Therapies for rare diseases: therapeutic modalities, progress and challenges ahead

Evolving Research and Development Landscape for Rare Diseases: Growing Concerns Over Orphan Drug Lag in Japan

Patients with rare diseases worldwide face substantial unmet therapeutic needs. In Japan, drug lag-delays in drug approval compared to other countries-has resurfaced as a pressing public health issue. This study analyzes orphan drugs (ODs) approved in the United States (US) from 2005 to 2021, examining OD lag trends, and research and development (R&D) models to streamline OD development in Japan. Despite increased OD approval in the United States since 2018, the number of unapproved ODs in Japan has substantially increased. Although OD lag decreased, it has resurged since 2017. This is largely due to changes in the R&D strategies of pharmaceutical companies, which are driven by the growing presence of US- and Europe-based small- to mid-sized enterprises (SMEs) and the evolving industry landscape. Large foreign pharmaceutical companies have shifted toward a global development strategy for Japan, aiming for more efficient development and competitive advantage. This has been propelled by a move toward in-licensing earlier-stage drug candidates with global exclusivity from SMEs. Japanese pharmaceutical companies have focused on in-licensing late-stage drug candidates for the Japanese market from SMEs without a business presence in Japan, which have not been developed locally, thereby employing a bridging strategy for Japan. With the increase in ODs developed in the United States by these SMEs, this practice has substantially exacerbated the OD lag. As these SMEs are unlikely to enter the Japanese market, it is crucial for Japanese pharmaceutical companies to proactively pursue earlier, more proactive global partnerships with SMEs.

National Creutzfeldt-Jakob disease research biobank, a novel approach to the establishment of the scientific platform: collaboration between patient advocacy group, scientists, regulators and physicians

Creutzfeldt-Jakob disease (CJD) is a severe neurodegenerative disorder characterized by the abnormal accumulation of prion proteins. In Israel, a unique epidemiological pattern of CJD has been identified, specifically a genetic form (gCJD) associated with the E200K mutation in the PRNP gene. Investigating rare diseases such as CJD syndrome poses challenges due to their low prevalence, hindering the formation of an adequate patient cohort for comprehensive research and treatment trials. To overcome this limitation, biobanks have emerged as transformative tools for collecting and distributing biological specimens along with corresponding health data. Biobanks offer a solution to the inherent heterogeneity in rare diseases, allowing researchers to access diverse and extensive sample sets, thereby enhancing the understanding of disease nuances toward potential therapy. We introduce a novel collaborative model involving the Negev BioBank (NBB), the Creutzfeldt-Jakob Israel Foundation, the Israeli National BioBank for Research (MIDGAM), and the Israeli Ministry of Health. Each entity contributes unique expertise and resources to establish a comprehensive platform for studying the disease. The goal was to establish a participant pool of 500 individuals, including clinically diagnosed cases, confirmed carriers of the E200K mutation, and their first- and second-degree relatives. During the pilot phase of the last year, 250 participants were enrolled, with each family contributing between 1 and 25 participants. This collaborative approach involving communities, scientists, physicians, and regulatory bodies establishes a model applicable across various fields. These synergistic efforts aim to advance research on CJD and potentially serve as a blueprint for studying other rare diseases.

Guanidinium/Phenyl-Rich Amphiphilic Cationic Polymer for Efficient Cytosolic Protein Delivery and Cancer Immunotherapy

Protein drugs have garnered increasing attention in biomedical applications due to their high specificity for target receptors and minimal side effects. However, the macromolecular and hydrophilic nature of proteins severely hinders their ability to penetrate cell membranes, restricting their intracellular applications. Herein, we present an innovative amphiphilic cationic polymer, p(PG420-co-HP15), capable of forming stable nanoparticles with diverse proteins and facilitating efficient cytosolic delivery. By incorporating guanidinium and phenyl ligands, p(PG420-co-HP15) effectively complexes with various proteins via hydrogen bonding, salt bridges, and hydrophobic and π-π interactions. Meanwhile, the phenyl ligands further enhance cellular uptake and promote endosomal escape by inducing membrane perturbations, likely through disruption of phospholipid packing and increased membrane fluidity. Consequently, p(PG420-co-HP15) enables efficient cytosolic delivery of 6 proteins, each with unique molecular weights, isoelectric points, and biological functions across different cell lines, surpassing the commercial reagent PULSin in delivery efficiency. Furthermore, p(PG420-co-HP15) effectively constructed nanovaccines with ovalbumin (OVA), significantly boosting T cell-mediated antitumor immunity in a B16-OVA melanoma mouse model. These findings emphasize the potential of p(PG420-co-HP15) as a versatile and efficient cytosolic protein delivery platform with broad applications in disease treatment, vaccine development, and biological research.

Applications of Artificial Intelligence in Drug Repurposing

Drug repurposing identifies new therapeutic uses for the existing drugs originally developed for different indications, aiming at capitalizing on the established safety and efficacy profiles of known drugs. Thus, it is beneficial to bypass of early stages of drug development, and to reduction of the time and cost associated with bringing new therapies to market. Traditional experimental methods are often time-consuming and expensive, making artificial intelligence (AI) a promising alternative due to its lower cost, computational advantages, and ability to uncover hidden patterns. This review focuses on the availability of AI algorithms in drug development, and their positive and specific roles in revealing repurposing of the existing drugs, especially being integrated with virtual screening. It is shown that the existing AI algorithms excel at analyzing large-scale datasets, identifying the complicated patterns of drug responses from these datasets, and making predictions for potential drug repurposing. Building on these insights, challenges remain in developing efficient AI algorithms and future research, including integrating drug-related data across databases for better repurposing, enhancing AI computational efficiency, and advancing personalized medicine.

Drug-device combinations in rare diseases: Challenges and opportunities

Drug-device combinations (DDCs) are therapeutic products that integrate drugs with medical devices to enhance treatment efficacy and/or safety. These combinations hold significant promise for rare diseases, which affect millions of patients globally, by improving drug delivery, targeting specific organs, and reducing side effects. However, the regulatory framework for DDCs remains complex and lacks specific incentives for rare diseases, unlike orphan drugs. This review examines regulatory approaches and case studies of DDCs in rare diseases, and highlights specific challenges and untapped opportunities. Moreover, the publication discusses recommendations to overcome these challenges through tailored policies and incentives to unlock the potential of DDCs in the context of rare diseases.

