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

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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

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.

Functional prediction of the potential NGLY1 mutations associated with rare disease CDG

Genetic diseases are currently diagnosed by functional mutations. However, only some mutations are associated with disease. It is necessary to establish a quick prediction model for clinical screening. Pathogenic mutations in NGLY1 cause a rare autosomal recessive disease known as congenital disorder of deglycosylation (NGLY1-CDDG). Although NGLY1-CDDG can be diagnosed through gene sequencing, clinical relevance of a detected mutation in NGLY1 needs to be further confirmed. In this study, taken NGLY1-CDDG as an example, a comprehensive and practical predictive model for pathogenic mutations on NGLY1 through an NGLY1/Glycopeptide complex model was constructed, the binding sites of NGLY1 and glycopeptides were simulated, and an in vitro enzymatic assay system was established to facilitate quick clinical decisions for NGLY1-CDDG patients. The docking model covers 42 % of reported NGLY1-CDDG missense mutations (5/12). All reported mutations were subjected to in vitro enzymatic assay in which 18 mutations were dysfunctional (18/30). In addition, a full spectrum of functional R328 mutations was assayed and 11 mutations were dysfunctional (11/19). In this study, a model of NGLY1 and glycopeptides was built for potential functional mutations in NGLY1. In addition, the effect of potential regulatory compounds, including N-acetyl-l-cysteine and dithiothreitol, on NGLY1 was examined. The established in vitro assay may serve as a standard protocol to facilitate rapid diagnosis of all mutations in NGLY1-CDDG. This method could also be applied as a comprehensive and practical predictive model for the other rare genetic diseases.

Tribulations and future opportunities for artificial intelligence in precision medicine

Upon a diagnosis, the clinical team faces two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate the reported response from relevant clinical trials. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies with the changes in their condition. In practice, the drug and the dose selection depend significantly on the medical protocol and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data and Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit their application. AI is a rapidly evolving and dynamic field with the potential to revolutionize various aspects of human life. AI has become increasingly crucial in drug discovery and development. AI enhances decision-making across different disciplines, such as medicinal chemistry, molecular and cell biology, pharmacology, pathology, and clinical practice. In addition to these, AI contributes to patient population selection and stratification. The need for AI in healthcare is evident as it aids in enhancing data accuracy and ensuring the quality care necessary for effective patient treatment. AI is pivotal in improving success rates in clinical practice. The increasing significance of AI in drug discovery, development, and clinical trials is underscored by many scientific publications. Despite the numerous advantages of AI, such as enhancing and advancing Precision Medicine (PM) and remote patient monitoring, unlocking its full potential in healthcare requires addressing fundamental concerns. These concerns include data quality, the lack of well-annotated large datasets, data privacy and safety issues, biases in AI algorithms, legal and ethical challenges, and obstacles related to cost and implementation. Nevertheless, integrating AI in clinical medicine will improve diagnostic accuracy and treatment outcomes, contribute to more efficient healthcare delivery, reduce costs, and facilitate better patient experiences, making healthcare more sustainable. This article reviews AI applications in drug development and clinical practice, making healthcare more sustainable, and highlights concerns and limitations in applying AI.

Prospective cohort study of genomic newborn screening: BabyScreen+ pilot study protocol

INTRODUCTION

Newborn bloodspot screening (NBS) is a highly successful public health programme that uses biochemical and other assays to screen for severe but treatable childhood-onset conditions. Introducing genomic sequencing into NBS programmes increases the range of detectable conditions but raises practical and ethical issues. Evidence from prospectively ascertained cohorts is required to guide policy and future implementation. This study aims to develop, implement and evaluate a genomic NBS (gNBS) pilot programme.

METHODS AND ANALYSIS

The BabyScreen+ study will pilot gNBS in three phases. In the preimplementation phase, study materials, including education resources, decision support and data collection tools, will be designed. Focus groups and key informant interviews will also be undertaken to inform delivery of the study and future gNBS programmes. During the implementation phase, we will prospectively recruit birth parents in Victoria, Australia, to screen 1000 newborns for over 600 severe, treatable, childhood-onset conditions. Clinically accredited whole genome sequencing will be performed following standard NBS using the same sample. High chance results will be returned by genetic healthcare professionals, with follow-on genetic and other confirmatory testing and referral to specialist services as required. The postimplementation phase will evaluate the feasibility of gNBS as the primary aim, and assess ethical, implementation, psychosocial and health economic factors to inform future service delivery.

ETHICS AND DISSEMINATION

This project received ethics approval from the Royal Children's Hospital Melbourne Research Ethics Committee: HREC/91500/RCHM-2023, HREC/90929/RCHM-2022 and HREC/91392/RCHM-2022. Findings will be disseminated to policy-makers, and through peer-reviewed journals and conferences.

