—can cost millions of dollars to manufacture and deliver.

We propose a solution analogous to the multi-product approach to late-stage clinical trials presented. In this case, where the same process is used to manufacture multiple products that are largely identical, save the target-specific element of the payload, after the process first receives regulatory approval for one indication, each similar process for a new indication would, for regulatory purposes, be treated as an identical process. Manufacturing suites for these very similar products housed in the same facility would be treated by regulators like additional suites for an already-approved product and process in the same facility.

This regulatory-driven approach could work synergistically with existing efforts, such as the manufacturing efficiency and cost efforts of the Bespoke Gene Therapy Consortium and the FDA’s existing Platform Technology Designation Program, to lower manufacturing costs of approved gene therapies.

Examples of multi-company and public/private cooperative strategies

There are limited resources available for drug development, and a significant cost borne by investors and society is for programs that ultimately fail to reach the market and patients. In today’s competitive drug development environment, there are typically multiple companies employing related technologies pursuing new therapies for the same indication. If one company’s program fails, another company’s similar program might fail for related reasons.

Sharing program failure data. We propose that companies share their program failure data with other companies or a third party (e.g., a patient advocacy group or regulatory authority) so that information can be shared with other companies developing similar products. This would allow other companies to terminate earlier in the development process those programs most likely to fail or attempt to address the cause of failure. If the shared data does allow a program to succeed, the successful company could pay some value (e.g., an appropriate product royalty) to the company that shared its data.

Promising strategies to lower the cost of drug development

Many personalized medicines are prohibitively expensive on a per-patient basis. This results both from high cost of goods and the need to generate an investment return on development costs from a small patient population. Genetic therapies that promise cures are both expensive and face a temporal challenge: the cost of the treatment is realized entirely up-front, while the benefits accrue over a lifetime of health and productivity. This latter challenge is uniquely acute in the US, where the system of employer-provided private insurance results in more than one-third of all patients switching health insurance providers each year. An employer and the associated health insurer are asked to bear the full cost of the treatment, but most of the benefit will be realized by other employers and insurers in subsequent years.

Insurers have many mechanisms (e.g., prior authorization requirements, increased copays) to manage the cost of expensive therapeutics. But the challenges of paying for multi-million-dollar curative therapies are unique. While all of us would like to see everyone have access to all potentially beneficial treatments, the reality is that healthcare is a finite resource and one facing significant cost containment pressure. The $3 million cost of a gene therapy treatment could alternatively fund a thousand patient-years of a $3,000 annual therapy.

Paying for uniquely expensive personalized therapies—which is necessary to ensure these products will be available to patients and new generations of these medicines will be developed—may require unique payment mechanisms. Already, payers and industry are implementing innovative payment mechanisms in which the cost of the drug is paid over multiple years; payments over time typically are dependent on continued efficacy.

Examples of individual company strategies

Shared cost with patients and payers. To promote equitable and widespread access to these therapies, additional novel payment strategies may be required. For example, recipients of these therapies could pay some limited percentage of income over a fixed number of years into a fund that would pay for the treatments and ensure they were available for future patients. Patients with fewer means and lower income would pay less than those of greater means. Like existing pay-over-time mechanisms, this approach would also help address the temporal misalignment resulting from a single treatment that generates benefits over a lifetime. In this scenario, if the therapy ceased to be effective, such payments would stop so risk is also borne by the drug manufacturer. These approaches could supplement other innovative risk-sharing payment mechanisms such as “corridor” agreements where payers pay the manufacturer different amounts if predefined efficacy limits are either exceeded or not achieved.

Shared risk with patients and payers. Patients receiving medicines that were approved based on limited data or other accelerated pathways, such as those suggested previously could sign a release, for example, the informed consent used in clinical trials, to limit the liability of manufacturers and payers. This could result in lower industry product liability costs and, therefore, lower overall costs for the therapies.

Examples of multi-company and public/private collaborative strategies

Public-private cooperative studies and registries. Some of our proposals result in increased reliance on post-marketing data. One mechanism to increase efficiency and lower the cost of generating this data is to have a single, indication-standard registry to gather clinician and patient experience, rather than duplicating this investment for multiple drugs from different sponsors. Such a common registry could be sponsored by a consortium of relevant companies, a patient association, or a form of public-private partnership (e.g., NIH financial support for a registry run by a multi-company consortium or patient advocacy association). This approach has benefits for clinicians and site staff, who only have to work with a single registry platform, and provides the opportunity to more directly compare outcomes with different therapies through a structured real-world evidence study.

