A call for an integrated approach to improve efficiency, equity and sustainability in rare disease research in the United States

Clinical trial evidence supporting FDA approval of novel orphan drugs between 2017 and 2023

Characterization analysis of 87 pivotal clinical trials for 72 novel orphan drugs (76 orphan indications) approved by the FDA from 2017 to 2023 revealed that the clinical trial evidence supporting FDA orphan drug approvals often lacked high-quality designs, which frequently did not incorporate randomization, blinding, placebo or no treatment control, or clinical endpoint-driven methodologies. Additionally, regulatory flexibility was observed in the quantity of clinical trial evidence required, which included choices such as a single trial plus confirmatory evidence, one large multicenter trial or at least two trials. Furthermore, the overall strength of the clinical trial evidence exhibited variations across different orphan drugs and indications, influenced by features such as the therapeutic area and whether the orphan drug was granted accelerated approvals.

High-throughput assays to assess variant effects on disease

Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.

Application of long read sequencing in rare diseases: The longer, the better?

Rare diseases encompass a diverse group of genetic disorders that affect a small proportion of the population. Identifying the underlying genetic causes of these conditions presents significant challenges due to their genetic heterogeneity and complexity. Conventional short-read sequencing (SRS) techniques have been widely used in diagnosing and investigating of rare diseases, with limitations due to the nature of short-read lengths. In recent years, long read sequencing (LRS) technologies have emerged as a valuable tool in overcoming these limitations. This minireview provides a concise overview of the applications of LRS in rare disease research and diagnosis, including the identification of disease-causing tandem repeat expansions, structural variations, and comprehensive analysis of pathogenic variants with LRS.

Qualified placebo for trials of herbal medicine treatment in rare diseases? A cross-sectional analysis

BACKGROUND

While substantial placebos have been used in herbal medicine (HM) clinical trials for rare diseases, the use and quality of reporting of HM-placebo remain unclear. We aim to describe the use of HM-placebo in clinical trials for rare diseases and determine the quality of reporting in these trials.

METHODS

This is a cross-sectional study. We searched PubMed, Embase, Web of Science, SinoMed, China National Knowledge Infrastructure, WanFang database, China Science and Technology Journal Database, National Institute of Informatics Support Academic Information Services, ClinicalTrials.gov and Chinese Clinical Trials Registry from their inception date to 14 February 2023 to identify registered and published trials that use placebos as a comparator in rare diseases. We collected data on placebo use reporting and the efficacy and safety of placebo. Descriptive statistics, the Chi-square test, and Binary multivariable logistic regression analysis were used to determine the placebo characteristics of the HM trial and its effect on reporting.

RESULTS

Among the 55 studies, we included that with a median administration time of placebo of 84 days (IQR 42-180) and a median placebo sample size of 30 (IQR 24-54). About half of the trials (27, 49.1%) did not provide their ethical approvals, and one trial had details of informed consent. None of the studies were fully reported and more than half of the items reported less than 50%. A total of 10 trials (18.2%) of placebo has active ingredients even though none of them performed pharmacological inert tests. Of the 29 studies with available data on adverse events, 5 (17.2%) trials did not show a better safety profile in the placebo group. Under the context that a relatively high-quality report is defined as a report with more than 9 items, there was a statistically significant difference between the two groups in the rate of relatively high-quality reports of the administration time (p = 0.047, OR 0.10, 95% CI 0.01 to 0.90), but the results are not representative.

CONCLUSION

The overall situation of HM-placebo in the field of rare diseases was poor. In particular, the placebo is tied to the quality of trials, and poor placebo hinders the generation of high-quality evidence for herbal clinical trials in the field of rare diseases. We summarize the current methods of assessment involved in the use of placebos and propose various considerations for placebos in different contexts. Our study can greatly promote rare disease researchers to review the quality of their placebo and clinical trials. It is imperative to guarantee that meticulously conducted research generates clinical evidence of the highest caliber. We also expect that in the future, more rigorous relevant standards about the reporting and design of HM-placebo will be developed. High-quality clinical trials are the prerequisite for the wide clinical application of herbal medicines for rare diseases.

