The research focus and findings of the 23 journal articles are provided in Table 1. Please refer below:

Table 1 Summary of research findings in the reviewed literature

The studies of rare disease trials have proposed key conceptual frameworks and have also provided empirical insights into the design, conduct, evaluation, and outcome of these trials. A baseline synthesisation of key findings from these studies provides a core observation that the design and conduct of clinical trials can be assumed to be centered around three themes: Disease characteristics, Trial Design and Methodology, and Clinical Outcome Assessment. The core concept of clinical research plans begins with understanding specific rare diseases, their heterogeneity, and natural history, which inform Trial Design and Methodology, including study objectives, endpoints, and ethical considerations. Clinical outcomes and impacts, such as efficacy, safety, patient-reported outcomes, and cost-effectiveness, are influenced by the chosen methodology and may vary across different ethnic groups and even within patients at various stages of the disease or encountering specific molecular subsets of the disease. Relationships between these themes highlight the iterative nature of clinical research and especially in the case of rare diseases these iterations may not be sequential but in most cases need to be concurrent and flexible to ensure maximum and diverse patient coverage. Incorporating the themes in a common regulatory and funding framework across the EU becomes challenging due to huge ethnic, geographical, financial, infrastructural, and cultural diversity. Stakeholder perspectives, comparative analysis, ethical considerations, and future directions add depth to ongoing drug development initiatives. This approach warrants the inclusion of diverse viewpoints, ethical awareness, ongoing refinement of research practices, and continuous innovation in the design and conduct of trials to address the unique challenges and opportunities in rare disease clinical trials within the EU.

Landscape of orphan drug clinical trials in the EU:Clinical trials conducted based on therapeutic areas in the EU

Between 2007 and 2022, 152 clinical trials were conducted on orphan drugs in the EU, as recorded in the EU Clinical Trial Registry. Refer to Fig. 1. 23% of the trials were on cancer-related therapies, followed by blood disorders with an 18% share of the trials and congenital abnormalities with a 14% share of the trials. The rest of the trials were related to other therapeutic areas, such as cardiovascular diseases, immune system diseases, and nervous disorders.

Fig. 1

Orphan drug clinical trials based on therapeutic area (2007–2022) (EU Clinical Trial Registry). Source International Clinical Trials Registry Platform (ICTRP) [9]

Yearly spread of clinical trials of orphan drugs in the EU

Between 2007 and 2022, clinical trials on orphan drugs have seen both an increase and a decrease on a year-on-year basis, with a decrease observed during the intermittent period mainly in 2015 and 2016. Refer to Fig. 2. After that, the trend has been upward again, with 22 trials being conducted in 2021, which is the highest in the period under observation. The number again decreased to 12 in 2022. There is an average increase of 51% in the clinical trial volume from 2007 to 2022.

Fig. 2

Yearly orphan drug clinical trials in EU (2007–2022). Source International Clinical Trials Registry Platform (ICTRP) [9]

Clinical trial volume of orphan drugs based on product types in the EU

Between 2007 and 2022, biological products underwent 78 trials compared to 71 trials for synthetic drugs. Refer to Fig. 3. This might be an indication that investments made by the EU in the field of biotechnology have created a favorable environment for sponsors for biologic development. The EU market provided potential commercial opportunities due to less competition in the field of biologics. Biologics may also be favored due to their targeted mechanism of action, high specificity and efficacy, and ability to modulate complex biological processes underlying the specific disease being treated. These factors make biologics more suitable therapies than synthetic drugs for diseases belonging to certain therapeutic areas.

Fig. 3

Orphan drug trial volume based on product type in EU (2007–2022). Source International Clinical Trials Registry Platform (ICTRP) [9]

Top 10 companies conducting orphan drug clinical trials in the EU

Between 2007 and 2022, Novo Nordisk conducted the maximum number of clinical trials focusing on congenital, hereditary, and neonatal diseases and abnormalities, nutritional and metabolic diseases, digestive system diseases, cardiovascular diseases, and blood and nervous disorders. It was followed by BioCryst Pharmaceuticals Inc., which conducted 19 trials focusing on blood disorders and immune system diseases. The top 10 companies contributed to 64% of all orphan drug clinical trials in the EU between 2007 and 2022. Refer to Fig. 4.