DNA nanotechnology-based strategies for minimising hybridisation-dependent off-target effects in oligonucleotide therapies

Targeted therapy has emerged as a transformative breakthrough in modern medicine. Oligonucleotide drugs, such as antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs), have made significant advancements in targeted therapy. Other oligonucleotide-based therapeutics like clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) systems are also leading a revolution in targeted gene therapy. However, hybridisation-dependent off-target effects, arising from imperfect base pairing, remain a significant and growing concern for the clinical translation of oligonucleotide-based therapeutics. These mismatches in base pairing can lead to unintended steric blocking or cleavage events in non-pathological genes, affecting the efficacy and safety of the oligonucleotide drugs. In this review, we examine recent developments in oligonucleotide-based targeted therapeutics, explore the factors influencing sequence-dependent targeting specificity, and discuss the current approaches employed to reduce the off-target side effects. The existing strategies, such as chemical modifications and oligonucleotide length optimisation, often require a trade-off between specificity and binding affinity. To further address the challenge of hybridisation-dependent off-target effects, we discuss DNA nanotechnology-based strategies that leverage the collaborative effects of nucleic acid assembly in the design of oligonucleotide-based therapies. In DNA nanotechnology, collaborative effects refer to the cooperative interactions between individual strands or nanostructures, where multiple bindings result in more stable and specific hybridisation behaviour. By requiring multiple complementary interactions to occur simultaneously, the likelihood of unintended partially complementary binding events in nucleic acid hybridisation should be reduced. And thus, with the aid of collaborative effects, DNA nanotechnology has great promise in achieving both high binding affinity and high specificity to minimise the hybridisation-dependent off-target effects of oligonucleotide-based therapeutics.

Novel integrated Omics based computational approach for drug repurposing for non-muscle invasive bladder cancer (NMIBC)

Non-muscle invasive bladder cancer (NMIBC) refers to a subtype of bladder carcinoma where cancer is localized in the inner lining of bladder. NMIBC consider as one of most costly malignancy and requires significant surgical and therapeutic measure. However, recurrence and progression of tumor is common in treated patients. Here we presented an integrated OMICs approach for the identification and inhibition of NMIBC specific genes. We utilized a case study where three group of patients were compared: 1) Relapsed tumors 2) recurrent tumors and 3) tumor in progression. Common transcriptome signature between patients facing recurrence and progression allowed us to identify three NMIBC specific genes FLT-1, WHSC-1 and CD34. We further utilized novel approach of Co-expressed gene-set enrichment analysis (COGENA) on the differentially expressed genes of this case study. Three drugs (paroxetine, adiphenine and H-89) with role of receptors inhibition were identified and predicted as repurposed drugs for the inhibition NMIBC specific genes. We further tested this hypothesis by performing molecular docking and simulation analysis between cancer specific proteins and drugs. FLT-1 have shown significant stable interaction with both drugs paroxetine and adiphenine whereas WHSC-1 have shown compact interaction with adiphenine and H-89. In the light of these evidence, we suggest that adiphenine could be repositioned as alternate targeted medicine for the treatment of NMIBC. In the future, this study will help for strengthening the strategies development at the molecular level for the control of carcinomas at early as well as detection of active and binding site, receptor-ligand interaction and also make drug repurposing for the early treatment of the carcinomas.

Big data and transformative bioinformatics in genomic diagnostics and beyond

The current era of high-throughput analysis-driven research offers invaluable insights into disease etiologies, accurate diagnostics, pathogenesis, and personalized therapy. In the field of movement disorders, investigators are facing an increasing growth in the volume of produced patient-derived datasets, providing substantial opportunities for precision medicine approaches based on extensive information accessibility and advanced annotation practices. Integrating data from multiple sources, including phenomics, genomics, and multi-omics, is crucial for comprehensively understanding different types of movement disorders. Here, we explore formats and analytics of big data generated for patients with movement disorders, including strategies to meaningfully share the data for optimized patient benefit. We review computational methods that are essential to accelerate the process of evaluating the increasing amounts of specialized data collected. Based on concrete examples, we highlight how bioinformatic approaches facilitate the translation of multidimensional biological information into clinically relevant knowledge. Moreover, we outline the feasibility of computer-aided therapeutic target evaluation, and we discuss the importance of expanding the focus of big data research to understudied phenotypes such as dystonia.

A call to action to scale up research and clinical genomic data sharing

Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical data sets, optimizing benefit.

Human-based complex in vitro models: their promise and potential for rare disease therapeutics

Rare diseases affect a small percentage of an individual country's population; however, with over 7,000 in total, rare diseases represent a significant disease burden impacting up to 10% of the world's population. Despite this, there are no approved treatments for almost 95% of rare diseases, and the existing treatments are cost-intensive for the patients. More than 70% of rare diseases are genetic in nature, with patient-specific mutations. This calls for the need to have personalised and patient-specific preclinical models that can lead to effective, speedy, and affordable therapeutic options. Complex in vitro models (CIVMs), including those using induced pluripotent stem cells (iPSCs), organoids, and organs-on-chips are emerging as powerful human-based pre-clinical systems with the capacity to provide efficacy data enabling drugs to move into clinical trials. In this narrative review, we discuss how CIVMs are providing insights into biomedical research on rare diseases. We also discuss how these systems are being used in clinical trials to develop efficacy models for rare diseases. Finally, we propose recommendations on how human relevant CIVMs could be leveraged to increase translatability of basic, applied and nonclinical research outcomes in the field of rare disease therapeutics in developed as well as middle-and low-income countries.

Rare Disease Policy in High-Income Countries: An Overview of Achievements, Challenges, and Solutions

OBJECTIVES

To provide an overview of policy initiatives in high-income countries aimed at supporting the development and accessibility of treatments for rare diseases.

METHODS

We examine how legislative, research, and pricing policies in high-income countries address barriers that have historically hindered innovation and access to rare disease treatments. By analyzing examples from the European Union, United Kingdom, United States, Canada, Japan, and Australia, the article identifies ongoing initiatives, outlines current challenges, and explores proposed solutions to foster a sustainable, innovative, and accessible rare disease treatment ecosystem.

RESULTS

The review highlights policies such as legislative incentives in the European Union, United States, and Japan for orphan drug development, public-private partnerships to boost innovation, and patient registries to support research and clinical trials. Despite these efforts, major challenges persist, including high therapy costs, limited access to innovation for ultrarare diseases, and diagnostic delays, with significant disparities across regions.

CONCLUSIONS

Overcoming these challenges will require sustainable pricing and reimbursement frameworks, alongside stronger collaboration between stakeholders, particularly for ultrarare diseases. Advanced technologies, such as artificial intelligence, hold promise for improving diagnostic accuracy and data collection, supported by enhanced coding systems and registries to facilitate more robust research.

Tandem mass spectrometry-based assay for heparan-N-sulphatase in paediatric CSF: A potential pharmacodynamic biomarker for mucopolysaccharidosis type IIIA therapy

Mucopolysaccharidosis type IIIA is a lysosomal storage disorder caused by mutations in the gene coding for heparan-N-sulphatase, a crucial enzyme in the degradation of heparan sulfate. In mucopolysaccharidosis type IIIA, heparan sulfate accumulates in the lysosomes, predominantly affecting the central nervous system. It is the most common and most severe form of mucopolysaccharidosis type III, with onset typically before the age of ten years. There is an ongoing effort to develop therapies that aim at restoring enzyme function in the brain. This study introduces a novel tandem mass spectrometry method for assessing heparan-N-sulphatase activity in pediatric cerebrospinal fluid from healthy and disease individuals. Analysis of cerebrospinal fluid samples revealed marked differences in enzyme activity, with mucopolysaccharidosis type IIIA individuals exhibiting significantly reduced levels. This new method could serve as a valuable tool for evaluating the efficacy of future therapeutic interventions targeting sulphatase activity restoration in the brain.

