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N.B. You can find the full, published text for this article at the bottom of this blog.
Dose adjustment and/or dose individualization beyond the guidance recommended by the drug manufacturer is part of a modern precision medicine strategy. Using models to guide dosing in such cases leveraging available data an augmenting model-based prediction by including available patient-specific data has been an approach used in a few, mostly research settings for some time. Precision dosing is an approach to utilize various patient-specific data sources to individualize pharmacotherapy of critical medicines used in the care of disease and other conditions for which drug therapy is recommended. Often the “data” in question refers to therapeutic drug monitoring of drug concentrations in blood or plasma. More recently, biomarkers and clinical outcomes have been utilized to further guide dose individualization for critical pharmacotherapy. One of the challenges that many institutions seeking to develop such solutions face is the fact that the input data of interest may not all reside in the same data location and not all are captured in sufficient detail in the electronic medical records. Moreover, different data systems, locations and governance may make the assembly of accurate, real-time data assembly and subsequent analysis particularly challenging.
Aridhia’s Digital Research Environment (DRE) provides a secure collaborative research environment for digital analysis of data. Essential companions to the DRE are dynamically updated and searchable metadata catalogs, in situ analysis tools with code versioning, as well as data provenance, and audit trails. These features facilitate the collaboration but also make it compatible with regulatory requirements. One of the more longstanding implementations of the DRE has been at the Great Ormond Street Hospital (GOSH) in London, UK. Specifically the DRIVE (Data Research, Innovation and Virtual Environments) initiative from GOSH provides a state-of-the-art unit dedicated to innovation through data and digital technologies, with partnerships across the NHS, industry and academia. While a central component of DRIVE is collaboration, an additional effort with the DRE implementation at the hospital (led by several UCL scientists) is the use of the DRE coupled with pharmacometric models to explore precision dosing solutions for the patients that walk through the door.
A tremendous opportunity exists with the enablement of precision dosing strategies within the capabilities of a DRE. The two distinct advantages I see are flexibility and collaboration driven. It is a benefit to patients in general to have dosing guidance informed by diverse patient populations (certainly beyond the boundaries of a single institution). This goes beyond the drug model as the standards of care are different around the world as well as the global marketplace for available treatments. Why not benefit from this collective knowledge? Also, for LMICs and geographic regions with limited infrastructure, sharing and collaborative environments is a means to normalize the knowledgebase and experience.
You can find the full text for the publication below.
(If you are viewing on your phone, you can download the pdf here instead.)