Outcome Measures and Biomarkers for Clinical Trials in Hereditary Spastic Paraplegia: A Scoping Review

Hereditary spastic paraplegia (HSP) is characterized by progressive lower limb spasticity. There is no disease-modifying treatment currently available. Therefore, standardized, validated outcome measures to facilitate clinical trials are urgently needed. We performed a scoping review of outcome measures and biomarkers for HSP to provide recommendations for future studies and identify areas for further research. We searched Embase, Medline, Scopus, Web of Science, and the Central Cochrane database. Seventy studies met the inclusion criteria, and eighty-three outcome measures were identified. The Spastic Paraplegia Rating Scale (SPRS) was the most widely used (27 studies), followed by the modified Ashworth Scale (18 studies) and magnetic resonance imaging (17 studies). Patient-reported outcome measures (PROMs) were infrequently used to assess treatment outcomes (28% of interventional studies). Diffusion tensor imaging, gait analysis and neurofilament light chain levels were the most promising biomarkers in terms of being able to differentiate patients from controls and correlate with clinical disease severity. Overall, we found variability and inconsistencies in use of outcome measures with a paucity of longitudinal data. We highlight the need for (1) a standardized set of core outcome measures, (2) validation of existing biomarkers, and (3) inclusion of PROMs in HSP clinical trials.

Committing to genomic answers for all kids: Evaluating inequity in genomic research enrollment

PURPOSE

Persistent inequities in genomic medicine and research contribute to health disparities. This analysis uses a context-specific and equity-focused strategy to evaluate enrollment patterns for Genomic Answers for Kids (GA4K), a large, metropolitan-wide genomic study on children.

METHODS

Electronic health records for 2247 GA4K study participants were used to evaluate the distribution of individuals by demographics (race, ethnicity, and payor type) and location (residential address). Addresses were geocoded to produce point density and 3-digit zip code maps showing local and regional enrollment patterns. Health system reports and census data were used to compare participant characteristics with reference populations at different spatial scales.

RESULTS

Racial and ethnic minoritized and populations with low-income were underrepresented in the GA4K study cohort. Geographic variation demonstrates inequity in enrollment and participation among children from historically segregated and socially disadvantaged communities.

CONCLUSION

Our findings illustrate inequity in enrollment related to both GA4K study design and structural inequalities, which we suspect may exist for similar US-based studies. Our methods provide a scalable framework for continually evaluating and improving study design to ensure equitable participation in and benefits from genomic research and medicine. The use of high-resolution, place-based data represents a novel and practical means of identifying and characterizing inequities and targeting community engagement.

Rare Disease, Advocacy and Justice: Intersecting Disparities in Research and Clinical Care

Rare genetic diseases collectively impact millions of individuals in the United States. These patients and their families share many challenges including delayed diagnosis, lack of knowledgeable providers, and limited economic incentives to develop new therapies for small patient groups. As such, rare disease patients and families often must rely on advocacy, including both self-advocacy to access clinical care and public advocacy to advance research. However, these demands raise serious concerns for equity, as both care and research for a given disease can depend on the education, financial resources, and social capital available to the patients in a given community. In this article, we utilize three case examples to illustrate ethical challenges at the intersection of rare diseases, advocacy and justice, including how reliance on advocacy in rare disease may drive unintended consequences for equity. We conclude with a discussion of opportunities for diverse stakeholders to begin to address these challenges.

Individualized interventions for rare genetic conditions and the research-treatment spectrum: Stakeholder perspectives

PURPOSE

Advances in the study of ultrarare genetic conditions are leading to the development of targeted interventions developed for single or very small numbers of patients. Owing to the experimental but also highly individualized nature of these interventions, they are difficult to classify cleanly as either research or clinical care. Our goal was to understand how parents, institutional review board members, and clinical geneticists familiar with individualized genetic interventions conceptualize these activities and their implications for the relationship between research and clinical care.

METHODS

We conducted qualitative, semi-structured interviews with 28 parents, institutional review board members, and clinical geneticists and derived themes from those interviews through content analysis.

RESULTS

Individuals described individualized interventions as blurring the lines between research and clinical care and focused on hopes for therapeutic benefit and expectations for generalizability of knowledge and benefit to future patients.

CONCLUSION

Individualized interventions aimed at one or few patients reveal the limitations of a binary framing of research and clinical care. As a hybrid set of activities, individualized interventions suggest the need for flexibility and new frameworks that acknowledge these activities across the spectrum of research and clinical care.

Data Challenges for Externally Controlled Trials: Viewpoint

The preferred evidence of a large randomized controlled trial is difficult to adopt in scenarios, such as rare conditions or clinical subgroups with high unmet needs, and evidence from external sources, including real-world data, is being increasingly considered by decision makers. Real-world data originate from many sources, and identifying suitable real-world data that can be used to contextualize a single-arm trial, as an external control arm, has several challenges. In this viewpoint article, we provide an overview of the technical challenges raised by regulatory and health reimbursement agencies when evaluating comparative efficacy, such as identification, outcome, and time selection challenges. By breaking down these challenges, we provide practical solutions for researchers to consider through the approaches of detailed planning, collection, and record linkage to analyze external data for comparative efficacy.