A collaborative network analysis for the interpretation of transcriptomics data in Huntington's disease

Rare diseases may affect the quality of life of patients and be life-threatening. Therapeutic opportunities are often limited, in part because of the lack of understanding of the molecular mechanisms underlying these diseases. This can be ascribed to the low prevalence of rare diseases and therefore the lower sample sizes available for research. A way to overcome this is to integrate experimental rare disease data with prior knowledge using network-based methods. Taking this one step further, we hypothesized that combining and analyzing the results from multiple network-based methods could provide data-driven hypotheses of pathogenic mechanisms from multiple perspectives.We analyzed a Huntington's disease transcriptomics dataset using six network-based methods in a collaborative way. These methods either inherently reported enriched annotation terms or their results were fed into enrichment analyses. The resulting significantly enriched Reactome pathways were then summarized using the ontological hierarchy which allowed the integration and interpretation of outputs from multiple methods. Among the resulting enriched pathways, there are pathways that have been shown previously to be involved in Huntington's disease and pathways whose direct contribution to disease pathogenesis remains unclear and requires further investigation.In summary, our study shows that collaborative network analysis approaches are well-suited to study rare diseases, as they provide hypotheses for pathogenic mechanisms from multiple perspectives. Applying different methods to the same case study can uncover different disease mechanisms that would not be apparent with the application of a single method.

Effective Newborn Screening for Type 1 and 3 Primary Hyperoxaluria

Introduction

Newborn screening (NBS) programs for a defined set of eligible diseases have been enormously successful, but genomic NBS allowing for detection of additional treatable disorders has not been broadly implemented. All 3 types of primary hyperoxaluria (PH1-3) are rare autosomal recessive diseases caused by distinct defects of glyoxylate metabolism that are diagnosed genetically with certainty. Early diagnosis and treatment are mandatory to avoid renal failure or sequalae associated with persistent hyperoxaluria.

Methods

This prospective pilot study was undertaken within the framework of the German NBS. DNA samples extracted from dried blood spot cards were screened by multiplex polymerase chain reaction (PCR) for the 2 most prevalent variants: AGXT c.508G>A (PH1) and HOGA1 c.700 + 5G>T (PH3). Heterozygous AGXT/HOGA1 carriers received repeated spot urine analyses and, in case of persistent hyperoxaluria, complete Sanger sequencing of AGXT and HOGA1 genes, respectively.

Results

Between March 15, 2022 and June 30, 2023, additional screening for PH1 and PH3 was performed in 77,199 out of 222,638 newborns included in the regular NBS program. No homozygous individuals, but 274 potential carriers for the AGXT mistargeting and 287 potential carriers for the HOGA1 splice variant were identified. Further workup revealed 2 already symptomatic compound heterozygous infants, 1 with PH1 (genotype c.508G>A; c.33delC) and 1 with PH3 (genotype: c.700 + 5G>T; c.134C>G). A second symptomatic patient with PH1 (father of an identified carrier; genotype: c.508G>A; c.508G>A) was uncovered via family history.

Conclusion

This pilot study demonstrates the efficacy of a genomic neonatal screening program for PH even in relatively small cohorts.

The state-of-the-art of N-of-1 therapies and the IRDiRC N-of-1 development roadmap

In recent years, a small number of people with rare diseases caused by unique genetic variants have been treated with therapies developed specifically for them. This pioneering field of genetic N-of-1 therapies is evolving rapidly, giving hope for the individualized treatment of people living with very rare diseases. In this Review, we outline the concept of N-of-1 individualized therapies, focusing on genetic therapies, and illustrate advances and challenges in the field using cases for which therapies have been successfully developed. We discuss why the traditional drug development and reimbursement pathway is not fit for purpose in this field, and outline the pragmatic, regulatory and ethical challenges this poses for future access to N-of-1 therapies. Finally, we provide a roadmap for N-of-1 individualized therapy development.

Assessing Post-Marketing Requirements for Orphan Drugs: A Cross-Sectional Analysis of FDA and EMA Oversight

The U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) oversee pharmaceutical regulations, including orphan drugs targeting rare diseases with limited patient populations. Post-marketing studies are crucial for monitoring safety and efficacy, with post-marketing requirements (PMRs) mandated by the regulatory agencies to ensure compliance. This study aims to compare PMR statuses, objectives, and pivotal trial characteristics of orphan drugs approved by the FDA (n = 154) and EMA (n = 79) from 2008 to 2018, shedding light on regulatory differences and their impact on drug development. Contrary to expectations, our analysis found no significant disparity in the proportion of orphan drugs with and without PMRs approved by both the FDA (48.1%) and EMA (55.7%). Safety concerns surrounding orphan drugs post-approval, attributed partly to pivotal trial design, underscore the need for robust post-marketing surveillance. While the FDA primarily focuses on post-marketing safety (36.1%), the EMA places a higher emphasis on both efficacy and safety (47.1%), reflecting distinct approaches to PMR management between the two regulatory bodies. The observed trend of delayed PMRs at the EMA (47.1%) highlights the importance of effective cooperation between regulators and pharmaceutical companies to ensure the timely completion of PMRs and enhance drug safety.

Getting the Dose Right in Drug Development for Rare Diseases: Barriers and Enablers

In the relentless pursuit of optimizing drug development, the intricate process of determining the ideal dosage unfolds. This involves "dose-finding" studies, crucial for providing insights into subsequent registration trials. However, the challenges intensify when tackling rare diseases. The complexity arises from poorly understood pathophysiologies, scarcity of appropriate animal models, and limited natural history understanding. The inherent heterogeneity, coupled with challenges in defining clinical end points, poses substantial challenges, hindering the utility of available data. The small affected population, low disease awareness, and restricted healthcare access compound the difficulty in conducting dose-finding studies. This white paper delves into critical dose selection aspects, focusing on key therapeutic areas, such as oncology, neurology, hepatology, metabolic rare diseases. It also explores dose selection challenges posed by pediatric rare diseases as well as novel modalities, including enzyme replacement therapies, cell and gene therapies, and oligonucleotides. Several examples emphasize the pivotal role of clinical pharmacology in navigating the complexities associated with these diseases and emerging treatment modalities.

Implementing genomic medicine in clinical practice for adults with undiagnosed rare diseases

The global burden of undiagnosed diseases, particularly in adults, is rising due to their significant socioeconomic impact. To address this, we enrolled 232 adult probands with undiagnosed conditions, utilizing bioinformatics tools for genetic analysis. Alongside exome and genome sequencing, repeat-primed PCR and Cas9-mediated nanopore sequencing were applied to suspected short tandem repeat disorders. Probands were classified into probable genetic (n = 128) or uncertain (n = 104) origins. The study found genetic causes in 66 individuals (28.4%) and non-genetic causes in 12 (5.2%), with a longer diagnostic journey for those in the probable genetic group or with pediatric symptom onset, emphasizing the need for increased efforts in these populations. Genetic diagnoses facilitated effective surveillance, cascade screening, drug repurposing, and pregnancy planning. This study demonstrates that integrating sequencing technologies improves diagnostic accuracy, may shorten the time to diagnosis, and enhances personalized management for adults with undiagnosed diseases.

