How to select optimal endpoints for rare disease trials

Selecting the right endpoints to establish clinical benefit is one of the most challenging aspects of rare disease drug development. The starting point for determining relevant and sensitive efficacy endpoints is understanding the etiology of the disease and the drug’s precise mechanism of action (MOA). But with rare and ultra-rare diseases, often little is known about the condition’s natural course, and the experimental agent’s MOA may not be fully elucidated. Patients are often difficult to locate, making it hard to power a study adequately enough to measure treatment effects.

Identifying the optimal endpoints for rare and ultra-rare diseases takes a lot of work. Based on my experiences in this fast-evolving field, I can offer some advice on how best to do it:

Seek optimal endpoints, not just relevant or convenient ones

In my experience working with sponsors, they often face a situation where there are many possible endpoints, but it’s unclear which are the most meaningful. In this scenario, the task is to identify the optimal endpoints. Recently, a sponsor approached us with a complex case: they were developing a treatment for a rare autoimmune disorder with progressive neurologic phenotypes affecting patients’ motor function. This chronic condition systematically damages the peripheral nervous system, offering many potential objective and subjective endpoints to measure the impact of the drug on the loss or alteration of function. But which endpoints were optimal clinically and statistically? And which were the most meaningful to patients? There is no gold standard for endpoints in this disease. 

We took a multidisciplinary approach to solve the dilemma. Our medical experts interviewed key opinion leaders (KOLs) on scientific and medical aspects of the disease, conducted a thorough review of published literature, and analyzed the briefing documents of approved drugs in similar indications and information about failed drugs. After exhaustive due diligence, we proposed a data-driven set of clinical endpoints optimized for the experimental agent. The sponsor is incorporating these into the trial protocol. 

To find the optimal endpoints for a rare disease trial, conduct thorough and cross-disciplinary due diligence on the condition. Endpoint selection should be science- and data-driven and reflect patients’ priorities whenever possible. Don’t settle for relevant or convenient endpoints; they may not be optimal.

Parse the rare disease patient population thoroughly

One of the most common problems I encounter working in rare diseases is the lack of a thorough, in-depth scientific understanding of the condition’s genetic target and complex mutation profiles. This can lead to treating the wrong patient group because of insufficient patient subcategorization or suboptimal biomarker testing. 

For example, research shows that more than 80 percent of rare diseases are genetic, and about 50 percent affect infants and children. In this setting, endpoints often need to be customized by age group and genotype or phenotype. And companies should stratify the patient population: for example, patients under two years old, patients aged 3 to 12, and adolescents represent heterogeneous subpopulations that may require different age-appropriate endpoints and cutoffs. Further, patients in different age groups suffering from a rare disease will be at different stages of disease progression and likely harbor different subtypes of genetic profiles. 

Endpoint selection needs to proceed from a thorough understanding of the heterogeneity of patients and disease expression across different age groups that will be studied in a trial. For example, recently, we worked with a sponsor developing a gene therapy for a rare musculoskeletal disease. The due diligence assessment revealed that the rate of ambulatory decline varies for these patients by mutational subgroup. We collaborated with the sponsor to establish different clinical endpoints, cutoffs, and biomarkers tailored to the targeted patient subgroups in the study.

Further, how feasible and practical will it be to capture and assess the chosen endpoints in each age group at investigative sites, clinics, or remotely? The answer is critical to endpoint selection in clinical study design and in quality implementation. 

NICHD Rare Disease Research

SOURCE: https://www.nichd.nih.gov/newsroom/resources/spotlight/020116-rare-disease-day

Work with regulators to co-develop and validate endpoints

Sometimes, developers face a situation where there are no verified endpoints or existing measures of a disease due to its rarity. In this scenario, they will need to develop a novel endpoint, defined as one which has never been used to support drug approval or has been substantially modified from existing ones.

Fortunately, regulators understand that developers struggle to identify and validate endpoints in rare and ultra-rare diseases. In October 2022, the FDA launched its Rare Disease Endpoint Advancement (RDEA) Pilot Program to support novel endpoint development and help sponsors qualify endpoints that have “never been used to support drug approval.” About five months earlier, the agency launched its Accelerating Rare disease Cures program (ARC), which also addresses endpoint selection, among other challenges.

The RDEA pilot program represents an excellent opportunity for developers with an active pre-investigational new drug (IND) or IND program for a rare disease that want to use novel endpoints. They can submit their proposal for an opportunity to work closely with regulators and benefit from advisory discussions and direct advice from the FDA. The agency may also consider endpoint proposals for a natural history study if it is to be conducted in a rare disease or for a common disease if there is sufficient justification that the endpoint could apply to a rare disease. Proposal submissions will start on July 1, 2023, and only one applicant per quarter, up to a maximum of three per year, will be selected through 2027. This pilot initiative offers a new pathway that envisions sponsors collaborating with regulators, patient groups, thought leaders, and other stakeholders to drive novel endpoint development.

Conduct correlation analyses to validate a novel biomarker or endpoint

In rare diseases, many endpoints, such as patient-reported outcomes (PROs) for how a patient feels or functions, are subjective. In contrast, a biomarker endpoint is an objective measure. At Parexel, we conduct biomarker and endpoint evaluation and qualification. For example, correlation analyses between the biomarker and subjective measures can assess whether either or both are valid for rare diseases and rare types of common diseases. Correlation analyses require computational biologists and statistical geneticists who understand the biomarker data, genetics, and clinical conditions. Often, the data are "dirty" and incomplete, complicating the analysis. But these analyses are crucial to validating biomarkers or endpoints: developing a treatment using a non-validated biomarker will likely end in regulatory failure.

At Parexel, we have successfully conducted biomarker and endpoint evaluation and development in clinical trials. Over the past 18 months, our biomarker and genomic medicine team has supported more than 300 biomarker and endpoint analysis projects for sponsors, ranging from genetics-genomics assessments to biomarker-endpoint analyses and validation. Recently, we helped a sponsor select and assess candidate biomarkers for their drug development program. Our findings established the value of and evidence for an objective surrogate biomarker endpoint in disease progression monitoring and drug responses.

Endpoint selection needs to proceed from a thorough understanding of the heterogeneity of patients and disease expression across different age groups that will be studied in a trial.

Angela Qu, M.D., Ph.D.
Senior Vice President of Biomarker Genomic Medicine, Parexel International

In our biomarker genomic medicine practice, we start the conversation very early with large pharma and emerging biotech sponsors. Often we begin with a one-page study concept for a clinical trial protocol and add design features using a data-and evidence-based approach. We leverage natural history data, registry data, genomic and biomarker data, and real-world evidence to compile all the knowledge available for the study design and endpoint selection. To overcome the obstacles because of different rules about accessing data in non-U.S. countries, we also increasingly access data through partnerships, fee-for-service arrangements, electronic medical record databases, and data mining to add insights to biomarker and patient selection.

Contributing Expert