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

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.

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.

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.

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.

Schizophrenia interactome derived repurposable drugs and randomized control trials of two candidates

There is a substantial unmet need for effective and patient-acceptable drugs to treat severe mental illnesses like schizophrenia. Computational analysis of genomic, transcriptomic, and pharmacologic data generated in the past two decades enables repurposing of drugs or compounds with acceptable safety profiles, namely those that are FDA-approved or reached late stages in clinical trials. We developed a rational approach to achieve this computationally for schizophrenia 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: their target networks were enriched for pathways relevant to schizophrenia etiology or for genes that had an association with diseases pathogenically similar to schizophrenia. To translate these computational results to the clinic, these shortlisted drugs must be tested empirically through randomized controlled trials (RCT), where their prior safety approvals obviate the need for time-consuming phase I and II studies. We selected two among the shortlisted candidates based on likely adherence and side effect profiles. We are testing them through adjunctive RCTs for patients with schizophrenia 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 future and should also be exploited for other psychiatric disorders.

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.

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.

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.

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.

Determining Commonalities in the Experiences of Patients with Rare Diseases: A Qualitative Analysis of US Food and Drug Administration Patient Engagement Sessions

BACKGROUND

Rare diseases are estimated to affect more than one in ten Americans. However, most patients with a rare disease face significant emotional, physical, and social challenges. To better understand the burden of disease and unmet needs, the US Food and Drug Administration (FDA) conducts and supports multiple patient engagement platforms. We analyzed summaries from these discussions to identify commonalities among patients with disparate rare diseases, the results of which could inform priorities for cross-disease policies and medical product development.

METHODS

We conducted a qualitative analysis of patient engagement session summaries to investigate shared experiences across rare diseases. Cross-disease similarities were identified within four dimensions: product development/regulatory, clinical/physical, social/psychological, and economic/financial. Summaries from 29 rare diseases were included in our analyses.

RESULTS

Within the product development/regulatory dimension, we observed that patients and caregivers across rare diseases shared the desire for development of medical products that cured their disease or improved their overall quality of life. In the clinical/physical dimension, we found that patients had numerous common symptoms, including pain and fatigue. In the social/psychological dimension, we observed significant negative impact on mental health. Within the economic/financial dimension, patients and caregivers shared that disease burden caused significant financial hardships.

CONCLUSION

We found remarkable similarities among patients with rare diseases across all four dimensions. Our results indicate that, even among rare diseases with diverse etiologies, patients share numerous commonalties due to their diseases: a lack of effective treatment options, certain physical symptoms, mental health challenges, and financial concerns.

En Route to Targeted Ribosome Editing to Replenish Skin Anchor Protein LAMB3 in Junctional Epidermolysis Bullosa

Severe junctional epidermolysis bullosa is a rare genetic, postpartum lethal skin disease, predominantly caused by nonsense/premature termination codon (PTC) sequence variants in LAMB3 gene. LAMB3 encodes LAMB3, the β subunit of epidermal-dermal skin anchor laminin 332. Most translational reads of a PTC mRNA deliver truncated, nonfunctional proteins, whereas an endogenous PTC readthrough mechanism produces full-length protein at minimal and insufficient levels. Conventional translational readthrough-inducing drugs amplify endogenous PTC readthrough; however, translational readthrough-inducing drugs are either proteotoxic or nonselective. Ribosome editing is a more selective and less toxic strategy. This technique identified ribosomal protein L35/uL29 (ie, RpL35) and RpL35-ligands repurposable drugs artesunate and atazanavir as molecular tools to increase production levels of full-length LAMB3. To evaluate ligand activity in living cells, we monitored artesunate and atazanavir treatment by dual luciferase reporter assays. Production levels of full-length LAMB3 increased up to 200% upon artesunate treatment, up to 150% upon atazanavir treatment, and up to 170% upon combinatorial treatment of RpL35 ligands at reduced drug dosage, with an unrelated PTC reporter being nonresponsive. Proof of bioactivity of RpL35 ligands in selective increase of full-length LAMB3 provides the basis for an alternative, targeted therapeutic route to replenish LAMB3 in severe junctional epidermolysis bullosa.

The best of both worlds: Blending cutting-edge research with clinical processes for a productive exome clinic

Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes. Our program is enabled by a cost-effective investment by the health system and is unique in encompassing all the processes that have been variably included in other hybrid/clinical programs. These include careful patient selection, utilization of a phenotype-agnostic bioinformatics pipeline followed by manual curation of variants and phenotype integration by clinicians, close collaborations between the clinicians and the bioinformatician, pursuit of interesting variants, communication of results to patients in categories that are predicated upon the certainty of a diagnosis, and tracking changes in results over time and the underlying mechanisms for such changes. Due to its effectiveness, scalability to GS and its resource efficiency, specific elements of our paradigm can be incorporated into existing clinical settings, or the entire hybrid model can be implemented within health systems that have genomic medicine programs, to provide NGS in a scientifically rigorous, yet pragmatic setting.