Fig. 4

Top 10 companies in terms of orphan drug trials in EU (2007–2022). Source International Clinical Trials Registry Platform (ICTRP) [9]

Clinical trials on biologics have seen an increase between 2019 and 2022 primarily due to an increased focus on biologics development for rare disease therapies. This is also backed by the growing knowledge of genetic markers of specific diseases that help in the development of targeted therapies for patients. It was observed that 45% of all biologic therapeutic trials between 2007 and 2022, were carried out between 2019 and 2022. Refer to Fig. 5.

Fig. 5

Yearly trend of clinical trials of orphan drugs based on product types in EU (2007–2022). Source International Clinical Trials Registry Platform (ICTRP) [9]

Inferences from landscape data

Companies have been showing an increased interest in orphan drug development in the EU, primarily supported by the EMA’s orphan drug development incentives such as ten years of market exclusivity for orphan-designated products, centralized and accelerated review of marketing authorization applications for orphan products, conditional marketing authorization of certain drug types, compassionate access under exceptional circumstances for patients with high morbidity, application and regulatory fee waivers and EC research frameworks and grants for orphan drug innovation and rare disease natural history studies. Most of the major pharmaceutical companies have developed and conducted trials on a considerable number of orphan drugs across different therapeutic areas. This, supported by collaborative programs by European Reference Networks (ERNs), the European Joint Program on Rare Diseases (EJP-RD) [10, 11], and the International Rare Diseases Research Consortium (IRDiRC) [12] has played a major role in creating a translational research environment for orphan drug development and innovative trial design. Many small and medium enterprises (SMEs) working on rare disease innovation in the biotechnology and pharmaceutical domain are supported by the European Confederation of Pharmaceutical Entrepreneurs (EUCOPE) in terms of financial incentives, development support, and scientific advisory. EUCOPE also acts as a bridge for advancing translational research. Qualified SMEs receive additional incentives from the EMA like a 100% fee reduction for administrative and procedural assistance, pre-authorization inspection, initial marketing authorization application and post-authorization applications, and annual fee, specified in Council Regulation (EC) No 297/9554, in the first year from granting of a marketing authorization. The development of unified patient databases through the European Rare Disease Registry Infrastructure (ERDRI) and Patient-Reported Outcome and Quality of Life Instruments Database (PROQOLID) [13] database by Mapi Research Trust has provided valuable information on Real World Data from patient treatment outcomes, valuable biomarkers, diagnostic reports, and observer as well patient experience feedback [14]. Although there have been definitive steps taken at the EC level, regulatory agency level, and by research consortiums and patient organizations such as the European Organization for Rare Diseases (EURORDIS) [15], the pace of innovation and marketing approval of drugs is not as expected, as is evident from the overall analysis presented in the landscape section Apart from the practical challenges that are discussed in a later section, ineffective utilization of regulatory incentives and the requirement of high capital investment have been factors behind a slower pace of therapeutic development. Along with the key requirements of addressing clinical trial issues, it is equally important to implement an alternative approach to drug development planning to increase the participation of players in orphan drug clinical research and development.

