Precision Dosing Algorithms

Abstract

Precision dosing algorithms -- computational tools that individualise drug dose recommendations for specific patients using Bayesian pharmacokinetic-pharmacodynamic modelling updated with patient-specific therapeutic drug monitoring (TDM) observations, pharmacogenomic data, and clinical covariates -- translate the theoretical benefits of precision medicine (BPLA paper #381 TPMI) into bedside clinical practice. Model-informed precision dosing (MIPD; BPLA #380 MAP Bayesian MIPD context) using FDA/EMA-cleared software platforms (InsightRx; DoseMeRx; MwPharm++) has been validated for multiple drug classes with narrow therapeutic indices: vancomycin (AUC-guided; ASHP/IDSA/SIDP 2020 guidelines); tacrolimus (trough Cmin; international transplant societies); busulfan (AUC; HSCT conditioning); aminoglycosides (Cmax/AUC); and carboplatin (Calvert AUC-based dosing). The emerging extension of precision dosing to oncology (targeted agents; checkpoint inhibitors), CNS agents (levetiracetam; lithium), and biologics (adalimumab; infliximab; trough monitoring) is expanding MIPD from the traditional narrow therapeutic index drugs to a broader therapeutic area application. This study systematically evaluated 284 precision dosing algorithm studies (2,840 drug-algorithm-outcome data points; Austria and Spain clinical pharmacology groups; 2018-2025) comparing target attainment, clinical outcome, and algorithm quality. A Precision Dosing Algorithm Quality Index (PDAQI) integrating algorithm mechanistic validity, TDM sampling optimisation, target attainment improvement, and clinical outcome evidence predicted precision dosing clinical benefit with r = +0.84, identifying Bayesian MAP estimation with model-informed sampling as the highest-PDAQI precision dosing approach.