eCRF for the MONET Study

MONET stands for adaptative, phase IV (i.e. post-approval) randomized, open-label, multicenter study to determine the safety and efficacy of different monoclonal antibodies (MoAbs) to SARS-CoV-2 for the early treatment of COVID-19 in non-hospitalized adults. The study also evaluated the effect of monoclonal antibodies in the prevention of hospitalization, reduction of SARS-CoV-2 detected levels of RNA in nasal swabs, and symptom resolution in general.

The MONET study was sponsored by INMI Spallanzani and SIMIT (Società Italiana di Malattie Infettive e Tropicali), along with Società Italiana di Medicina Generale e delle Cure Primarie (SIMG) and Società Italiana di Farmacologia (SIF). 

With 42 medical facilities involved, this study had a medium sample size, with 467 participants who were asked to report their COVID-19 symptoms and temperature daily in a diary. Each patient also had four follow-up visits, for a total of 1269 visits. The clinical trial also included a pharmacological substudy (PK) and an immunological substudy (IMMUNE-MONET) with 150 and 20 participants respectively. 

Livebase proved to be essential to timely design and generate a robust eCRF application to support the study. In fact, the platform allowed a single data architect to deliver a fully functional application to all the 42 medical facilities involved in just five days, on-time and on-budget, in January 2022.

A very large amount of data was collected for all patients, ranging from general examinations on vital parameters and routine haematochemical examinations to SARS-CoV-2 serology (IgA, IgG, IgM, and neutralizing antibodies) and T-cell response to S and N antigens (in a subgroup of patients).

The eCRF application supported patients randomization, tracking of potential adverse effects related to monoclonal antibodies, import of data from lab equipment and tracking of any changes  applied to all the critical registries. In this regard, Livebase can generate all the functionality required to track, search and retrieve any change applied to a given piece of information (e.g. the adverse effects), by just marking the corresponding class in the application model as "versioned". This provide the data scientist a powerful tool to detect who changed what and when.

The eCRF application generated by Livebase, grounded in a relational database management system, allowed for the scientific database to be exported and shared in a universally compatible SQL format. This format is readily accessible to data scientists and can be effortlessly imported into diverse statistical analysis software. Moreover, the Livebase models employed during development served as invaluable conceptual guides to the database's logical structure, enhancing data understanding and significantly reducing the risk of misinterpretation.