Key aspects of rare disease trial designsPractical challenges in conducting orphan drug clinical trials in the European Union

Clinical trials, being one of the most significant stages in the drug development lifecycle face various hurdles, especially in a multi-country setup like the EU. It includes finding eligible patients and overcoming awareness issues. International trials introduce further complexities like consensus on diagnosis and cultural considerations [4] Disease heterogeneity poses further challenges making progression tracking difficult, and varied manifestations across different patient groups create challenges in diagnosis, treatment, and understanding effectiveness [5]. Genetic factors, variability in disease frequency among patient groups [3], lack of knowledge about disease progression [7], and co-existing illnesses complicate the determination of inclusion/exclusion criteria and the tenure of trials [8, 16]. In many cases, RCTs fail to deliver the desired trial outcomes in normal settings. Limited knowledge about appropriate endpoints complicates protocol design, hindering regulatory approval. Small patient populations and data variability exacerbate challenges in demonstrating drug effectiveness and safety, compounded by the absence of standardized clinical trial templates for most rare [6, 17]. Balancing risks and benefits, respecting autonomy, and ensuring equal access are crucial issues. The limited treatment options make patients more likely to accept risks, raising concerns about informed consent which becomes a critical ethical issue [17]. Evolving regulations with stricter requirements and limited expert resources can delay research [18]. Regulatory processes and differing policies across countries add complexity to the design and conduct of rare disease trials in the EU [19]. Regulators must rely on literature review information and empirical data to a large extent when making decisions. Data extrapolation is followed for diseases with existing data, while for diseases with little prior data, several iterations need to be performed across different patient population samples resulting in cost overruns or high expenditure for the sponsors. A considerable patient population of rare disease patients is children, posing challenges in recruitment, retention, and management due to factors like developmental, emotional, and family dynamics. The varying clinical research approaches for pediatric and adult use intensify complexities in recruitment criteria, consent, and regulatory acceptance of study outcomes, amplifying oversight of ethical aspects in conducting trials [20]. In terms of costs, rare disease clinical trials incur high costs due to challenges such as the geographical spread of patients, complex trial protocols, and expensive manufacturing overheads to meet regulatory standards. Specialized trial designs may be necessary to recruit the required number of patients, further escalating expenses. Additionally, data collection and analysis using sophisticated statistical models, drive up the overall cost of drug development. Hence, this factor becomes one of the key components in drug pricing, treatment availability, and reimbursement as well. Countries like Germany, with a strong economy and financial budget, have the privilege to establish initial prices of innovative therapies making it one of the initial markets for product launch. This results in a price that may be attractive to the sponsor company but may pose a significant financial burden on countries with less financial resources and undeveloped reimbursement schemes. The downside of high pricing needs to be considered as well. Any kind of failure in price negotiations for high-cost therapies with the national Governments results in the withdrawal of the therapeutic product from the entire EU market due to a lack of reference and attractive pricing for the company. An example of this was the withdrawal of Zynteglo, for the treatment of severe Beta thalassemia and of Skysona, for the treatment of Cerebral adrenoleukodystrophy by Bluebird Bio. Pricing remains a critical issue in rare disease drug development and treatment availability [21]. One approach to mitigate the cost issue, is to implement specialized National Action Plans for rare diseases as per recommendations of the European Council. From an economic point of view, it seems difficult to implement uniform research plans, funding mechanisms, and reimbursement schemes across all member states. To address this, the European Committee of Experts on Rare Diseases (EUCERD) came out with EUROPLAN indicators to monitor the progress of plans in individual member states. These indicators can help track the progress of the National Action Plans. Stronger economies can provide financial and administrative expertise and financial grants through the E-Rare (ERA-NET) research program on rare diseases. An increased public-private partnership should be encouraged to enhance the expertise in conducting clinical research through a multi-stakeholder collaborative approach. This will provide an initial booster to the weaker economies to streamline their action plans and frame appropriate funding and reimbursement mechanisms for rare disease drug development and treatment.

Technical aspects of clinical trial design for rare diseases

RCTs have been the globally accepted and most reliable clinical trial design among clinical researchers, investigators, and regulatory agencies for demonstrating the effectiveness of a drug. However, conducting multiple RCTs can be time-consuming, and expensive, and may not fully reflect real-world clinical settings. As a result, there is a growing interest in finding innovative approaches to enhance the efficiency of clinical research [22]. RCTs are designed with standardized and comprehensive outcome measurements to determine the safety of the drug under trial. RCTs generate substantial evidence to determine the effectiveness of the drug by incorporating bias-reduction techniques to reduce errors in observations [22].

