Reproducibility is essential to Open Science, as there is limited relevance for finding that cannot be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, challenged, and built upon. However, due to recent advances in the biological and computational sciences, it has become difficult to process, analyze, and share data with the community in a manner that is transparent. This has made reproducing research findings more challenging, with some researchers going as far as suggesting that the biomedical sciences are experiencing a “reproducibility crisis”. To overcome these issues, we created a cloud-based platform called ORCESTRA (www.orcestra.ca), which provides a flexible framework for the reproducible processing of multimodal biomedical data. The platform enables processing of genomic and pharmacological profiles of cancer samples through the use of automated processing pipelines that are user-customizable, which are executed through Pachyderm, a data versioning and orchestration tool. ORCESTRA creates an integrated and fully documented data object known as a PharmacoSet (PSet), with a persistent identifier (DOI), that can be used and shared for future analyses using the Bioconductor PharmacoGx package.