The development of model-informed precision dosing (MIPD) tools, especially in the form of native or web-based applications to be used at the bedside, has garnered marked attention in recent years. Their potential clinical benefit can be large, but it should be ensured that such tools make optimal use of available clinical data and have adequate predictive ability. Unique scientific challenges specific to MIPD remain, which may require adaptation of commonly used diagnostics in pharmacometrics.
In 1969, Lewis B. Sheiner published a paper that can now only be described as seminal, as it launched the field of pharmacometrics as we know it. This paper, and similar work done in the early 1970s by Roger Jelliffe and his group at USC, demonstrated the rudimentary concepts of how clinical pharmacokinetic (PK) data can be fed into computer-based algorithms to optimize drug treatment for patients. In the ensuing 5 decades, the field of pharmacometrics has grown markedly. Although model-informed precision dosing (MIPD), a recently introduced label, has always attracted a subset of clinical researchers, it seems to have gained renewed attention from the modeling community, evidenced by the release of new software tools, the publication of opinion papers the scheduling of various dedicated conference sessions (ASCPT, PAGE, ACoP, and ACCP), and the creation of a Special Interest Group within ISoP (“Applied Clinical Pharmacometrics”).
MIPD generally requires custom-made software tools because generic modeling software, such as MATLAB or NONMEM, is too cumbersome and complex for most practicing clinical providers to learn and apply. Dedicated tools are likely to come in the form of a mobile or web-based application that contains algorithms for drawing inference from available clinical data and evaluating future personalized treatment courses. For any academic or commercial MIPD tool to be applied successfully at the point-of-care, a considerable number of technical, organizational, regulatory, and financial hurdles need to be overcome, some of which have been highlighted before. Furthermore, to drive adoption of these tools in the clinic practice, it is essential to provide proper education of the intended end-user, and provide proof of improved efficacy, reduced toxicity, and/or reduced costs, preferably from prospective clinical trials. Finally, even though the science of pharmacometrics has progressed considerably, within the subfield of MIPD, a considerable number of scientific challenges still remain.
Keizer, R.J., ter Heine, R., Frymoyer, A., Lesko, L.J., Mangat, R. and Goswami, S. (2018), Model-Informed Precision Dosing at the Bedside: Scientific Challenges and Opportunities. CPT Pharmacometrics Syst. Pharmacol., 7: 785-787. https://doi.org/10.1002/psp4.12353