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Pediatric clinical research, especially in rare diseases, faces persistent challenges including the identification and recruitment of eligible patients, assessing protocol feasibility, and ensuring efficient trial execution. These issues are compounded by small, age-stratified populations and fragmented clinical data. Real-world data (RWD), especially when drawn from electronic health records (EHRs), present an opportunity to support innovative trial designs, such as real-world comparator arms and postmarketing surveillance. However, realizing this potential depends on the routine availability of structured, reusable clinical data. This proof-of-concept study aimed to assess the availability and structure of routine clinical data in European pediatric hospitals, focusing on data elements relevant for use in comparator arms and postmarketing surveillance studies. The study focused on 2 disease areas-neurofibromatosis (NF) and atopic dermatitis (AD)-as examples of rare and common conditions in children, respectively. An inventory of 113 high-value clinical data items was developed based on expert analysis of clinical protocols for NF, AD, and safety studies. These items were included in a structured web-based survey disseminated through the connect4children (c4c) National Hub network, reaching sites across. Europe. Respondents were asked to indicate how each data item is collected and stored: in structured/coded EHR fields, as free text, in external systems, or on paper. Survey responses from 24 hospitals across 11 European countries revealed considerable variability in how data are captured and stored. While many general clinical and drug safety data elements-such as demographics, vital signs, and medication use-were often collected in structured formats, disease-specific and contextual variables were frequently captured as free text or not documented in a standardized way. For example, structured data capture was more prevalent for basic demographic and safety-related variables, whereas only a minority of sites recorded key disease-specific clinical details in a structured form. Lifestyle and family history data were among the least consistently documented. These gaps in structured data entry reduce the immediate reusability of EHR data for secondary research purposes. This study highlights gaps in the structured documentation of pediatric clinical data across European sites. While the routine collection of many variables is promising, the lack of structured and coded formats poses a barrier to reusing these data for observational studies or comparator arms. As a first step toward the broader integration of RWD into pediatric research, this study demonstrates the feasibility of assessing EHR data availability and sets the stage for future scaling across more diseases and sites.

Data dictionaries for clinical trials are often created manually, with data structures and controlled vocabularies specific for a trial or family of trials within a sponsor’s portfolio. Microsoft Excel is commonly used to capture the representation of data dictionary items but has limited functionality for this purpose. The conect4children (c4c) network is piloting the Direcht clinical data modelling tool to model their Cross Cutting Paediatric Data Dictionary (CCPDD) in a more formalised way. The first pilot had the key objective of testing whether a clinical data modelling tool could be used to represent data items from the CCPDD. The key objective of the second pilot is to establish whether a small team with little or no experience of clinical data modelling can use Direcht to expand the CCPDD. Clinical modelling is the process of structuring clinical data so it can be understood by computer systems and humans. The model contains all of the elements that are needed to define the data item. Results from the pilots show that Direcht creates a structured environment to build data items into models that fit into the larger CCPDD. Models can be represented as an HTML document, mind map, or exported in various formats for import into a computer system. Challenges identified over the course of both pilots are being addressed with c4c partners and external stakeholders.

The reuse of paediatric individual patient data (IPD) from clinical trials (CTs) is essential to overcome specific ethical, regulatory, methodological, and economic issues that hinder the progress of paediatric research. Sharing data through repositories enables the aggregation and dissemination of clinical information, fosters collaboration between researchers, and promotes transparency. This work aims to identify and describe existing data-sharing repositories (DSRs) developed to store, share, and reuse paediatric IPD from CTs. A rapid review of platforms providing access to electronic DSRs was conducted. A two-stage process was used to characterize DSRs: a first step of identification, followed by a second step of analysis using a set of eight purpose-built indicators. From an initial set of forty-five publicly available DSRs, twenty-one DSRs were identified as meeting the eligibility criteria. Only two DSRs were found to be totally focused on the paediatric population. Despite an increased awareness of the importance of data sharing, the results of this study show that paediatrics remains an area in which targeted efforts are still needed. Promoting initiatives to raise awareness of these DSRs and creating ad hoc measures and common standards for the sharing of paediatric CT data could help to bridge this gap in paediatric research.

The conect4children (c4c) project aims to facilitate efficient planning and delivery of paediatric clinical trials. One objective of c4c is data standardization and reuse. Interoperability and reusability of paediatric clinical trial data is challenging due to a lack of standardization. The Clinical Data Interchange Standards Consortium (CDISC) standards that are required or recommended for regulatory submissions in several countries lack paediatric specificity with limited awareness within academic institutions. To address this, c4c and CDISC collaborated to develop the Pediatrics User Guide (PUG) consisting of cross-cutting data items that are routinely collected in paediatric clinical trials, factoring in all paediatric age ranges. The development of the PUG consisted of six stages. During the scoping phase, subtopics (each containing several clinically relevant concepts) were suggested and debated for inclusion in the PUG. Ninety concepts were selected for the modelling phase. Concept maps describing the Research Topic and representation procedure were developed for the 19 concepts that had no (or partial) previous modelling in CDISC. Next, metadata and implementation examples were developed for concepts. This was followed by a CDISC internal review and a public review. For both these review stages, the feedback comments were either implemented or rejected based on budget, timelines, expert review, and scope. The PUG was published on the CDISC website on February 23, 2023. The PUG is a first step in bridging the lack of child specific CDISC standards, particularly within academia. Several academic and industrial partners were involved in the development of the PUG, and c4c has undertaken multiple steps to publicize the PUG within its academic partner organizations - in particular, the European Reference Networks (ERNs) that are developing registries and dictionaries in 24 disease areas. In the long term, continued use of the PUG in paediatric clinical trials will enable the pooling of data from multiple trials, which is particularly important for medical domains with small populations.

