Orphan drug development: the increasing role of clinical pharmacology

Paediatric clinical study of 3D printed personalised medicines for rare metabolic disorders

Rare diseases are infrequent, but together they affect up to 6-10 % of the world's population, mainly children. Patients require precise doses and strict adherence to avoid metabolic or cardiac failure in some cases, which cannot be addressed in a reliable way using pharmaceutical compounding. 3D printing (3DP) is a disruptive technology that allows the real-time personalization of the dose and the modulation of the dosage form to adapt the medicine to the therapeutic needs of each patient. 3D printed chewable medicines containing amino acids (citrulline, isoleucine, valine, and isoleucine and valine combinations) were prepared in a hospital setting, and the efficacy and acceptability were evaluated in comparison to conventional compounded medicines in six children. The inclusion of new flavours (lemon, vanilla and peach) to obtain more information on patient preferences and the implementation of a mobile app to obtain patient feedback in real-time was also used. The 3D printed medicines controlled amino acid levels within target levels as well as the conventional medicines. The deviation of citrulline levels was narrower and closer within the target concentration with the chewable formulations. According to participants' responses, the chewable formulations were well accepted and can improve adherence and quality of life. For the first time, 3DP enabled two actives to be combined in the same formulation, reducing the number of administrations. This study demonstrated the benefits of preparing 3D printed personalized treatments for children diagnosed with rare metabolic disorders using a novel technology in real clinical practice.

Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases

Pediatric populations represent a major fraction of rare diseases and compound the intrinsic challenges of pediatric drug development and drug development for rare diseases. The intertwined complexities of pediatric and rare disease populations impose unique challenges to clinical pharmacologists and require integration of novel clinical pharmacology and quantitative tools to overcome multiple hurdles during the discovery and development of new therapies. Drug development strategies for pediatric rare diseases continue to evolve to meet the inherent challenges and produce new medicines. Advances in quantitative clinical pharmacology research have been a key component in advancing pediatric rare disease research to accelerate drug development and inform regulatory decisions. This article will discuss the evolution of the regulatory landscape in pediatric rare diseases, the challenges encountered during the design of rare disease drug development programs and will highlight the use of innovative tools and potential solutions for future development programs.

Exploring the Potential Challenges for Developing Generic Orphan Drugs for Rare Diseases: A Survey of US and European Markets

OBJECTIVES

The US Food and Drug Administration in 1983 and the European Union's European Medicines Agency in 2000 implemented the orphan drug development program for rare diseases. The study aimed to find the potential challenges encountered by generic companies in developing generics for rare diseases.

METHODS

We performed a thematic analysis, which consists of qualitative and quantitative research. For data analysis of approved orphan drugs, we used statistical methods, and for the industrial case study, we selected 14 generic companies and conducted semistructured interviews related to 10 critical areas of drug development.

RESULTS

The orphan drug approvals were classified into 4 categories: the number of orphan approvals, pediatric claims, formulation, and therapeutic areas. We analyzed the approvals from 2001 to 2021; the Food and Drug Administration approved 815 drugs and European Medicines Agency approved 258 drugs. The pediatric orphan approvals were analyzed from 2010 to 2021; the average percentage of orphan drugs claim pediatric exclusivity during this period was found to be 31.8%. In formulation, we found the highest percentage of drugs belong to small molecules at 71%. In the therapeutic class, oncology drugs have a majority of approvals at 25%. The industrial case study responses revealed that the major challenge for drug development is the complexity of the disease at 21%, followed by the limited market at 17%.

CONCLUSIONS

There is a high need for generic orphan drugs in the developing countries. The generic companies can use the opportunities provided by health authorities for the benefit of both the company and the patient perspective.

Opportunities and Challenges for Machine Learning in Rare Diseases

Rare diseases (RDs) are complicated health conditions that are difficult to be managed at several levels. The scarcity of available data chiefly determines an intricate scenario even for experts and specialized clinicians, which in turn leads to the so called “diagnostic odyssey” for the patient. This situation calls for innovative solutions to support the decision process via quantitative and automated tools. Machine learning brings to the stage a wealth of powerful inference methods; however, matching the health conditions with advanced statistical techniques raises methodological, technological, and even ethical issues. In this contribution, we critically point to the specificities of the dialog of rare diseases with machine learning techniques concentrating on the key steps and challenges that may hamper or create actionable knowledge and value for the patient together with some on-field methodological suggestions and considerations.

A Glance at the Use of Glucocorticoids in Rare Inflammatory and Autoimmune Diseases: Still an Indispensable Pharmacological Tool?