Randomization helps to differentiate between treatment outcomes as well as the variability of outcomes within a group. However, despite the multiple benefits and robustness of the design of RCTs, the validity of these cannot be always confirmed in orphan drug scenarios due to the small patient population. This is due to sampling techniques being unable to provide sufficient observation points. The design of orphan drug trials requires multicentre coordination across different locations in the world [8]. This requires the design and analysis of innovative trials through appropriate randomization procedures for a smaller population of patients. As the patient population varies across diseases as well as across demography or geography, there are always differing amounts of bias. Hence, it is imperative that no unique procedure or randomization technique is applicable, and it should be supported by proper design methodology, statistical tests, and analytical methods [3].

Rare disease clinical trial design considerations

Randomized trials are highly dependent on patient registry information to identify specific representative populations. Periodic reference to the updated registries can help sponsors improve study design and determine study cohorts to conduct case-control and observational studies. This helps in bias reduction but there are also certain challenges in terms of rare disease trial design. Existing registries may not have adequate information and validation of the correctness becomes a challenge due to highly fragmented content, lack of expertise, and data sharing or privacy controls. From a disease perspective, the progression of rare diseases is highly heterogeneous and varies between demographics and geographical dispersions. Genetic markers within the same geographical area can vary between communities with few communities highly susceptible to the disease due to cultural or lifestyle practices. In this scenario, it is difficult to determine the proper natural history and clinical endpoint based on diagnostic and treatment outcomes [3].

Analytical and statistical considerations for clinical trial designs

While statistical sampling and analytical methodologies are proven to be highly effective in identifying patient subsets and trial effectiveness outcomes for RCTs for nonorphan drug trials, the same methodologies may not prove effective in the case of rare disease trial designs. It is important to identify efficient design and analysis techniques. While it is recommended to adopt well-defined, widely used, and regulatory-approved techniques, evaluations need to be performed and continuous monitoring is required to establish method validity and adaptability to various trial designs for rare diseases [3]. In studies of rare diseases, small sample sizes can severely restrict design options, hinder the usage of standard statistical models as mandated by regulators, and make replication of study models difficult. To assess the efficacy and safety of potential treatments, it is imperative to explore novel and innovative statistical designs [23]. It is also important to identify an appropriate observation population and study cohort to ensure that bias is properly addressed by using computer simulation models and advanced statistical techniques. While computer simulation methodologies can address the population issue to a considerable extent by identifying patient cohorts for randomized studies; it is also important to systematically study the interactions between treatment and disease phenotypes to prepare targeted trials to understand drug-patient interactions under personalized settings and individual requirements. Statistical algorithmic models can prove helpful in this regard. Digital endpoints generated from sensors installed in wearables can provide valuable real-time data that can be fed to computer simulation models to identify appropriate biomarkers and generate clinically relevant endpoints or surrogate endpoints [24]. However, there is a challenge, as identifying relevant and meaningful data from multiple observations in the form of digital data is time-consuming and requires multiple iterations.

Recommendations for improving the clinical trial design of rare diseasesEffective usage of natural history and disease registry data for trial design

