D2.1 Whitepaper on the platform knowledge base and data standards for in silico drug repurposing

Computational drug repurposing integrates data from diverse sources, such as sequence databases, GWAS studies, or high-throughput screens. Depending on the original use case or field of research, they vary in availability, timeliness, and compatibility with other data sources. Further, numerous computational tools have been introduced designed to identify active disease modules, indications, or drug-target interactions that use different methods and strategies while not adhering to standard guidelines. Clearing and harmonising the resulting inconsistencies consume essential resources such that compiling a well-structured work plan is fundamental. This whitepaper demonstrates the results of a systematic review effort of about 400 publications and proposes valuable resources and specific strategies for the REPO4EU consortium. We present reviews, databases and computational methods by their applicability to work package-specific tasks and suggest using popular data standards such as FASTQ, SAM and VCF for sequencing data. In detail, we argue how NeDRexDB should serve as an instance of a knowledge base in this project, outline how to create a reproducible yet flexible pipeline for module discovery, and lay out the application of the BioPAX standard for disease module representation. Future challenges include establishing guidelines for computational drug repurposing, flexible and standardised workflows, and comprehensive in silico validation. We are confident that this work will provide a solid basis for tackling them.