Exploring the potential of compound-protein complex structure-free models in virtual screening using BlendNet

Identifying new compounds that interact with a target is a crucial time-limiting step in the initial phases of drug discovery. Compound-protein complex structure-based affinity prediction models can expedite this process; however, their dependence on high-quality three-dimensional (3D) complex structures limits their practical application. Prediction models that do not require 3D complex structures for binding-affinity estimation offer a theoretically attractive alternative; however, accurately predicting affinity without interaction information presents significant challenges. We introduce BlendNet, a framework that employs a knowledge transfer strategy to improve affinity prediction accuracy by learning the interdependent relationships between compounds and proteins without relying on 3D complex structures. Compared with state-of-the-art models for affinity prediction, BlendNet demonstrated superior performance across various cold-start cases. The ability of BlendNet to interpret compound-protein interactions without utilizing complex structure data highlights its potential to accelerate and streamline drug development.

The relative importance of severity and rarity criteria in health resource allocation: an umbrella review

OBJECTIVES

The primary objectives of this umbrella review were to (a) quantify the relative importance, of "severity" and "rarity" criteria in health resource allocation; and (b) analyze the contextual factors influencing the relative importance. The secondary objective was to examine how "severity" and "rarity" criteria are defined.

METHODS

Searches were carried out in PubMed and Embase to identify eligible systematic reviews. Quality appraisal of systematic reviews was undertaken. From identified systematic reviews, primary studies were extracted and further screened for eligibility. The inclusion of severity and rarity criteria and their respective weights in primary studies were examined. Descriptive and regression analyses were performed.

RESULTS

Twenty-nine systematic reviews were screened, of which nine met the inclusion criteria. Primary studies included in these systematic reviews were retrieved and screened, resulting in forty articles included in the final analysis. Disease severity was more frequently considered (n = 29/40) than disease rarity (n = 23/40) as an evaluation criterion. Out of all cases where both were included as evaluation criteria, disease severity was assigned higher weights 84 percent of the time (n = 21/25).

CONCLUSIONS

Our review found consistent evidence that disease severity is more relevant and preferred to rarity as a priority-setting criterion albeit constraints in statistical analysis imposed by limited sample size and data availability. Where funding for rare diseases is concerned, we advocate that decision-makers be explicit in clarifying the significance of disease severity and/or rarity as a value driver behind decisions. Our findings also reinforce the relevance of disease severity as a criterion in priority setting.

Pre-clinical development of AP4B1 gene replacement therapy for hereditary spastic paraplegia type 47

Spastic paraplegia 47 (SPG47) is a neurological disorder caused by mutations in the adaptor protein complex 4 β1 subunit (AP4B1) gene leading to AP-4 complex deficiency. SPG47 is characterised by progressive spastic paraplegia, global developmental delay, intellectual disability and epilepsy. Gene therapy aimed at restoring functional AP4B1 protein levels is a rational therapeutic strategy to ameliorate the disease phenotype. Here we report that a single delivery of adeno-associated virus serotype 9 expressing hAP4B1 (AAV9/hAP4B1) into the cisterna magna leads to widespread gene transfer and restoration of various hallmarks of disease, including AP-4 cargo (ATG9A) mislocalisation, calbindin-positive spheroids in the deep cerebellar nuclei, anatomical brain defects and motor dysfunction, in an SPG47 mouse model. Furthermore, AAV9/hAP4B1-based gene therapy demonstrated a restoration of plasma neurofilament light (NfL) levels of treated mice. Encouraged by these preclinical proof-of-concept data, we conducted IND-enabling studies, including immunogenicity and GLP non-human primate (NHP) toxicology studies. Importantly, NHP safety and biodistribution study revealed no significant adverse events associated with the therapeutic intervention. These findings provide evidence of both therapeutic efficacy and safety, establishing a robust basis for the pursuit of an IND application for clinical trials targeting SPG47 patients.

Evaluation of orphan maintained biological medicinal products in the European Union between 2018 to 2023: a regulatory perspective

OBJECTIVES

Orphan medicinal products (OMPs) authorized by the European Union (EU) benefit from market exclusivity, fee waivers, and national incentives. Maintaining orphan status during a marketing authorization application requires meeting eligibility criteria, especially demonstrating significant benefit (SB), which is challenging. This study identifies key features linked to successful orphan status maintenance for biological OMPs approved in the EU between 2018 and 2023.

METHODS

Data from European public assessment reports and orphan maintenance assessment reports were analyzed.

RESULTS

Among the 50 biological OMP maintained orphan designations, 68.0% had to demonstrate SB over existing treatments, with 91.2% leveraging the clinically relevant advantage area, utilizing better clinical efficacy (83.9%) and efficacy in subpopulations (38.7%) subdomains. However, 32.0% did not need to demonstrate SB due to a lack of alternative treatments, most of which were ultra-orphan drugs. Advanced therapy medicinal products and monoclonal antibodies were the most numerous OMP categories, whereas oncology and immunomodulation were the preferred therapeutic areas.

CONCLUSION

The Orphan Regulation is essential in advancing treatments for rare diseases, fostering innovation while addressing unmet medical needs. Nonetheless, the insufficient return on investment criterion remains underused, whereas refining major contribution to patient care guidelines and incorporating real-world evidence may enhance regulatory evaluations.

A biodegradable lipid nanoparticle delivers a Cas9 ribonucleoprotein for efficient and safe in situ genome editing in melanoma

The development of melanoma is closely related to Braf gene, which is a suitable target for CRISPR/Cas9 based gene therapy. CRISPR/Cas9-sgRNA ribonucleoprotein complexes (RNPs) stand out as the safest format compared to plasmid and mRNA delivery. Similarly, lipid nanoparticles (LNPs) emerge as a safer alternative to viral vectors for delivering the CRISPR/Cas9-sgRNA gene editing system. Herein, we have designed multifunctional cationic LNPs specifically tailored for the efficient delivery of Cas9 RNPs targeting the mouse Braf gene through transdermal delivery, aiming to treat mouse melanoma. LNPs are given a positive charge by the addition of a newly synthesized polymer, deoxycholic acid modified polyethyleneimine (PEI-DOCA). Positive charge enables LNPs to be delivered in vivo by binding to negatively charged cell membranes and proteins, thereby facilitating efficient skin penetration and enhancing the delivery of RNPs into melanoma cells for gene editing purposes. Our research demonstrates that these LNPs enhance drug penetration through the skin, successfully delivering the Cas9 RNPs system and specifically targeting the Braf gene. Cas9 RNPs loaded LNPs exert a notable impact on gene editing in melanoma cells, significantly suppressing their proliferation. Furthermore, in mice experiments, the LNPs exhibited skin penetration and tumor targeting capabilities. This innovative LNPs delivery system offers a promising gene therapy approach for melanoma treatment and provides fresh insights into the development of safe and effective delivery systems for Cas9 RNPs in vivo. STATEMENT OF SIGNIFICANCE: CRISPR/Cas9 technology brings new hope for cancer treatment. Cas9 ribonucleoprotein offers direct genome editing, yet delivery challenges persist. For melanoma, transdermal delivery minimizes toxicity but faces skin barrier issues. We designed multifunctional lipid nanoparticles (LNPs) for Cas9 RNP delivery targeting the Braf gene. With metal microneedle pretreatment, our LNPs effectively edited melanoma cells, reducing Braf expression and inhibiting tumor growth. Our study demonstrates LNPs' potential for melanoma therapy and paves the way for efficient in vivo Cas9 RNP delivery systems in cancer therapy.