The strategic utilization of natural history and disease registry data plays a pivotal role in the design of clinical trials for rare diseases. This data serves as a roadmap, providing valuable insights into the complex and unique progression trajectories of these diseases, which is an essential component in assessing the impact of new therapeutic interventions [25]. It is important to harness the crucial information around these studies to derive quantifiable biomarkers to effectively chart the therapeutic roadmap, design the trial along with devising a robust drug development plan to augment the possibilities of regulatory approval supported by appropriate safety and efficacy data. Studies have been conducted on Duchenne Muscular Dystrophy based on natural history data for identification of relevant biomarkers based on progression and severity and these data provided valuable data for regulatory assessment [26, 27]. It is to be noted that the landscape of natural history studies on rare diseases faces multiple challenges, including a limited pool of participants, issues with data quality, and the existence of data silos [28]. However, innovative solutions to design simulation models utilizing machine learning, are emerging to address these obstacles, fostering an environment of collaboration among stakeholders and promoting shared learning to enhance knowledge and expedite orphan drug discovery. Properly designed and maintained non-proprietary patient and disease registries based on real-world data, clinician and patient-reported outcomes and natural history study databases are cornerstones in this endeavor, offering a wealth of information about rare diseases [23]. These resources enable the design of robust clinical trials equipped with outcome measures that are both relevant and clinically meaningful. By harnessing this data, researchers can significantly enhance the design of clinical trials for rare diseases. This will lead to the development of more effective therapies in the EU, enable informed regulatory approvals, and pave the way for improved patient outcomes, marking a significant stride in developing and implementing a robust patient-centered approach toward orphan drug development.

Adoption of innovative clinical trial design

In clinical trial designs for orphan drugs, the process of obtaining approvals should take into account the outcome variations and underlying variability in disease manifestations. Due to the lack of a sufficient population, Phase 3 studies for orphan drug approvals tend to include a smaller number of patients, do not have placebo controls in many cases, and employ nonrandomized and unblinded trial designs, such as a single-arm design and surrogate endpoints, for assessing efficacy [3]. This requires proper planning, collaboration, and timeliness. As in most cases, rare disease trials involve multiple sites, and consensus is required between researchers and regulatory agencies in terms of the definition and classification of the disease under trial, identification of appropriate biomarkers and endpoints, and assessment of outcomes on commonly accepted standards. Under these circumstances, innovative trial designs such as basket trials and umbrella trials can help to address these issues. Basket trials enable researchers to investigate certain disease types with specific genetic biomarkers under a common trial design and protocol. Using this approach, researchers test the efficacy of targeted therapies by grouping patients based on molecular characteristics of the disease and provide valuable insights into the potential benefits of a treatment in rare diseases. These trials use a common targeted intervention. On the other hand, umbrella trials involve enrolling patients with the same disease but with different molecular or genetic subtypes. This design allows researchers to test multiple targeted therapies simultaneously within the same disease population, including rare diseases. Umbrella trials help identify which subgroups of patients may benefit from specific treatments, leading to more personalized and effective interventions. These trials use multiple targeted interventions. Both of these trials can also be designed using control groups through randomization, thus ensuring bias reduction and effective assessment of clinical outcomes. These trials have certain advantages, such as sharing the same control group to improve efficiency, reducing the likelihood of patients receiving a placebo, allowing comparisons between active substances and pooling of data from active treatments, and sharing of resources, thus leading to reduced trial costs and more efficient use of trial logistics [16]. In a rare disease setting, these trials may face some challenges around sponsor coordination in terms of multiple treatment trials, complex study design, competing and conflicting interests among stakeholders, operational challenges when international centers and multiple sites are involved, and implementing and following a common protocol. In this scenario, the ERICA, ERNs, patient advocacy groups, and centers of excellence can play an active role in identifying suitable patient populations and can act as co-ordinators or collaborators for designing, funding, and assisting in conducting trials through disease expertise, data sharing, execution management and assessing the outcomes of trials in multicenter settings [16].

Adaptive trial design for rare disease trials

Adaptive trial designs can offer flexibility and increase the efficacy of rare disease trials. Adaptive design trials encompass modified randomization procedures, the addition or discontinuation of treatment arms or doses, sample size adjustments based on interim results, adaptive patient population enrichment, and the incorporation of prespecified rules for efficacy. These designs in exploratory settings allow for the evaluation of various doses, regimens, and populations, focusing on the most favorable observations that will ensure promising results. They increase flexibility and acceptability and maximize the trial’s potential based on gathered data. Prespecified modifications maintain validity and integrity while adjusting elements of the study design [29]. The statistical approach of these trial designs enables modifications of study elements for minimizing errors, careful planning, and ensuring trial ethics and integrity [8]. While designing these trials, it is important to address and mitigate challenges around operational logistics, feasibility, and access to technical expertise. These are crucial considerations in designing clinical trials and special attention should be given to rare disease trials. Adequate study design expertise is necessary to ensure appropriate planning, for which experienced clinical researchers, statisticians, and healthcare professionals who are well-versed in rare diseases and orphan drug trial design, execution, and outcome assessment should be identified. Additionally, maintaining data and trial integrity becomes essential for post-interim analyses. This requires data storage and analytics planning. Addressing concerns related to bias in estimated treatment effects further strengthens the integrity of the trial, and outcomes and observations become more acceptable to regulators [8].