Therapeutic potential of natural antisense transcripts and various mechanisms involved for clinical applications and disease prevention

Antisense transcription, a prevalent occurrence in mammalian genomes, gives rise to natural antisense transcripts (NATs) as RNA molecules. These NATs serve as agents of diverse transcriptional and post-transcriptional regulatory mechanisms, playing crucial roles in various biological processes vital for cell function and immune response. However, when their normal functions are disrupted, they can contribute to human diseases. This comprehensive review aims to establish the molecular foundation linking NATs to the development of disorders like cancer, neurodegenerative conditions, and cardiovascular ailments. Additionally, we evaluate the potential of oligonucleotide-based therapies targeting NATs, presenting both their advantages and limitations, while also highlighting the latest advancements in this promising realm of clinical investigation.Abbreviations: NATs- Natural antisense transcripts, PRC1- Polycomb Repressive Complex 1, PRC2- Polycomb Repressive Complex 2, ADARs- Adenosine deaminases acting on RNA, BDNF-AS- Brain-derived neurotrophic factor antisense transcript, ASOs- Antisense oligonucleotides, SINEUPs- Inverted SINEB2 sequence-mediated upregulating molecules, PTBP1- Polypyrimidine tract binding protein-1, HNRNPK- heterogeneous nuclear ribonucleoprotein K, MAPT-AS1- microtubule-associated protein tau antisense 1, KCNQ1OT- (KCNQ1 opposite strand/antisense transcript 1, ERK- extracellular signal-regulated kinase 1, USP14- ubiquitin-specific protease 14, EGF- Epidermal growth factor, LSD1- Lysine Specific Demethylase 1, ANRIL- Antisense Noncoding RNA in the INK4 Locus, BWS- Beckwith-Wiedemann syndrome, VEGFA- Vascular Endothelial Growth component A.

Gene-editing technology, from macromolecule therapeutics to organ transplantation: Applications, limitations, and prospective uses

Gene editing technologies (GETs) could induce gene knockdown or gene knockout for biomedical applications. The clinical success of gene silence by RNAi therapies pays attention to other GETs as therapeutic approaches. This review aims to highlight GETs, categories, mechanisms, challenges, current use, and prospective applications. The different academic search engines, electronic databases, and bibliographies of selected articles were used in the preparation of this review with a focus on the fundamental considerations. The present results revealed that, among GETs, CRISPR/Cas9 has higher editing efficiency and targeting specificity compared to other GETs to insert, delete, modify, or replace the gene at a specific location in the host genome. Therefore, CRISPR/Cas9 is talented in the production of molecular, tissue, cell, and organ therapies. Consequently, GETs could be used in the discovery of innovative therapeutics for genetic diseases, pandemics, cancer, hopeless diseases, and organ failure. Specifically, GETs have been used to produce gene-modified animals to spare human organ failure. Genetically modified pigs are used in clinical trials as a source of heart, liver, kidneys, and lungs for xenotransplantation (XT) in humans. Viral, non-viral, and hybrid vectors have been utilized for the delivery of GETs with some limitations. Therefore, extracellular vesicles (EVs) are proposed as intelligent and future cargoes for GETs delivery in clinical applications. This study concluded that GETs are promising for the production of molecular, cellular, and organ therapies. The use of GETs as XT is still in the early stage as well and they have ethical and biosafety issues.

The future of rare disease drug development: the rare disease cures accelerator data analytics platform (RDCA-DAP)

Rare disease drug development is wrought with challenges not the least of which is access to the limited data currently available throughout the rare disease ecosystem where sharing of the available data is not guaranteed. Most pharmaceutical sponsors seeking to develop agents to treat rare diseases will initiate data landscaping efforts to identify various data sources that might be informative with respect to disease prevalence, patient selection and identification, disease progression and any data projecting likelihood of patient response to therapy including any genetic data. Such data are often difficult to come by for highly prevalent, mainstream disease populations let alone for the 8000 rare disease that make up the pooled patient population of rare disease patients. The future of rare disease drug development will hopefully rely on increased data sharing and collaboration among the entire rare disease ecosystem. One path to achieving this outcome has been the development of the rare disease cures accelerator, data analytics platform (RDCA-DAP) funded by the US FDA and operationalized by the Critical Path Institute. FDA intentions were clearly focused on improving the quality of rare disease regulatory applications by sponsors seeking to develop treatment options for various rare disease populations. As this initiative moves into its second year of operations it is envisioned that the increased connectivity to new and diverse data streams and tools will result in solutions that benefit the entire rare disease ecosystem and that the platform becomes a Collaboratory for engagement of this ecosystem that also includes patients and caregivers.

