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1.
Int J Health Plann Manage ; 38(2): 416-429, 2023 Mar.
Article in English | MEDLINE | ID: mdl-36335084

ABSTRACT

INTRODUCTION: The conect4children (c4c) consortium was setup to facilitate the development of new drugs and therapies for paediatric populations and address key challenges associated with paediatric clinical trials. Two of the major adopting principles for c4c were academia-industry partnership and data harmonisation and interoperability through common eCRF definitions. To understand the challenges arising out of these principles, the c4c team at Newcastle University conducted semi-structured interviews with four c4c industry partners. METHODS: Each partner was asked 10 questions about the data standards used in their company, management and maintenance of data dictionaries, how they dealt with paediatric-specific issues, major knowledge gaps and how academia could aid in bridging these gaps. Thematic analysis was performed to identify patterns in their answers. RESULTS: All companies use the Clinical Data Interchange Standards Consortium (CDISC) standards but face problems when certain terminology is not included in CDISC (e.g., paediatric-specific terminologies). All companies were committed to interoperability and had strict policies about how additional terminology could be added to their dictionaries. Three of the four companies maintained a single dictionary but also had lighter versions for specific usage. The two major knowledge gaps identified from the interviews were handling of non-CDISC terminology and maintenance of normal lab ranges in dictionaries. DISCUSSION: To address these gaps, c4c has been working on a four-point plan including the development of a cross-cutting paediatric dictionary and a paediatric user guide in collaboration with CDISC.


Subject(s)
Drug Development , Public-Private Sector Partnerships , Child , Humans , Qualitative Research , Clinical Trials as Topic
2.
Front Med (Lausanne) ; 11: 1370916, 2024.
Article in English | MEDLINE | ID: mdl-38966540

ABSTRACT

Introduction: 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. Methods and Results: 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. Discussion: 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.

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