A mouse model of Zhu-Tokita-Takenouchi-Kim syndrome reveals indispensable SON functions in organ development and hematopoiesis

Rare diseases are underrepresented in biomedical research, leading to insufficient awareness. Zhu-Tokita-Takenouchi-Kim (ZTTK) syndrome is a rare disease caused by genetic alterations that result in heterozygous loss of function of SON. While patients with ZTTK syndrome live with numerous symptoms, the lack of model organisms hampers our understanding of SON and this complex syndrome. Here, we developed Son haploinsufficiency (Son+/-) mice as a model of ZTTK syndrome and identified the indispensable roles of Son in organ development and hematopoiesis. Son+/- mice recapitulated clinical symptoms of ZTTK syndrome, including growth retardation, cognitive impairment, skeletal abnormalities, and kidney agenesis. Furthermore, we identified hematopoietic abnormalities in Son+/- mice, including leukopenia and immunoglobulin deficiency, similar to those observed in human patients. Surface marker analyses and single-cell transcriptome profiling of hematopoietic stem and progenitor cells revealed that Son haploinsufficiency shifted cell fate more toward the myeloid lineage but compromised lymphoid lineage development by reducing genes required for lymphoid and B cell lineage specification. Additionally, Son haploinsufficiency caused inappropriate activation of erythroid genes and impaired erythropoiesis. These findings highlight the importance of the full gene expression of Son in multiple organs. Our model serves as an invaluable research tool for this rare disease and related disorders associated with SON dysfunction.

Cell-cell interaction in the pathogenesis of inherited retinal diseases

The retina is part of the central nervous system specialized for vision. Inherited retinal diseases (IRD) are a group of clinically and genetically heterogenous disorders that lead to progressive vision impairment or blindness. Although each disorder is rare, IRD accumulatively cause blindness in up to 5.5 million individuals worldwide. Currently, the pathophysiological mechanisms of IRD are not fully understood and there are limited treatment options available. Most IRD are caused by degeneration of light-sensitive photoreceptors. Genetic mutations that abrogate the structure and/or function of photoreceptors lead to visual impairment followed by blindness caused by loss of photoreceptors. In healthy retina, photoreceptors structurally and functionally interact with retinal pigment epithelium (RPE) and Müller glia (MG) to maintain retinal homeostasis. Multiple IRD with photoreceptor degeneration as a major phenotype are caused by mutations of RPE- and/or MG-associated genes. Recent studies also reveal compromised MG and RPE caused by mutations in ubiquitously expressed ciliary genes. Therefore, photoreceptor degeneration could be a direct consequence of gene mutations and/or could be secondary to the dysfunction of their interaction partners in the retina. This review summarizes the mechanisms of photoreceptor-RPE/MG interaction in supporting retinal functions and discusses how the disruption of these processes could lead to photoreceptor degeneration, with an aim to provide a unique perspective of IRD pathogenesis and treatment paradigm. We will first describe the biology of retina and IRD and then discuss the interaction between photoreceptors and MG/RPE as well as their implications in disease pathogenesis. Finally, we will summarize the recent advances in IRD therapeutics targeting MG and/or RPE.

Rare diseases: still on the fringes of universal health coverage in Europe

Despite general advancements in population health indicators and universal health coverage, people living with rare diseases and their families still experience considerable unmet needs, including prolonged diagnostic journeys, limited treatment options, and a huge psychosocial burden due to the lack of coordinated, integrated care. Attainment of universal health coverage for rare diseases is dependent on fundamentally different health determinants and demands for different solutions. This involves consolidating expertise through Centers of Excellence, establishing efficient care pathways, fostering extensive collaboration at European and global levels in research and healthcare, and putting patients at the center of care. Furthermore, development of specific indicators and coding systems is crucial for monitoring progress. Only in this way Europe can strive towards a future where people living with rare diseases receive the same level of equitable, safe, high-quality healthcare as other members of the society, in alignment with the overarching goal of leaving no one behind.

New orphan disease therapies from the proteome of industrial plasma processing waste- a treatment for aceruloplasminemia

Plasma-derived therapeutic proteins are produced through an industrial fractionation process where proteins are purified from individual intermediates, some of which remain unused and are discarded. Relatively few plasma-derived proteins are exploited clinically, with most of available plasma being directed towards the manufacture of immunoglobulin and albumin. Although the plasma proteome provides opportunities to develop novel protein replacement therapies, particularly for rare diseases, the high cost of plasma together with small patient populations impact negatively on the development of plasma-derived orphan drugs. Enabling therapeutics development from unused plasma fractionation intermediates would therefore constitute a substantial innovation. To this objective, we characterized the proteome of unused plasma fractionation intermediates and prioritized proteins for their potential as new candidate therapies for human disease. We selected ceruloplasmin, a plasma ferroxidase, as a potential therapy for aceruloplasminemia, an adult-onset ultra-rare neurological disease caused by iron accumulation as a result of ceruloplasmin mutations. Intraperitoneally administered ceruloplasmin, purified from an unused plasma fractionation intermediate, was able to prevent neurological, hepatic and hematological phenotypes in ceruloplasmin-deficient mice. These data demonstrate the feasibility of transforming industrial waste plasma fraction into a raw material for manufacturing of new candidate proteins for replacement therapies, optimizing plasma use and reducing waste generation.

