To accelerate the discovery and development of the next generation of medicines, it is important to efficiently incorporate the outcomes of translational research into clinical studies, while transferring scientific insights from the clinic to the bench to guide further laboratory research. The goal of translational and exploratory clinical research is thereby to increase the probability of success of clinical trials through enabling understanding and prediction of drugs’ mechanism of action, potential side effects, and patient responses to treatment.
This approach presents significant logistic and technical challenges. Firstly, bioinformaticians, statisticians, and data scientists need to find the right data from within or across clinical and pre-clinical studies, stored in different locations and management systems. Once they do find the relevant data, they may not have permission to access it, since clinical data contains sensitive information about patients. It is also common that the available data is not in the appropriate format, thus requiring harmonization prior to analysis. After the data has been collected from different sources, processed, and harmonized, scientists need to integrate and potentially further harmonize multi-modal data for downstream analysis and visualization using a range of statistical and data visualization tools, such as RStudio. All these processes are highly time-consuming and can delay subsequent important business decisions.
What bioinformaticians, statisticians, and data scientists need is a platform that provides them with analysis-ready datasets. They would also vastly benefit from a tool that allows the communication of results to stakeholders (e.g., scientists and clinical researchers) in a standardized, reproducible, and interactive manner. This is where Genedata Profiler makes a difference.
Integrable RStudio Products