Schizophrenia Interactome-Derived Repurposable Drugs and Randomized Controlled Trials of Two Candidates

There is a substantial unmet need for effective and patient-acceptable drugs to treat severe mental illnesses such as schizophrenia (SZ). Computational analysis of genomic, transcriptomic, and pharmacologic data generated in the past 2 decades enables repurposing of drugs or compounds with acceptable safety profiles, namely those that are U.S. Food and Drug Administration approved or have reached late stages in clinical trials. We developed a rational approach to achieve this computationally for SZ by studying drugs that target the proteins in its protein interaction network (interactome). This involved contrasting the transcriptomic modulations observed in the disorder and the drug; our analyses resulted in 12 candidate drugs, 9 of which had additional supportive evidence whereby their target networks were enriched for pathways relevant to SZ etiology or for genes that had an association with diseases pathogenically similar to SZ. To translate these computational results to the clinic, these shortlisted drugs must be tested empirically through randomized controlled trials, in which their previous safety approvals obviate the need for time-consuming phase 1 and 2 studies. We selected 2 among the shortlisted candidates based on likely adherence and side-effect profiles. We are testing them through adjunctive randomized controlled trials for patients with SZ or schizoaffective disorder who experienced incomplete resolution of psychotic features with conventional treatment. The integrated computational analysis for identifying and ranking drugs for clinical trials can be iterated as additional data are obtained. Our approach could be expanded to enable disease subtype-specific drug discovery in the future and should also be exploited for other psychiatric disorders.

A comprehensive review on the current status of CRISPR based clinical trials for rare diseases

A considerable fraction of population in the world suffers from rare diseases. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and its related Cas proteins offer a modern form of curative gene therapy for treating the rare diseases. Hereditary transthyretin amyloidosis, hereditary angioedema, duchenne muscular dystrophy and Rett syndrome are a few examples of such rare diseases. CRISPR/Cas9, for example, has been used in the treatment of β-thalassemia and sickle cell disease (Frangoul et al., 2021; Pavani et al., 2021) [1,2]. Neurological diseases such as Huntington's have also been focused in some studies involving CRISPR/Cas (Yang et al., 2017; Yan et al., 2023) [3,4]. Delivery of these biologicals via vector and non vector mediated methods depends on the type of target cells, characteristics of expression, time duration of expression, size of foreign genetic material etc. For instance, retroviruses find their applicability in case of ex vivo delivery in somatic cells due to their ability to integrate in the host genome. These have been successfully used in gene therapy involving X-SCID patients although, incidence of inappropriate activation has been reported. On the other hand, ex vivo gene therapy for β-thalassemia involved use of BB305 lentiviral vector for high level expression of CRISPR biological in HSCs. The efficacy and safety of these biologicals will decide their future application as efficient genome editing tools as they go forward in further stages of human clinical trials. This review focuses on CRISPR/Cas based therapies which are at various stages of clinical trials for treatment of rare diseases and the constraints and ethical issues associated with them.

A weighted Bayesian integration method for predicting drug combination using heterogeneous data

BACKGROUND

In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies.

METHODS

In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profiles. By constructing a multiplex drug similarity network, we formulate new features for drug pairs and propose a novel Bayesian-based integration scheme with the introduction of weights to integrate information from various sources. This method yields support strength scores for drug combinations to assess their potential effectiveness.

RESULTS

Upon comprehensive comparison with other methods, our method shows superior performance across multiple metrics, including the Area Under the Receiver Operating Characteristic Curve, accuracy, precision, and recall. Furthermore, literature validation shows that many top-ranked drug combinations based on the support strength score, such as goserelin and letrozole, have been experimentally or clinically validated for their effectiveness.

CONCLUSIONS

Our findings have significant clinical and practical implications. This new method enhances the performance of drug combination predictions, enabling effective pre-screening for trials and, thereby, benefiting clinical treatments. Future research should focus on developing new methods for application in various scenarios and for integrating diverse data sources.

Rare diseases: What rheumatologists need to know?

Although the terms "rare diseases" (RD) and "orphan diseases" (OD) are often used interchangeably, specific nuances in definitions should be noted to avoid misconception. RD are characterized by a low prevalence within the population, whereas OD are those inadequately recognized or even neglected by the medical community and drug companies. Despite their rarity, as our ability on discovering novel clinical phenotypes and improving diagnostic tools expand, RD will continue posing a real challenge for rheumatologists. Over the last decade, there has been a growing interest on elucidating mechanisms of rare autoimmune and autoinflammatory rheumatic diseases, allowing a better understanding of the role played by immune dysregulation on granulomatous, histiocytic, and hypereosinophilic disorders, just to name a few. This initiative enabled the rise of innovative targeted therapies for rheumatic RD. In this review, we explore the state-of-the art of rare RD and the critical role played by rheumatologists in healthcare. We also describe the challenges rheumatologists may face in the coming decades.

Antisense oligonucleotides and their applications in rare neurological diseases

Rare diseases affect almost 500 million people globally, predominantly impacting children and often leading to significantly impaired quality of life and high treatment costs. While significant contributions have been made to develop effective treatments for those with rare diseases, more rapid drug discovery strategies are needed. Therapeutic antisense oligonucleotides can modulate target gene expression with high specificity through various mechanisms determined by base sequences and chemical modifications; and have shown efficacy in clinical trials for a few rare neurological conditions. Therefore, this review will focus on the applications of antisense oligonucleotides, in particular splice-switching antisense oligomers as promising therapeutics for rare neurological diseases, with key examples of Duchenne muscular dystrophy and spinal muscular atrophy. Challenges and future perspectives in developing antisense therapeutics for rare conditions including target discovery, antisense chemical modifications, animal models for therapeutic validations, and clinical trial designs will also be briefly discussed.

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.

Does gene therapies clinical research in rare diseases reflects the competitivity of the country: Example of France

Rare diseases are chronic, serious and generally genetic conditions affecting a small number of people, and their therapeutic management is a real challenge. They represent a considerable burden for patients, caregivers and society alike. Compared with existing symptomatic treatments, gene therapies represent a promising new approach aimed at treating these diseases by replacing a defective gene, or by abolishing or reviving a gene-derived function. France is considered one of the leading countries in the research and development of drugs for rare diseases, yet the position of French public and private stakeholders in the research and development of gene therapies for rare diseases at global and European level remains unclear. To answer this question, we used the GENOTRIAL FR database developed by OrphanDev to clarify France's involvement and competitiveness in this field. The results show that France is actively involved in gene therapy clinical trials, with a dense international collaboration network and solid expertise. However, the French medical infrastructure is mainly involved in clinical research on gene therapy candidates sponsored by several foreign countries. To a lesser extent, French public and private entities are also developing their own gene therapy candidates for various rare diseases, some of which have already reached advanced clinical phases. In conclusion, a number of technical and financial challenges need to be overcome if France is to maintain its position as a European and world leader and increase its contribution to reducing the economic and social burden of rare diseases by developing revolutionary and effective new therapies.