Clinical trials through inferentially seamless adaptive designs

In the adaptive seamless design, trials are merged, and analyses are seamlessly integrated by including data from patients enrolled both before and after the adaptation in the final analysis [30]. Adaptive seamless designs, particularly in the context of rare diseases, offer an appealing approach when traditional group sequential designs for assessing efficacy or futility may not be feasible due to limited sample sizes [31]. These designs integrate a Phase 2 study, which focuses on treatment selection, with a Phase 3 study for confirmatory testing. This integration allows for treatment selection and the re-evaluation of sample size at a predefined interim analysis [3]. The use of adaptive seamless designs in rare disease clinical trials offers several benefits. It maximizes patient data utilization, leading to stronger conclusions, while reducing the number of patients and saving time and costs in Phase 3. It improves target dose and participant selection, explores covariates between Phase 2 endpoints and Phase 3 outcomes, and provides valuable information on treatment effects and safety by following patients from terminated treatment groups. Additionally, it allows for treatment modifications, enhancing the chances of patients receiving safe and effective treatments [32]. Challenges arise when working with these designs, including the time required for their design and the need for appropriate analyses to account for potential bias in treatment effect estimates due to data combinations at different study phases [16].

Decentralized clinical trial design for rare diseases

Decentralized methods involve conducting assessments in alternative locations such as participants’ homes, local clinics, or digital platforms on mobile devices or computers and not at centralized medical facilities. Decentralized clinical trial (DCT) approaches that incorporate physical and virtual consultations, along with online access to medicines or providing drugs through local clinicians or pharmacists, can bring substantial benefits by reducing the burden on patients and their families [33]. DCTs do not completely remove the physical interactions between clinicians and patients. It leverages digital health technologies (DHTs) such as medical devices and wearables. for electronic collection and usage of reliable diagnostic and clinical data, clinical outcome assessments (COAs), Patient and Observer Reported Outcomes, and clinical health records. These enable clinicians to determine exploratory patient-relevant endpoints, enable targeted patient recruitment, and help in collecting and updating data registries for secondary usage in future trials as reference points. This integrated approach will help clinical trial design be more focused on the outcomes. DCTs have their setup challenges in terms of technology adoption and usage, data privacy and technology literacy concerns, and site readiness with appropriate infrastructure, trained personnel, and logistical support. Keeping in mind the needs of patients, industry and clinical stakeholders need to upgrade technical aspects and knowledge of data collection and analysis [34]. Addressing data privacy concerns while sharing data across multiple trial sites as per domestic and international regulations will ensure confidentiality and appropriate usage of data. If the challenges are properly addressed, DCTs can play a crucial role in terms of increased adoption in conducting rare disease clinical trials and acceptance across regulators during decision-making.

Usage of external controls in designing effective rare disease trials

As rare disease clinical trials are subjected to small patient populations, nonrandomization has been adopted in multiple scenarios. Nonrandomized clinical trials that compare against external controls have proven effective in an expanding range of cases, especially in the context of rare diseases. These designs are particularly valuable when randomization is impractical or ethically challenging, or when the available pool of patients with a specific condition is limited [22]. Clinical trial researchers need to understand disease progression and interpret measurements accordingly, but precise methods often don’t translate well to real-world practice. Control groups in these studies are generally being replaced with historical controls based on natural history data. Natural history st