Novel SDTM Implementation to Maximize Benefits of Sharing Legacy Data
Creators: name: Lee, Jennifer
name: Kennon, Kalynn
Publisher: name: Zenodo
Year: 2025
Subjects: Working with challenging data: Universal standards and expectations and that of context and discipline specific adaptations
Data standards
Data re-use
Challenging data
IDCC25
Lightning Talks

description: The Infectious Diseases Data Observatory (IDDO) is a scientifically independent multi-disciplinary coalition of the global infectious disease community. It is a data sharing platform which hosts poverty-related infectious disease data and promotes data sharing and re-use. IDDO is unique in that we curate individual participant data (IPD) in-house from many different sources, to produce freely available harmonised datasets, enabling scientists to answer new research questions from existing data.

IDDO is built on and incorporates the pioneering work of the WorldWide Antimalarial Resistance Network (WWARN). WWARN is a collaborative data-sharing platform begun in 2009 that proved it was possible to produce policy-changing scientific evidence from pooling existing data. Pivoting from WWARN’s success, IDDO developed to fulfil the need of various infectious disease research communities to create a similar IPD sharing platform. The IDDO data sharing platform hosts IPD for over one million participants across a wide range of poverty-related infectious diseases data including malaria, Covid-19, Ebola virus, Visceral leishmaniasis, Chagas disease, schistosomiasis and soil-transmitted helminthiases, and antimicrobial resistance with more being scoped for feasibility.

Due to the disparate nature of the IPD contributed to IDDO, transformation to a single data standard was key – to alleviate the burden of having to create a unique standard and repository for each disease type and, to harmonise the data allowing pooling for secondary analysis of IPD across disease types, interventions, and populations. IDDO chose the Study Data Tabulation Model (SDTM) developed by the Clinical Data Interchange Standards Consortium (CDISC), which provides powerful tools for collection, storage, and analysis of clinical trial data. The comprehensiveness of CDISC SDTM allowed for aggregation and storage of standardised data while providing the flexibility needed to accommodate the intricacies of the real-world data IDDO receives from various clinical trials and observational studies.

The SDTM model and implementation was originally created to organize clinical trial data for submission to drug regulatory authorities. There were instances where standard implementation of the SDTM model was not appropriate for the legacy and real-world data contributed to IDDO. Therefore, while embracing the core SDTM model and adhering to the rules and original intent for the standard, IDDO has made use of a bespoke implementation of SDTM. We have made specific adaptations with the aim to maximise usefulness and usability of the data for pooled analysis, especially to those unfamiliar with CDISC standards, to encourage reuse of this limited resource and enable the generation of new evidence to impact public policy and treatment guidelines to improve the lives of those suffering from these diseases.

This talk will provide an overview of our data reuse platform, a single repository that allows for pooling of existing data across all infectious diseases data held by IDDO. We will discuss the challenges inherent in this process as well as our solutions, including customised adaptations of CDISC SDTM to promote findability, accessibility, and interoperability of legacy and real-world patient data, allowing for the generation of new evidence and extending the life of existing data resources beyond a single clinical trial.