Health-related quality of life in patients with diverse rare diseases: An online survey

Purpose

Rare diseases substantially contribute to population morbidity and mortality. Understanding rare disease health-related quality of life (HRQL) is essential for evaluating platform-based interventions that aim to tackle multiple rare diseases at a time. However, most HRQL studies focus on single or select group of rare diseases, often in a single country. Our study aimed to identify patient- and disease-specific correlates of HRQL across diverse rare diseases.

Methods

We conducted an international online survey of rare disease patients and caregiver proxies affected by a systematically identified sample of rare diseases. We calculated EQ-5D scores and conducted multivariate linear regression to examine sociodemographic and disease predictors of EQ-5D-5L visual analog scale (VAS) and utility scores (United States only).

Results

A total of 1053 individuals affected by 103 different rare diseases participated, including 660 patients and 393 caregiver proxies. Disability status and disease prevalence correlated with poorer HRQL across models (P < .05). Increased pain and decreased ability to perform usual activities also correlated with lower VAS for both adult patients and caregiver proxies (P < .05). Being unemployed approached significance as a correlate of both lower caregiver proxy VAS and lower patient utility scores.

Conclusion

Our results suggest that across rare diseases, lower HRQL is associated with a reduced rare disease prevalence and disability status, among other predictors. Understanding the key correlates of HRQL is essential for developing interventions for improving health care delivery and quality of life for rare disease patients and families.

How to customize common data models for rare diseases: an OMOP-based implementation and lessons learned

BACKGROUND

Given the geographical sparsity of Rare Diseases (RDs), assembling a cohort is often a challenging task. Common data models (CDM) can harmonize disparate sources of data that can be the basis of decision support systems and artificial intelligence-based studies, leading to new insights in the field. This work is sought to support the design of large-scale multi-center studies for rare diseases.

METHODS

In an interdisciplinary group, we derived a list of elements of RDs in three medical domains (endocrinology, gastroenterology, and pneumonology) according to specialist knowledge and clinical guidelines in an iterative process. We then defined a RDs data structure that matched all our data elements and built Extract, Transform, Load (ETL) processes to transfer the structure to a joint CDM. To ensure interoperability of our developed CDM and its subsequent usage for further RDs domains, we ultimately mapped it to Observational Medical Outcomes Partnership (OMOP) CDM. We then included a fourth domain, hematology, as a proof-of-concept and mapped an acute myeloid leukemia (AML) dataset to the developed CDM.

RESULTS

We have developed an OMOP-based rare diseases common data model (RD-CDM) using data elements from the three domains (endocrinology, gastroenterology, and pneumonology) and tested the CDM using data from the hematology domain. The total study cohort included 61,697 patients. After aligning our modules with those of Medical Informatics Initiative (MII) Core Dataset (CDS) modules, we leveraged its ETL process. This facilitated the seamless transfer of demographic information, diagnoses, procedures, laboratory results, and medication modules from our RD-CDM to the OMOP. For the phenotypes and genotypes, we developed a second ETL process. We finally derived lessons learned for customizing our RD-CDM for different RDs.

DISCUSSION

This work can serve as a blueprint for other domains as its modularized structure could be extended towards novel data types. An interdisciplinary group of stakeholders that are actively supporting the project's progress is necessary to reach a comprehensive CDM.

CONCLUSION

The customized data structure related to our RD-CDM can be used to perform multi-center studies to test data-driven hypotheses on a larger scale and take advantage of the analytical tools offered by the OHDSI community.

Application progress of deep generative models in de novo drug design

The deep molecular generative model has recently become a research hotspot in pharmacy. This paper analyzes a large number of recent reports and reviews these models. In the central part of this paper, four compound databases and two molecular representation methods are compared. Five model architectures and applications for deep molecular generative models are emphatically introduced. Three evaluation metrics for model evaluation are listed. Finally, the limitations and challenges in this field are discussed to provide a reference and basis for developing and researching new models published in future.

In-situ-formed immunotherapeutic and hemostatic dual drug-loaded nanohydrogel for preventing postoperative recurrence of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent malignancy characterized by an exceedingly high recurrence rate post-surgery, significantly impairing the prognosis of HCC patients. However, a standard in-care strategy for postoperative therapy is still lacking. Although encouraging results have been obtained in a newly published clinical trial for postoperative therapy by targeting the vascular endothelial growth factor (VEGF) and programmed death ligand 1 (anti-PD-L1), its efficacy remains constrained. Combining a hemostatic hydrogel with a nanoparticle-based drug delivery system presents an opportunity to optimize the antitumor effect. Herein, we developed a nanoplatform, termed HMSN@Sor/aP@Gel, comprising a hemostatic fibrin hydrogel and functionalized hollow mesoporous silica nanoparticles (HMSNs) loaded with sorafenib and anti-PD-L1 for locally administered targeted-immunotherapy to prevent the postoperative recurrence and metastasis of HCC. The antitumor mechanism is grounded in dual inhibition of Ras/Raf/MEK/ERK (MAPK) and phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) pathways, synergistically complemented by PD-L1 blockade. HMSN@Sor/aP@Gel facilitates dendritic cell maturation, enhances cytotoxic T-lymphocyte infiltration, promotes the polarization of tumor-associated macrophages to M1 phenotype, induces tumor immunogenic cell death, reverses immunosuppression, and establishes immune memory to counter postoperative recurrence. Animal studies corroborate that HMSN@Sor/aP@Gel-mediated targeted immunotherapy significantly impedes primary and metastatic tumor growth and establishes immune memory to prevent recurrence post-surgery. This investigation presents a promising strategy for postoperative therapy with considerable potential for clinical translation.

Tailored antisense oligonucleotides designed to correct aberrant splicing reveal actionable groups of mutations for rare genetic disorders

Effective translation of rare disease diagnosis knowledge into therapeutic applications is achievable within a reasonable timeframe; where mutations are amenable to current antisense oligonucleotide technology. In our study, we identified five distinct types of abnormal splice-causing mutations in patients with rare genetic disorders and developed a tailored antisense oligonucleotide for each mutation type using phosphorodiamidate morpholino oligomers with or without octa-guanidine dendrimers and 2'-O-methoxyethyl phosphorothioate. We observed variations in treatment effects and efficiencies, influenced by both the chosen chemistry and the specific nature of the aberrant splicing patterns targeted for correction. Our study demonstrated the successful correction of all five different types of aberrant splicing. Our findings reveal that effective correction of aberrant splicing can depend on altering the chemical composition of oligonucleotides and suggest a fast, efficient, and feasible approach for developing personalized therapeutic interventions for genetic disorders within short time frames.

