Orphan diseases: state of the drug discovery art

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.

Literature Review on Health Emigration in Rare Diseases-A Machine Learning Perspective

The article deals with one of the effects of health inequalities and gaps in access to treatments for rare diseases, namely health-driven emigration. The purpose of the paper is to systematize knowledge about the phenomenon of health emigration observed among families affected by rare diseases, for which reimbursed treatment is available, but only in selected countries. The topic proved to be niche; the issue of "health emigration in rare diseases" is an area for exploration. Therefore, the further analysis used text mining and machine learning methods based on a database selected based on keywords related to this issue. The results made it possible to systematize the guesses made by researchers in management and economic fields, to identify the most common keywords and thematic clusters around the perspective of the patient, drug manufacturer and treatment reimbursement decision-maker, and the perspective integrating all the others. Since the topic of health emigration was not directly addressed in the selected sources, the authors attempted to define the related concepts and discussed the importance of this phenomenon in managing the support system in rare diseases. Thus, they indicated directions for further research in this area.

Exploring different approaches to improve the success of drug discovery and development projects: a review

Background

There has been a significant increase in the cost and timeline of delivering new drugs for clinical use over the last three decades. Despite the increased investments in research infrastructure by pharmaceutical companies and technological advances in the scientific tools available, efforts to increase the number of molecules coming through the drug development pipeline have largely been unfruitful.

Main body

A non-systematic review of the current literature was undertaken to enumerate the various strategies employed to improve the success rates in the pharmaceutical research and development. The review covers the exploitation of genomics and proteomics, complementarity of target-based and phenotypic efficacy screening platforms, drug repurposing and repositioning, collaborative research, focusing on underserved therapeutic fields, outsourcing strategy, and pharmaceutical modeling and artificial intelligence. Examples of successful drug discoveries achieved through application of these strategies are highlighted and discussed herein.

Conclusions

Genomics and proteomics have uncovered a wide array of potential drug targets and are facilitative of enhanced scrupulous target identification and validation thus reducing efficacy-related drug attrition. When used complementarily, phenotypic and target-based screening platforms would likely allow serendipitous drug discovery while increasing rationality in drug design. Drug repurposing and repositioning reduces financial risks in drug development accompanied by cost and time savings, while prolonging patent exclusivity hence increased returns on investment to the innovator company. Equally important, collaborative research is facilitative of cross-fertilization and refinement of ideas, while sharing resources and expertise, hence reducing overhead costs in the early stages of drug discovery. Underserved therapeutic fields are niche drug discovery areas that may be used to experiment and launch novel drug targets, while exploiting incentivized benefits afforded by drug regulatory authorities. Outsourcing allows the pharma industries to focus on their core competencies while deriving greater efficiency of specialist contract research organizations. The existing and emerging pharmaceutical modeling and artificial intelligence softwares and tools allow for in silico computation enabling more efficient computer-aided drug design. Careful selection and application of these strategies, singly or in combination, may potentially harness pharmaceutical research and innovation.

Rare disease data stewardship in Canada

The Canadian Genomics Partnership for Rare Diseases, spearheaded by Genome Canada, will integrate genome-wide sequencing to rare disease clinical care in Canada. Centralized and tiered models of data stewardship are proposed to ensure that the data generated can be shared for secondary clinical, research, and quality assurance purposes in compliance with ethics and law. The principal ethico-legal obligations of clinicians, researchers, and institutions are synthesized. Governance infrastructures such as registered access platforms, data access compliance offices, and Beacon systems are proposed as potential organizational and technical foundations of responsible rare disease data sharing. The appropriate delegation of responsibilities, the transparent communication of rights and duties, and the integration of data privacy safeguards into infrastructure design are proposed as the cornerstones of rare disease data stewardship.

Orphan drugs: major development challenges at the clinical stage

Biotechnology has provided powerful tools to assist in research and development (R&D) for rare diseases. However, orphan drug development presents several major challenges and obstacles, such as low disease prevalence, disease severity, small and heterogeneous patient populations, difficulties in patient recruitment, and limited knowledge of the natural history of disease, among others. Several strategies can be used to plan for and overcome these clinical and regulatory challenges, namely improved clinical trial design, improved patient recruitment, and closer collaboration with the regulatory authorities and with patient associations. As growth in the orphan drug market is expected over the next few years, improving its relevance in the global pharmaceutical market, further challenges might present themselves in the development of orphan drugs.

In silico clinical trials for pediatric orphan diseases

To date poor treatment options are available for patients with congenital pseudarthrosis of the tibia (CPT), a pediatric orphan disease. In this study we have performed an in silico clinical trial on 200 virtual subjects, generated from a previously established model of murine bone regeneration, to tackle the challenges associated with the small, pediatric patient population. Each virtual subject was simulated to receive no treatment and bone morphogenetic protein (BMP) treatment. We have shown that the degree of severity of CPT is significantly reduced with BMP treatment, although the effect is highly subject-specific. Using machine learning techniques we were also able to stratify the virtual subject population in adverse responders, non-responders, responders and asymptomatic. In summary, this study shows the potential of in silico medicine technologies as well as their implications for other orphan diseases.

M344 promotes nonamyloidogenic amyloid precursor protein processing while normalizing Alzheimer's disease genes and improving memory

Hundreds of failed clinical trials with Alzheimer’s disease (AD) patients over the last fifteen years demonstrate that the one-target–one-disease approach is not effective in AD. In silico, structure-based, multitarget drug design approaches to treat multifactorial diseases have not been successful in the context of AD either. Here, we show that M344, an inhibitor of class I and IIB histone deacetylases, affects multiple AD-related genes, including those related to both early- and late-onset AD. We also show that M344 improves memory in the 3xTg AD mouse model. This work endorses a shift to a multitargeted approach to the treatment of AD, supporting the therapeutic potential of a single small molecule with an epigenetic mechanism of action.

Alzheimer’s disease (AD) comprises multifactorial ailments for which current therapeutic strategies remain insufficient to broadly address the underlying pathophysiology. Epigenetic gene regulation relies upon multifactorial processes that regulate multiple gene and protein pathways, including those involved in AD. We therefore took an epigenetic approach where a single drug would simultaneously affect the expression of a number of defined AD-related targets. We show that the small-molecule histone deacetylase inhibitor M344 reduces beta-amyloid (Aβ), reduces tau Ser³⁹⁶ phosphorylation, and decreases both β-secretase (BACE) and APOEε4 gene expression. M344 increases the expression of AD-relevant genes: BDNF, α-secretase (ADAM10), MINT2, FE65, REST, SIRT1, BIN1, and ABCA7, among others. M344 increases sAPPα and CTFα APP metabolite production, both cleavage products of ADAM10, concordant with increased ADAM10 gene expression. M344 also increases levels of immature APP, supporting an effect on APP trafficking, concurrent with the observed increase in MINT2 and FE65, both shown to increase immature APP in the early secretory pathway. Chronic i.p. treatment of the triple transgenic (APP_sw/PS1_M146V/Tau_P301L) mice with M344, at doses as low as 3 mg/kg, significantly prevented cognitive decline evaluated by Y-maze spontaneous alternation, novel object recognition, and Barnes maze spatial memory tests. M344 displays short brain exposure, indicating that brief pulses of daily drug treatment may be sufficient for long-term efficacy. Together, these data show that M344 normalizes several disparate pathogenic pathways related to AD. M344 therefore serves as an example of how a multitargeting compound could be used to address the polygenic nature of multifactorial diseases.