BioPharma companies have multiple streams of data collection to support their research, development, and regulatory submissions. These streams serve disparate parts of the R&D organizations and separate departments. Therefore, these data rarely gets integrated or unified to serve all the stakeholders. Despite advances in laboratory technology and bioinformatics, most organizations have barriers that prevent the immediate and complete access to an integrated view into clinical trial patient data and their biomarkers in disease or treatment. This is partly due to the lack of unification of the GxP data from clinical trials, that was originally intended for submission to the regulatory agencies; and the various translational assays that may be done by biomarker and translational scientists who are researching alternate targets, understanding pathways, biological mechanisms, and diagnostics. And, partly due to the difficulty of getting access to clinical trail data from the controlled systems of clinical operations. Organizational barriers in a global Biopharma are caused by departmental autonomy, regional regulations, and data parochialism. Xbiom™ creates a virtual global hub for all Biopharma R&D in a globally dispersed organization while maintaining the integrity of the source data.
This paper discusses best practices to optimize cross-functional processes in Biopharma R&D not just to create better efficiencies but to do it by accelerating innovation, and anticipating the disruptive changes in how clinical trials will be conducted in the coming years. These best practices are good for today and it prepares for the future and its accompanying uncertainties. We will describe the role of integrating digital technologies that facilitate data transformation into a unified model; holding it for R&D purpose or re-purpose; making it searchable, findable; making results available for analysis such as differential gene expression across cohorts or ex-vivo samples or relating it to clinical end points. We will demonstrate practical implementation through our Xbiom™ solutions platform under a F.A.I.R. principle.
The paper will contemplate the nature of disruptive changes to come in the way clinical trials are planned and conducted. Ideas such as those fostered by Verily and Google, and ideas on “Deep Medicine” (by Dr. Eric Topol) and how AI will inject itself in various aspect of trial designs will change the way organization will need to think of data and how it should be reposed, and re-purposed. We will show how the Smart Transformation capabilities of Xbiom serve these needs.
Translational science is now at the center of most biologics based Biopharmas. These touch data from in-vitro, to ex-vivo to in-vivo animal studies and human clinical trials and they touch drug safety, immunology, molecular and digital biomarkers from proteomics, transcriptomics and metabolomics; and markers for CAR-T for the development of therapies, alternate targets, stratified cohort identification for extra-ordinary responders, and companion diagnostics. Xbiom™ from PointCross serves this need.