Coding Therapeutic Nucleic Acids from Recombinant Proteins to Next-Generation Vaccines: Current Uses, Limitations, and Future Horizons

This study aims to highlight the potential use of cTNAs in therapeutic applications. The COVID-19 pandemic has led to significant use of coding therapeutic nucleic acids (cTNAs) in terms of DNA and mRNA in the development of vaccines. The use of cTNAs resulted in a paradigm shift in the therapeutic field. However, the injection of DNA or mRNA into the human body transforms cells into biological factories to produce the necessary proteins. Despite the success of cTNAs in the production of corona vaccines, they have several limitations such as instability, inability to cross biomembranes, immunogenicity, and the possibility of integration into the human genome. The chemical modification and utilization of smart drug delivery cargoes resolve cTNAs therapeutic problems. The success of cTNAs in corona vaccine production provides perspective for the eradication of influenza viruses, Zika virus, HIV, respiratory syncytial virus, Ebola virus, malaria, and future pandemics by quick vaccine design. Moreover, the progress cTNAs technology is promising for the development of therapy for genetic disease, cancer therapy, and currently incurable diseases.

Next-generation phenotyping integrated in a national framework for patients with ultrarare disorders improves genetic diagnostics and yields new molecular findings

Individuals with ultrarare disorders pose a structural challenge for healthcare systems since expert clinical knowledge is required to establish diagnoses. In TRANSLATE NAMSE, a 3-year prospective study, we evaluated a novel diagnostic concept based on multidisciplinary expertise in Germany. Here we present the systematic investigation of the phenotypic and molecular genetic data of 1,577 patients who had undergone exome sequencing and were partially analyzed with next-generation phenotyping approaches. Molecular genetic diagnoses were established in 32% of the patients totaling 370 distinct molecular genetic causes, most with prevalence below 1:50,000. During the diagnostic process, 34 novel and 23 candidate genotype-phenotype associations were identified, mainly in individuals with neurodevelopmental disorders. Sequencing data of the subcohort that consented to computer-assisted analysis of their facial images with GestaltMatcher could be prioritized more efficiently compared with approaches based solely on clinical features and molecular scores. Our study demonstrates the synergy of using next-generation sequencing and phenotyping for diagnosing ultrarare diseases in routine healthcare and discovering novel etiologies by multidisciplinary teams.

The Role of AI in Drug Discovery

The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This review paper elucidates the multifaceted applications of AI across various stages of drug development, highlighting significant advancements and methodologies. It delves into AI's instrumental role in drug design, polypharmacology, chemical synthesis, drug repurposing, and the prediction of drug properties such as toxicity, bioactivity, and physicochemical characteristics. Despite AI's promising advancements, the paper also addresses the challenges and limitations encountered in the field, including data quality, generalizability, computational demands, and ethical considerations. By offering a comprehensive overview of AI's role in drug discovery, this paper underscores the technology's potential to significantly enhance drug development, while also acknowledging the hurdles that must be overcome to fully realize its benefits.

Development of orphan drugs for rare diseases

Most rare diseases (orphan diseases) still lack approved treatment options despite major advances in research providing the necessary tools to understand their molecular basis and legislation providing regulatory and economic incentives to expedite the development of specific therapies. Addressing this translational gap is a multifaceted challenge, a key aspect of which is the selection of an optimal therapeutic modality to translate advances in rare disease knowledge to potential medicines known as orphan drugs. There are several strategies for developing orphan drugs for rare genetic disorders, including protein replacement therapies, small-molecule therapies (e.g., substrate reduction, chemical chaperone, cofactor, expression modification, and read-through therapies), monoclonal antibodies, antisense oligonucleotides, small interfering RNA or exon skipping therapies, gene replacement and direct genome-editing therapies, mRNA therapy, cell therapy, and drug repurposing. Each strategy has its own strengths and limitations in orphan drug development. Furthermore, numerous hurdles are present in clinical trials of rare genetic diseases because of difficulty with patient recruitment, unknown molecular physiology, the natural history of the disease, ethical concerns regarding pediatric patients, and regulatory challenges. To address these barriers, the rare genetic diseases community, including academic institutions, industry, patient advocacy groups, foundations, payers, and government regulatory and research organizations, must become engaged in discussions about these issues.

Regulation of Precise DNA Repair by Nuclear Actin Polymerization: A Chance for Improving Gene Therapy?

Although more difficult to detect than in the cytoplasm, it is now clear that actin polymerization occurs in the nucleus and that it plays a role in the specific processes of the nucleus such as transcription, replication, and DNA repair. A number of studies suggest that nuclear actin polymerization is promoting precise DNA repair by homologous recombination, which could potentially be of help for precise genome editing and gene therapy. This review summarizes the findings and describes the challenges and chances in the field.

The Multi-Omic Approach to Newborn Screening: Opportunities and Challenges

Newborn screening programs have seen significant evolution since their initial implementation more than 60 years ago, with the primary goal of detecting treatable conditions within the earliest possible timeframe to ensure the optimal treatment and outcomes for the newborn. New technologies have driven the expansion of screening programs to cover additional conditions. In the current era, the breadth of screened conditions could be further expanded by integrating omic technologies such as untargeted metabolomics and genomics. Genomic screening could offer opportunities for lifelong care beyond the newborn period. For genomic newborn screening to be effective and ready for routine adoption, it must overcome barriers such as implementation cost, public acceptability, and scalability. Metabolomics approaches, on the other hand, can offer insight into disease phenotypes and could be used to identify known and novel biomarkers of disease. Given recent advances in metabolomic technologies, alongside advances in genomics including whole-genome sequencing, the combination of complementary multi-omic approaches may provide an exciting opportunity to leverage the best of both approaches and overcome their respective limitations. These techniques are described, along with the current outlook on multi-omic-based NBS research.

The Role of Pharmacogenomics in Rare Diseases

Rare diseases have become an increasingly important public health priority due to their collective prevalence and often life-threatening nature. Incentive programs, such as the Orphan Drug Act have been introduced to increase the development of rare disease therapeutics. While the approval of these therapeutics requires supportive data from stringent pre-market studies, these data lack the ability to describe the causes of treatment response heterogeneity, leading to medications often being more harmful or less effective than predicted. If a Goal Line were to be used to describe the multifactorial continuum of phenotypic variations occurring in response to a medication, the 'Goal Posts', or the two defining points of this continuum, would be (1) Super-Response, or an extraordinary therapeutic effect; and (2) Serious Harm. Investigation of the pharmacogenomics behind these two extreme phenotypes can potentially lead to the development of new therapeutics, help inform rational use criteria in drug policy, and improve the understanding of underlying disease pathophysiology. In the context of rare diseases where cohort sizes are smaller than ideal, 'small data' and 'big data' approaches to data collection and analysis should be combined to produce the most robust results. This paper presents the importance of studying drug response in parallel to other research initiatives in rare diseases, as well as the need for international collaboration in the area of rare disease pharmacogenomics.

Drug repurposing for rare diseases

Repurposing drugs for rare diseases is a creative and cost-efficient method for creating new treatment options for certain conditions. This technique entails repurposing existing pharmaceuticals for new uses by utilizing established information regarding pharmacological characteristics, modes of operation, safety profiles, and interactions with biological systems. Creating new treatments for uncommon diseases is frequently difficult because of factors including small patient groups, disease intricacy, and insufficient knowledge of disease pathobiology. Drug repurposing is a more efficient and cost-effective approach compared to developing new drugs from scratch. It typically requires collaboration among academia, pharmaceutical firms, and patient advocacy groups.