A mouse model of ZTTK 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 ZTTK syndrome patients suffer from numerous symptoms, the lack of model organisms hamper our understanding of both 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, 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 inclines cell fate toward the myeloid lineage but compromises lymphoid lineage development by reducing key genes required for lymphoid and B cell lineage specification. Additionally, Son haploinsufficiency causes inappropriate activation of erythroid genes and impaired erythroid maturation. These findings highlight the importance of the full gene dosage of Son in organ development and hematopoiesis. Our model serves as an invaluable research tool for this rare disease and related disorders associated with SON dysfunction.

Ultrarapid-Acting Microneedles for Immediate Delivery of Biotherapeutics

Subcutaneous (SC) injection is a common administration route for rapid and efficient delivery of biotherapeutics. However, syringe-based injections usually require professional assistance and are associated with pain and potential risks of infections, thus leading to undesired patient compliance and poor life quality. Herein, this work presents an ultrarapid-acting microneedle (URA-MN) patch for immediate transdermal delivery of therapeutics in a minimally invasive manner. Effervescent agents are incorporated into the tip of URA-MN for rapid generation of CO2 bubbles upon insertion into the skin, immediately powering the biotherapeutics release within a few minutes. The release kinetics of diverse agents including liraglutide (LRT), insulin, and heparin from the URA-MN patches are evaluated in three different mouse models, and the rapid release of biotherapeutics and potent therapeutic effects are achieved with only 5 min administration. Noteworthily, attributed to the short application duration and negligible residuals of MN matrix remaining in the skin, the URA-MN patch shows desirable biocompatibility after six-week administration.

Genomic newborn screening for rare diseases

Rare diseases are a leading cause of infant mortality and lifelong disability. To improve outcomes, timely diagnosis and effective treatments are needed. Genomic sequencing has transformed the traditional diagnostic process, providing rapid, accurate and cost-effective genetic diagnoses to many. Incorporating genomic sequencing into newborn screening programmes at the population scale holds the promise of substantially expanding the early detection of treatable rare diseases, with stored genomic data potentially benefitting health over a lifetime and supporting further research. As several large-scale newborn genomic screening projects launch internationally, we review the challenges and opportunities presented, particularly the need to generate evidence of benefit and to address the ethical, legal and psychosocial issues that genomic newborn screening raises.

Protein-based Nanoparticles: From Drug Delivery to Imaging, Nanocatalysis and Protein Therapy

Proteins and enzymes are versatile biomaterials for a wide range of medical applications due to their high specificity for receptors and substrates, high degradability, low toxicity, and overall good biocompatibility. Protein nanoparticles are formed by the arrangement of several native or modified proteins into nanometer-sized assemblies. In this review, we will focus on artificial nanoparticle systems, where proteins are the main structural element and not just an encapsulated payload. While under natural conditions, only certain proteins form defined aggregates and nanoparticles, chemical modifications or a change in the physical environment can further extend the pool of available building blocks. This allows the assembly of many globular proteins and even enzymes. These advances in preparation methods led to the emergence of new generations of nanosystems that extend beyond transport vehicles to diverse applications, from multifunctional drug delivery to imaging, nanocatalysis and protein therapy.

Toward responsible clinical n-of-1 strategies for rare diseases

N-of-1 strategies can provide high-quality evidence of treatment efficacy at the individual level and optimize evidence-based selection of off-label treatments for patients with rare diseases. Given their design characteristics, n-of-1 strategies are considered to lay at the intersection between medical research and clinical care. Therefore, whether n-of-1 strategies should be governed by research or care regulations remains a debated issue. Here, we delineate differences between medical research and optimized clinical care, and distinguish the regulations which apply to either. We also set standards for responsible optimized clinical n-of-1 strategies with (off-label) treatments for rare diseases. Implementing clinical n-of-1 strategies as defined here could aid in optimized treatment selection for such diseases.

The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders

Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.

Pharmacovigilance for rare diseases: a bibliometrics and knowledge-map analysis based on web of science

OBJECTIVES

The aims of this paper is to search and explore publications in the field of pharmacovigilance for rare diseases and to visualize general information, research hotspots, frontiers and future trends in the field using the bibliometric tool CiteSpace to provide evidence-based evidence for scholars.

METHODS

We searched the Web of Science Core Collection (WoSCC) for studies related to pharmacovigilance for rare diseases, spanning January 1, 1997-October 25, 2022. CiteSpace software was utilized to discuss countries/regions, institutions, authors, journals, and keywords.

