On 28–29 June 2017, software developers and testers from the CLADE-IS-stars team held a hackathon focused on the processing of a series of user stories related to data management in clinical trials.
During the two days spent in the pleasant setting of Kaprálův Mlýn in a valley not far from Brno, the entire team tried out techniques of pair programming, could engage in leisure activities such as running workout or aquazorbing, or attend lectures of senior developers dedicated to the following topics: (i) Events in PHP/Symfony; (ii) Good habits in object-oriented programming (OOP) in PHP/Symfony; (iii) How and why cache should be used.
The CLADE-IS-stars team has continually developed the CLADE-IS platform, which serves to put together electronic data capture (EDC) systems dedicated to the collection, management and mining of data in the sectors of pharmaceutical industry and life sciences. During the June hackathon, the team focused on the extension of the existing modules called Adminer, Designer and Reporter and of the Proxy/Server/API unit; the new modules were (i) Cat – central administration of trials, (ii) Datavis – data visualisation and mining, (iii) Labyrinther – patient scenarios combining data in parametric and text-based form.
The Institute of Biostatistics and Analyses is an investigator of the project “Extending services portfolio of an information system for the data management in clinical research”. The project is supported by the OP EIC from the European Union funds.
Main objective of the project is the development of a platform for composition of information systems focused on data management and data mining in the field of pharmaceutical industry and life sciences. Offer of digital services based on a developed and validated information system will make reliable analytical models accessible to the companies for their decision-making and precise information sources for regulatory bodies. The project steps out of a laboratory environment of clinical trials and focuses on the evidence supported by real-world data.