Trends from two decades of orphan designations in paediatric rare neuromuscular diseases

Rare diseases are characterized by substantial unmet need mostly because the majority have limited, or no treatment options and a large number also affect children. Since the inception of EU orphan regulation in 2000 the European Medicines Agency Committee for Orphan Medicinal Products has received several applications for paediatric rare neuromuscular diseases (PERAN) however treatment options remain limited. Here we discuss the results form an observational, retrospective, cross-sectional study to characterize the currently authorised orphan medicinal products (OMP) and orphan designations (OD) given to products for PERAN in the last two decades. In the EU about half of PERAN diseases have at least one active OD approved since 2000, and about half of these are for Duchenne muscular dystrophy (DMD). The large majority of PERAN diseases do not have an authorised medicine with only 6 OMP currently authorised for Spinal muscular atrophy (3); DMD (1) and Myasthenia gravis (2). One in five products have inactive or discontinued regulatory development but clinical trials are ongoing for the vast majority of PERAN diseases, and more than half are in the final stage of clinical research with significantly more products with medical plausibility based in clinical data reaching advanced stages in clinical development.

Fair Funding Decisions: Consistency of the Time Horizons Used in the Calculation of Quality-Adjusted Life Years for Therapies for Very Rare Diseases by the National Institute for Health and Care Excellence in England

The National Institute for Health and Care Excellence (NICE) in England uses quality-adjusted life years (QALYs) to assess the cost-effectiveness of treatments. A QALY is a measure that combines the size of the clinical benefit of a treatment with the time the patient benefits from it, i.e., the time horizon. We wanted to know how consistently QALY gains are calculated at NICE. Therefore, we have analysed information on the time horizons used for the QALY calculations of the concluded evaluations conducted under the Highly Specialised Technologies programme for treatments of very rare diseases at NICE. For treatments with final guidance published by December 2023 (n = 29), a time horizon of median 97.5 years (range: 35 to 125 years) was used to calculate the QALY gains. For most QALY calculations, the accepted time horizon was longer than either the expected treatment duration or the estimated life expectancy. In contrast, for the only technology with a final negative funding decision, i.e., afamelanotide for treating the lifelong chronic disease erythropoietic protoporphyria, a time horizon that was shorter than the expected treatment duration was used. The fairness and consistency of the evaluation process of treatments for very rare diseases at NICE should be reviewed.

E-Health & Innovation to Overcome Barriers in Neuromuscular Diseases. Report from the 3rd eNMD Congress: Pisa, Italy, 29-30 October 2021: Remote Monitoring: New Solutions for New Avenues in Neuromuscular Disorders

Neuromuscular diseases (NMDs), in their phenotypic heterogeneity, share quite invariably common issues that involve several clinical and socio-economical aspects, needing a deep critical analysis to develop better management strategies. From diagnosis to treatment and follow-up, the development of technological solutions can improve the detection of several critical aspects related to the diseases, addressing both the met and unmet needs of clinicians and patients. Among several aspects of the digital transformation of health and care, this congress expands what has been learned from previous congresses editions on applicability and usefulness of technological solutions in NMDs. In particular the focus on new solutions for remote monitoring provide valuable insights to increase disease-specific knowledge and trigger prompt decision-making. In doing that, several perspectives from different areas of expertise were shared and discussed, pointing out strengths and weaknesses on the current state of the art on topic, suggesting new research lines to advance technology in this specific clinical field.

Systematic and quantitative analysis of stop codon readthrough in Rett syndrome nonsense mutations

Rett syndrome (RTT) is a neurodevelopmental disorder resulting from genetic mutations in the methyl CpG binding protein 2 (MeCP2) gene. Specifically, around 35% of RTT patients harbor premature termination codons (PTCs) within the MeCP2 gene due to nonsense mutations. A promising therapeutic avenue for these individuals involves the use of aminoglycosides, which stimulate translational readthrough (TR) by causing stop codons to be interpreted as sense codons. However, the effectiveness of this treatment depends on several factors, including the type of stop codon and the surrounding nucleotides, collectively referred to as the stop codon context (SCC). Here, we develop a high-content reporter system to precisely measure TR efficiency at different SCCs, assess the recovery of the full-length MeCP2 protein, and evaluate its subcellular localization. We have conducted a comprehensive investigation into the intricate relationship between SCC characteristics and TR induction, examining a total of 14 pathogenic MeCP2 nonsense mutations with the aim to advance the prospects of personalized therapy for individuals with RTT. Our results demonstrate that TR induction can successfully restore full-length MeCP2 protein, albeit to varying degrees, contingent upon the SCC and the specific position of the PTC within the MeCP2 mRNA. TR induction can lead to the re-establishment of nuclear localization of MeCP2, indicating the potential restoration of protein functionality. In summary, our findings underscore the significance of SCC-specific approaches in the development of tailored therapies for RTT. By unraveling the relationship between SCC and TR therapy, we pave the way for personalized, individualized treatment strategies that hold promise for improving the lives of individuals affected by this debilitating neurodevelopmental disorder. KEY MESSAGES: The efficiency of readthrough induction at MeCP2 premature termination codons strongly depends on the stop codon context. The position of the premature termination codon on the transcript influences the readthrough inducibility. A new high-content dual reporter assay facilitates the measurement and prediction of readthrough efficiency of specific nucleotide stop contexts. Readthrough induction results in the recovery of full-length MeCP2 and its re-localization to the nucleus. MeCP2 requires only one of its annotated nuclear localization signals.

How to develop new systemic treatments in ultra-rare cancers with high unmet needs? The case of alveolar soft-part sarcoma

Developing new drugs or generating evidence for existing drugs in new indications for ultra-rare cancers is complex and carries a high-risk of failure. This gets even harder in ultra-rare tumours, which have an annual incidence of 1 per 1,000,000 population or less. Here, we illustrate the problem of adequate evidence generation in ultra-rare tumours, using Alveolar Soft-Part Sarcomas (ASPS) - an ultra-rare sarcoma newly diagnosed in approximately 60 persons a year in the European Union - as an exemplar case showing challenges in development despite being potentially relevant for classes of agents. We discuss some possible approaches for addressing such challenges, especially focussing on constructive collaboration between academic groups, patients and advocates, drug manufacturers, and regulators to optimise drug development in ultra-rare cancers. This article, written by various European stakeholders, proposes a way forward to ultimately get better options for patients with ultra-rare cancers.

Rare diseases and pyruvate kinase M2: a promising therapeutic connection

Pyruvate kinase M2 (PKM2) is a key glycolytic enzyme that regulates proliferating cell metabolism. The role of PKM2 in common diseases has been well established, but its role in rare diseases (RDs) is less understood. Over the past few years, PKM2 has emerged as a crucial player in RDs, including, neoplastic, respiratory, metabolic, and neurological disorders. Herein, we summarize recent findings and developments highlighting PKM2 as an emerging key player in RDs. We also discuss the current status of PKM2 modulation in RDs with particular emphasis on preclinical and clinical studies in addition to current challenges in the field.