Journal of In Silico & In Vitro Pharmacology

Abstract

The unique skills of data management are always in high demand by the potential companies as they allow the candidate to effectively manage and use information and support the company’s overall biometrics objective. Apart from technical skills, data management team needs to strategically imbibe the required therapeutic area knowledge which always gives an upper hand cumulatively with the innovative technical skills. The skills of data management in general involves database planning and design, managing EDC (database software), data review and analysis etc. along with ability to understand what data means to the organization. The potential data manager should act as a strong communicator and should have a clear communication channel with all the internal and external stakeholders of the clinical trial. In a current scenario, as the clinical trials continue to become complex, it is inherent that the data produced should be customized in the most advantageous way during the trial. With the application of AI and powerful machine learning tools which has the ability to monitor the data as it is produced/generated by identifying the inconsistencies in an ongoing trial; biometrics service providers (CROs) can detect problems at an early stage and save the ongoing trail from implications of bad data. The adoption of AI and machine learning by CROs is the future of clinical research as they can pull multiple data sources, increase the load of data collected and in few hours they can accomplish tasks that would consume months or even years by the human researchers / data analysts which in turn facilitates pharmaceutical treatments to market faster.