Promising strategies to reduce capacity constraints and labor-intensive activity

The economics of personalized medicines and gene therapies for small patient populations and rare diseases are inherently challenging. These challenges are exacerbated when multiple companies develop similar drugs (e.g., gene therapies)
for the same disease. This is a common situation, as companies use similar metrics to determine which indications are most attractive.

Since costs of these therapies are so high, commercial viability cannot be assured. Having multiple, similar therapies vying for the same patient market exacerbates this challenge and likely results in lack of commercial viability for all but one or two—or perhaps any—products. Commercial failures of approved products increase perceived risk and result in less investment in the field. Less investment will prevent, or at least significantly delay, the fruits of breakthrough innovation reaching patients who might benefit.

Examples of individual company strategies

ROI-based portfolio management. We propose that companies rigorously and continuously apply ROI-based portfolio management, with an enhanced focus on competitive products in development. This should be an ongoing exercise, so additional information about competitive product development can be incorporated and companies can regularly evaluate which pipeline programs should be prioritized.

Platform technology investment. Another part of the solution would be to direct more investment to platform technologies with potential to fundamentally change the therapeutic index or economics of genetic therapies and other personalized medicines. Rather than investing in the nth gene therapy for a particular indication, scarce industry dollars might be better invested in technologies that can drive improved delivery (e.g., ex vivo to more economical in vivo delivery modalities) or significantly increase efficacy (e.g., through higher rates of targeted DNA changes or desirable protein expression). Allocating scarce risk capital to such platforms could lead to additional innovative therapies reaching more patients at lower prices.

QbD and risk-based quality management. Companies can prioritize the data collected in clinical development using quality by design (QbD) and risk-based quality management principles. One-hundred percent source data review and verification is highly labor intensive and unnecessary as sponsor companies have identified and prioritized data elements that are essential to demonstrating safety and efficacy. Clinical trials have grown increasingly complex, collecting more endpoints, which adds to both development time and cost. By applying QbD and risk-based quality management approaches, development time and cost may be reduced.

Examples of multi-company and public-private collaborative strategies

Umbrella trials. Perhaps the best way to select development candidates most likely to succeed is to evaluate them head-to-head in the same clinical trial, known as an umbrella trial. In this scenario, a consortium of companies (or some entity they created for the purpose) or a third party, such as a patient association, would run a clinical trial for multiple products targeting the same indication. This would allow evaluation of products in a directly comparable fashion and avoid duplication of many fixed costs associated with a clinical trial. The development candidate that performs best would be prioritized for further development and the sponsor(s) of the other product(s) in the trial would focus their resources on different products. An example of a similar approach in the rare disease space is the Scleroderma Research Foundation’s CONQUEST platform, on which drug candidates from different sponsors are evaluated using a common trial infrastructure and with a common control arm.

CONCLUDING THOUGHTS

Exciting biological insights and powerful new tools herald a new wave of medicines that can profoundly improve human health, potentially curing previously untreatable diseases. But these new therapies challenge the traditional drug development paradigm and the corresponding traditional risk-return relationship in drug development. Safe and effective new therapies may increasingly prove unaffordable and will, therefore, fail to be commercially viable.

The history of biotechnology is that innovation builds on innovation: a first wave of transformative therapies will be followed by subsequent generations that reach more patients and are more efficacious, safer, and economically attractive. But this pattern requires a first wave that is not only successful from a safety and efficacy perspective, but also commercially viable. Current trends suggest we may be heading for a scenario where too many high-cost genetic therapies target the same small patient populations. This could drive multiple commercial failures even from approved products with a favorable therapeutic index, resulting in a drying up of investment in the next generation of medicines.

We have proposed a framework and promising strategies to address the unique challenges of personalized and genetic therapies in rare diseases, set against a general backdrop of increasing drug development costs and declining ROI on drug development investments. We invite ideas and comments to this framework.

While implementation of these proposals will be challenging, we believe innovative approaches to investment, development and reimbursement are necessary to ensure success of this first wave of transformative therapies and drive investment in continued innovation.

Marc Blaustein, CFA, is Senior Fellow; and Kenneth Getz, MBA, is Executive Director; both with Tufts Center for the Study of Drug Development (CSDD)

References

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3. New Drug Therapy Approvals 2023. FDA. January 2024. https://www.fda.gov/media/175253/download?attachment

4. Andreu, P.; Karam, J.; Child, C.; Chiesi, G.; Cioffi, G. The Burden of Rare Diseases: An Economic Evaluation. Chiesi Global Rare Diseases. 2023. https://chiesirarediseases.com/assets/pdf/chiesiglobalrarediseases.whitepaper-feb.-2022_production-proof.pdf