Precision information extraction for rare disease epidemiology at scale

BACKGROUND

The United Nations recently made a call to address the challenges of an estimated 300 million persons worldwide living with a rare disease through the collection, analysis, and dissemination of disaggregated data. Epidemiologic Information (EI) regarding prevalence and incidence data of rare diseases is sparse and current paradigms of identifying, extracting, and curating EI rely upon time-intensive, error-prone manual processes. With these limitations, a clear understanding of the variation in epidemiology and outcomes for rare disease patients is hampered. This challenges the public health of rare diseases patients through a lack of information necessary to prioritize research, policy decisions, therapeutic development, and health system allocations.

METHODS

In this study, we developed a newly curated epidemiology corpus for Named Entity Recognition (NER), a deep learning framework, and a novel rare disease epidemiologic information pipeline named EpiPipeline4RD consisting of a web interface and Restful API. For the corpus creation, we programmatically gathered a representative sample of rare disease epidemiologic abstracts, utilized weakly-supervised machine learning techniques to label the dataset, and manually validated the labeled dataset. For the deep learning framework development, we fine-tuned our dataset and adapted the BioBERT model for NER. We measured the performance of our BioBERT model for epidemiology entity recognition quantitatively with precision, recall, and F1 and qualitatively through a comparison with Orphanet. We demonstrated the ability for our pipeline to gather, identify, and extract epidemiology information from rare disease abstracts through three case studies.

RESULTS

We developed a deep learning model to extract EI with overall F1 scores of 0.817 and 0.878, evaluated at the entity-level and token-level respectively, and which achieved comparable qualitative results to Orphanet's collection paradigm. Additionally, case studies of the rare diseases Classic homocystinuria, GRACILE syndrome, Phenylketonuria demonstrated the adequate recall of abstracts with epidemiology information, high precision of epidemiology information extraction through our deep learning model, and the increased efficiency of EpiPipeline4RD compared to a manual curation paradigm.

CONCLUSIONS

EpiPipeline4RD demonstrated high performance of EI extraction from rare disease literature to augment manual curation processes. This automated information curation paradigm will not only effectively empower development of the NIH Genetic and Rare Diseases Information Center (GARD), but also support the public health of the rare disease community.

Cost and availability of novel cell and gene therapies: Can we avoid a catastrophic second valley of death?: Can we avoid a catastrophic second valley of death?

Advanced gene and cellular therapies risk a second "valley of death" due to their high costs and low patient population. As these are life-saving therapies, measures are urgently needed to prevent their withdrawal from the market.

The use of pharmacological chaperones in rare diseases caused by reduced protein stability

Rare diseases are most often caused by inherited genetic disorders that, after translation, will result in a protein with altered function. Decreased protein stability is the most frequent mechanism associated with a congenital pathogenic missense mutation and it implies the destabilization of the folded conformation in favour of unfolded or misfolded states. In the cellular context and when experimental data is available, a mutant protein with altered thermodynamic stability often also results in impaired homeostasis, with the deleterious accumulation of protein aggregates, metabolites and/or metabolic by-products. In the last decades, a significant effort has enabled the characterization of rare diseases associated to protein stability defects and triggered the development of innovative therapeutic intervention lines, say, the use of pharmacological chaperones to correct the intracellular impaired homeostasis. Here, we review the current knowledge on rare diseases caused by reduced protein stability, paying special attention to the thermodynamic aspects of the protein destabilization, also focusing on some examples where pharmacological chaperones are being tested.

Diagnostic journeys: characterization of patients and diagnostic outcomes from an academic second opinion clinic

OBJECTIVES

Diagnostic programs and second opinion clinics have grown and evolved in the recent years to help patients with rare, puzzling, and complex conditions who often suffer prolonged diagnostic journeys, but there is a paucity of literature on the clinical characteristics of these patients and the efficacy of these diagnostic programs. This study aims to characterize the diagnostic journey, case features, and diagnostic outcomes of patients referred to a team-based second opinion clinic at Stanford.

METHODS

Retrospective chart review was performed for 237 patients evaluated for diagnostic second opinion in the Stanford Consultative Medicine Clinic over a 5 year period. Descriptive case features and diagnostic outcomes were assessed, and correlation between the two was analyzed.

RESULTS

Sixty-three percent of our patients were women. 49% of patients had a potential precipitating event within about a month prior to the start of their illness, such as medication change, infection, or medical procedure. A single clear diagnosis was determined in 33% of cases, whereas the remaining cases were assessed to have multifactorial contributors/diagnoses (20%) or remained unclear despite extensive evaluation (47%). Shorter duration of illness, fewer prior specialties seen, and single chief symptom were associated with higher likelihood of achieving a single clear diagnosis.

CONCLUSIONS

A single-site academic consultative service can offer additional diagnostic insights for about half of all patients evaluated for puzzling conditions. Better understanding of the clinical patterns and patient experiences gained from this study helps inform strategies to shorten their diagnostic odysseys.