RESULTS

After screening, a total of 599 valid publications were included in this study, with a significant upward trend in the number of publications. These studies were from 68 countries/regions with the United States and the United Kingdom making the largest contributions to the field. 4,806 research scholars from 493 institutions conducted studies on pharmacovigilance for rare diseases. Harvard University and University of California were the top two productive institutions in the research field. He Dian of the Affiliated Hospital of Guizhou Medical University and Peter G.M. Mol of the University of Groningen, The Netherlands, were the two most prolific researchers. The Cochrane Database of Systematic Reviews and the New England Journal of Medicine were the journals with the highest number of articles and co-citation frequency respectively. Clinical trial, therapy and adverse event were the top three most cited keywords.

CONCLUSIONS

Based on keywords co-occurrence analysis, four research topics were identified: orphan drug clinical trials, postmarketing ADR surveillance for orphan drugs, rare diseases and orphan drug management, and diagnosis and treatment of rare diseases. Immune-related adverse reactions and benefit-risk assessment of enzyme replacement therapy were at the forefront of research in this field. Treatment outcomes, early diagnosis and natural history studies of rare diseases may become hotspots for future research.

AutoCore: A network-based definition of the core module of human autoimmunity and autoinflammation

Although research on rare autoimmune and autoinflammatory diseases has enabled definition of nonredundant regulators of homeostasis in human immunity, because of the single gene-single disease nature of many of these diseases, contributing factors were mostly unveiled in sequential and noncoordinated individual studies. We used a network-based approach for integrating a set of 186 inborn errors of immunity with predominant autoimmunity/autoinflammation into a comprehensive map of human immune dysregulation, which we termed "AutoCore." The AutoCore is located centrally within the interactome of all protein-protein interactions, connecting and pinpointing multidisease markers for a range of common, polygenic autoimmune/autoinflammatory diseases. The AutoCore can be subdivided into 19 endotypes that correspond to molecularly and phenotypically cohesive disease subgroups, providing a molecular mechanism-based disease classification and rationale toward systematic targeting for therapeutic purposes. Our study provides a proof of concept for using network-based methods to systematically investigate the molecular relationships between individual rare diseases and address a range of conceptual, diagnostic, and therapeutic challenges.

RDKG-115: Assisting drug repurposing and discovery for rare diseases by trimodal knowledge graph embedding

Rare diseases (RDs) may affect individuals in small numbers, but they have a significant impact on a global scale. Accurate diagnosis of RDs is challenging, and there is a severe lack of drugs available for treatment. Pharmaceutical companies have shown a preference for drug repurposing from existing drugs developed for other diseases due to the high investment, high risk, and long cycle involved in RD drug development. Compared to traditional approaches, knowledge graph embedding (KGE) based methods are more efficient and convenient, as they treat drug repurposing as a link prediction task. KGE models allow for the enrichment of existing knowledge by incorporating multimodal information from various sources. In this study, we constructed RDKG-115, a rare disease knowledge graph involving 115 RDs, composed of 35,643 entities, 25 relations, and 5,539,839 refined triplets, based on 372,384 high-quality literature and 4 biomedical datasets: DRKG, Pathway Commons, PharmKG, and PMapp. Subsequently, we developed a trimodal KGE model containing structure, category, and description embeddings using reverse-hyperplane projection. We utilized this model to infer 4199 reliable new inferred triplets from RDKG-115. Finally, we calculated potential drugs and small molecules for each of the 115 RDs, taking multiple sclerosis as a case study. This study provides a paradigm for large-scale screening of drug repurposing and discovery for RDs, which will speed up the drug development process and ultimately benefit patients with RDs. The source code and data are available at https://github.com/ZhuChaoY/RDKG-115.

In-depth understanding of higher-order genome architecture in orphan cancer

The human genome is intertwined, folded, condensed, and gradually constitutes the 3D architecture, thereby affecting transcription and widely involving in tumorigenesis. Incidence and mortality rates for orphan cancers increase due to poor early diagnosis and lack of effective medical treatments, which are now getting attention. In-depth understanding in tumorigenesis has fast-tracked over the last decade, however, the further role and mechanism of 3D genome organization in variant orphan tumorigenesis remains to be fully understood. We summarize for the first time that higher-order genome organization can provide novel insights into the occurrence mechanisms of orphan cancers, and discuss probable future research directions for drug development and anti-tumor therapies.

Repurposable Drugs for Immunotherapy and Strategies to Find Candidate Drugs

Conventional drug discovery involves significant steps, time, and expenses; therefore, novel methods for drug discovery remain unmet, particularly for patients with intractable diseases. For this purpose, the drug repurposing method has been recently used to search for new therapeutic agents. Repurposed drugs are mostly previously approved drugs, which were carefully tested for their efficacy for other diseases and had their safety for the human body confirmed following careful pre-clinical trials, clinical trials, and post-marketing surveillance. Therefore, using these approved drugs for other diseases that cannot be treated using conventional therapeutic methods could save time and economic costs for testing their clinical applicability. In this review, we have summarized the methods for identifying repurposable drugs focusing on immunotherapy.