Since their discovery, glucocorticoids (GCs) have been used to treat almost all autoimmune and chronic inflammatory diseases, as well as allergies and some forms of malignancies, because of their immunosuppressive and anti-inflammatory effects. Although GCs provide only symptomatic relief and do not eliminate the cause of the pathology, in the majority of treatments, GCs frequently cannot be replaced by other classes of drugs. Consequently, long-term treatments cause adverse effects that may, in turn, lead to new pathologies that sometimes require the withdrawal of GC therapy. Therefore, thus far, researchers have focused their efforts on molecules that have the same efficacy as that of GCs but cause fewer adverse effects. To this end, some GC-induced proteins, such as glucocorticoid-induced leucine zipper (GILZ), have been used as drugs in mouse models of inflammatory pathologies. In this review, we focus on some important but rare autoimmune and chronic inflammatory diseases for which the biomedical research investment in new therapies is less likely. Additionally, we critically evaluate the possibility of treating such diseases with other drugs, either GC-related or unrelated.

One drug to treat many diseases: unlocking the economic trap of rare diseases

There are two major problems with the development of therapies for rare diseases. First, among over 7000 such diseases, the vast majority are caused by genetic defects and/or include neurodegeneration, making them very difficult to treat. Second, drugs for rare diseases, so-called orphan drugs, are extremely expensive, as only a small number of patients are interested in purchasing them. This results in the appearance of a specific economic trap of rare diseases; namely, despite high biomedical, pharmaceutical and technological potential, the development of new orphan drugs is blocked by the economic reality. The purpose of this work was to find a potential solution that might resolve this economic trap of rare diseases. A literature review was conducted, and a hypothesis was formulated assuming that the use of one drug for the treatment of many rare diseases might overcome the economic trap. We provide examples showing that finding such drugs is possible. Thus, a possible solution for the problem of developing orphan drugs is presented. Further preclinical and clinical studies, although neither easy nor inexpensive, should verify whether the hypothesis regarding the possibility of unlocking the economic trap of rare diseases is valid.

The challenges of pharmacoepidemiology of orphan drugs in rare diseases

Large electronic health records database available at a national level offer great opportunity for research in rare diseases and orphan drugs. Methods and data used in pharmacoepidemiology present a great potential for epidemiology, drug utilization studies, drug safety, drug effectiveness and pharmacoeconomics. This review presents the different sources of data in Europe, with a special focus on the French situation, with the recent implementation of SNDS (système national des données de santé [French national health data wharehouse]). Some examples are given. Development of rigorous and innovative methods must be encouraged in the future.

A methodological framework for drug development in rare diseases. The CRESim program: Epilogue and perspectives

Based on the 'European Child-Rare-Euro-Simulation' (CRESim) project, this article proposes a generalizable strategy utilizing datasets analysis in combination with modeling and simulation, in order to optimize the clinical drug development applied in the field of rare diseases. The global process includes: (i) the simulation of a realistic virtual population of patients (modeled from a real dataset of patients), (ii) the modeling of disease pathophysiological components and of pharmacokinetic-pharmacodynamic relations of the drug(s) of interest, (iii) the modeling of several randomized controlled clinical trials (RCTs) designs and (iv) the analysis of the results (multi-dimensional approach for RCTs durations and precision of the estimation of the treatment effect). However, whereas modeling and numerical simulation may provide supplementary tools for drug development, they cannot be considered as a substitute for RCTs performed in 'real' patients.

Videira P, Valadão G. Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?

The amount of data collected and managed in (bio)medicine is ever-increasing. Thus, there is a need to rapidly and efficiently collect, analyze, and characterize all this information. Artificial intelligence (AI), with an emphasis on deep learning, holds great promise in this area and is already being successfully applied to basic research, diagnosis, drug discovery, and clinical trials. Rare diseases (RDs), which are severely underrepresented in basic and clinical research, can particularly benefit from AI technologies. Of the more than 7000 RDs described worldwide, only 5% have a treatment. The ability of AI technologies to integrate and analyze data from different sources (e.g., multi-omics, patient registries, and so on) can be used to overcome RDs’ challenges (e.g., low diagnostic rates, reduced number of patients, geographical dispersion, and so on). Ultimately, RDs’ AI-mediated knowledge could significantly boost therapy development. Presently, there are AI approaches being used in RDs and this review aims to collect and summarize these advances. A section dedicated to congenital disorders of glycosylation (CDG), a particular group of orphan RDs that can serve as a potential study model for other common diseases and RDs, has also been included.