Artificial Intelligence for Drug Discovery: Are We There Yet?

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful drug discovery requires optimizing properties related to pharmacodynamics, pharmacokinetics, and clinical outcomes. This review discusses the use of AI in the three pillars of drug discovery: diseases, targets, and therapeutic modalities, with a focus on small-molecule drugs. AI technologies, such as generative chemistry, machine learning, and multiproperty optimization, have enabled several compounds to enter clinical trials. The scientific community must carefully vet known information to address the reproducibility crisis. The full potential of AI in drug discovery can only be realized with sufficient ground truth and appropriate human intervention at later pipeline stages.

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.Communicated by Ramaswamy H. Sarma.

High-content screening identifies a small molecule that restores AP-4-dependent protein trafficking in neuronal models of AP-4-associated hereditary spastic paraplegia

Unbiased phenotypic screens in patient-relevant disease models offer the potential to detect therapeutic targets for rare diseases. In this study, we developed a high-throughput screening assay to identify molecules that correct aberrant protein trafficking in adapter protein complex 4 (AP-4) deficiency, a rare but prototypical form of childhood-onset hereditary spastic paraplegia characterized by mislocalization of the autophagy protein ATG9A. Using high-content microscopy and an automated image analysis pipeline, we screened a diversity library of 28,864 small molecules and identified a lead compound, BCH-HSP-C01, that restored ATG9A pathology in multiple disease models, including patient-derived fibroblasts and induced pluripotent stem cell-derived neurons. We used multiparametric orthogonal strategies and integrated transcriptomic and proteomic approaches to delineate potential mechanisms of action of BCH-HSP-C01. Our results define molecular regulators of intracellular ATG9A trafficking and characterize a lead compound for the treatment of AP-4 deficiency, providing important proof-of-concept data for future studies.

Drug repurposing for rare: progress and opportunities for the rare disease community

Repurposing is one of the key opportunities to address the unmet rare diseases therapeutic need. Based on cases of drug repurposing in small population conditions, and previous work in drug repurposing, we analyzed the most important lessons learned, such as the sharing of clinical observations, reaching out to regulatory scientific advice at an early stage, and public-private collaboration. In addition, current upcoming trends in the field of drug repurposing in rare diseases were analyzed, including the role these trends could play in the rare diseases' ecosystem. Specifically, we cover the opportunities of innovation platforms, the use of real-world data, the use of artificial intelligence, regulatory initiatives in repurposing, and patient engagement throughout the repurposing project. The outcomes from these emerging activities will help progress the field of drug repurposing for the benefit of patients, public health and medicines development.

Highly efficient capture approach for the identification of diverse inherited retinal disorders

Our study presents a 319-gene panel targeting inherited retinal dystrophy (IRD) genes. Through a multi-center retrospective cohort study, we validated the assay's effectiveness and clinical utility and characterized the mutation spectrum of Taiwanese IRD patients. Between January 2018 and May 2022, 493 patients in 425 unrelated families, all initially suspected of having IRD without prior genetic diagnoses, underwent detailed ophthalmic and physical examinations (with extra-ocular features recorded) and genetic testing with our customized panel. Disease-causing variants were identified by segregation analysis and clinical interpretation, with validation via Sanger sequencing. We achieved a read depth of >200× for 94.2% of the targeted 1.2 Mb region. 68.5% (291/425) of the probands received molecular diagnoses, with 53.9% (229/425) resolved cases. Retinitis pigmentosa (RP) is the most prevalent initial clinical impression (64.2%), and 90.8% of the cohort have the five most prevalent phenotypes (RP, cone-rod syndrome, Usher's syndrome, Leber's congenital amaurosis, Bietti crystalline dystrophy). The most commonly mutated genes of probands that received molecular diagnosis are USH2A (13.7% of the cohort), EYS (11.3%), CYP4V2 (4.8%), ABCA4 (4.5%), RPGR (3.4%), and RP1 (3.1%), collectively accounted for 40.8% of diagnoses. We identify 87 unique unreported variants previously not associated with IRD and refine clinical diagnoses for 21 patients (7.22% of positive cases). We developed a customized gene panel and tested it on the largest Taiwanese cohort, showing that it provides excellent coverage for diverse IRD phenotypes.