Other benefits of data standards include the ability of information technology to intake and manipulate information directly from the source data (machine readability) and the capability to make information Findable, Accessible, Interoperable and Reusable (FAIR).1 As the paediatric population (babies, children and adolescents) is an important user of health services, health data standards need to cover data generated during paediatric healthcare, while supporting data use throughout the life of the patient. A concept is a precisely defined attribute that can take on values from an allowable set. c4c collaborated with the Clinical Data Interchange Standards Consortium (CDISC) to identify and prioritise 90 data element concepts unique to maternal and paediatric clinical research for representation in the CDISC Paediatrics User Guide (PUG).3 A snapshot of essential data element concepts included in the PUG is listed in table 1, including some concepts that relate to events during pregnancy that are necessary to interpret events after birth. c4c also collaborated with IMI FAIRPlus (https://fairplus-project.eu/) to develop a metadata schema for paediatric clinical trial protocols.4 This schema will make the metadata collected about paediatric clinical trials more FAIR. Table 1 Paediatric-specific data concepts, including relevant information relating to events during pregnancy Topic Concept Comment Demographic data Age unit (hours and days) More granularity about age is needed 8 hours after birth than 80 years after birth. By focusing investments by healthcare systems and electronic health record systems on this data, there is an additional risk that paediatric clinical research will find that routinely collected (real-world) data is in the future not appropriately adapted to its needs. Since 70% of rare diseases are of paediatric onset, there is, therefore, also a risk of the EHDS missing a vital opportunity to accelerate rare disease research.

Rare disease communities are spread around the globe and segmented by their condition. Little research has been performed on the majority of rare diseases. Most patients who are affected by a rare disease have no research on their condition because of a lack of knowledge due to absence of common groups in the research community. We aimed to develop a safe and secure community of rare disease patients, without geographic or language barriers, to promote research. Cocreation design methodology was applied to build Share4Rare, with consultation and input through workshops from a variety of stakeholders (patients, caregivers, clinicians, and researchers). The workshops allowed us to develop a layered version of the platform based on educating patients and caregivers with publicly accessible information, a secure community for the patients and caregivers, and a research section with the purpose of collecting patient information for analysis, which was the core and final value of the platform. Rare disease research requires global collaboration in which patients and caregivers have key roles. Collective intelligence methods implemented in digital platforms reduce geographic and language boundaries and involve patients in a unique and universal project. Their contributions are essential to increase the amount of scientific knowledge that experts have on rare diseases. Share4Rare has been designed as a global platform to facilitate the donation of clinical information to foster research that matters to patients with rare conditions. The codesign methods with patients have been essential to create a patient-centric design.

The conect4children (c4c) initiative was established to facilitate the development of new drugs and other therapies for paediatric patients. It is widely recognised that there are not enough medicines tested for all relevant ages of the paediatric population. To overcome this, it is imperative that clinical data from different sources are interoperable and can be pooled for larger post hoc studies. c4c has collaborated with the Clinical Data Interchange Standards Consortium (CDISC) to develop cross-cutting data resources that build on existing CDISC standards in an effort to standardise paediatric data. The natural next step was an extension to disease-specific data items. c4c brought together several existing initiatives and resources relevant to disease-specific data and analysed their use for standardising disease-specific data in clinical trials. Several case studies that combined disease-specific data from multiple trials have demonstrated the need for disease-specific data standardisation. We identified three relevant initiatives. These include European Reference Networks, European Joint Programme on Rare Diseases, and Pistoia Alliance. Other resources reviewed were National Cancer Institute Enterprise Vocabulary Services, CDISC standards, pharmaceutical company-specific data dictionaries, Human Phenotype Ontology, Phenopackets, Unified Registry for Inherited Metabolic Disorders, Orphacodes, Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP), and Observational Medical Outcomes Partnership. The collaborative partners associated with these resources were also reviewed briefly. A plan of action focussed on collaboration was generated for standardising disease-specific paediatric clinical trial data. A paediatric data standards multistakeholder and multi-project user group was established to guide the remaining actions—FAIRification of metadata, a Phenopackets pilot with RDCA-DAP, applying Orphacodes to case report forms of clinical trials, introducing CDISC standards into European Reference Networks, testing of the CDISC Pediatric User Guide using data from the mentioned resources and organisation of further workshops and educational materials.

Standardization of data items collected in paediatric clinical trials is an important but challenging issue. The Clinical Data Interchange Standards Consortium (CDISC) data standards are well understood by the pharmaceutical industry but lack the implementation of some paediatric specific concepts. When a paediatric concept is absent within CDISC standards, companies and research institutions take multiple approaches in the collection of paediatric data, leading to different implementations of standards and potentially limited utility for reuse. To overcome these challenges, the conect4children consortium has developed a cross-cutting paediatric data dictionary (CCPDD). The dictionary was built over three phases - scoping (including a survey sent out to ten industrial and 34 academic partners to gauge interest), creation of a longlist and consensus building for the final set of terms. The dictionary was finalized during a workshop with attendees from academia, hospitals, industry and CDISC. The attendees held detailed discussions on each data item and participated in the final vote on the inclusion of the item in the CCPDD. Nine industrial and 34 academic partners responded to the survey, which showed overall interest in the development of the CCPDD. Following the final vote on 27 data items, three were rejected, six were deferred to the next version and a final opinion was sought from CDISC. The first version of the CCPDD with 25 data items was released in August 2019. The continued use of the dictionary has the potential to ensure the collection of standardized data that is interoperable and can later be pooled and reused for other applications. The dictionary is already being used for case report form creation in three clinical trials. The CCPDD will also serve as one of the inputs to the Paediatric User Guide, which is being developed by CDISC.