Population Pharmacokinetic/Pharmacodynamic Modeling of Therapeutic Enzymes in Lysosomal Storage Diseases.

Lysosomal storage diseases (LSDs) are rare genetic disorders treated with enzyme replacement therapy (ERT). However, treatment outcomes are highly variable, reflecting the complexities of therapeutic enzyme pharmacology, patient heterogeneity and therapy response. Population pharmacokinetic/pharmacodynamic (popPK/PD) modeling can help characterize this variability, identify covariates, and optimize dosing strategies. This review aimed to provide a comprehensive overview of published popPK and popPD models of therapeutic enzymes in LSDs, summarize modeling strategies and study characteristics, and evaluate the quality of the available models. A systematic search of Medline, Embase, and Web of Science (inception-March 2025) identified studies reporting popPK and/or popPD models of therapeutic enzymes in patients with LSDs. Data on study characteristics, structural and statistical model choices, covariate analyses, and evaluation methods were extracted and compared. This review included studies describing 6 popPK models and 3 popPD models of therapeutic enzymes in LSD. All models were developed using the nonlinear mixed-effects (NLME) modeling approach. The PK characteristics were adequately described using a two-compartment model in three studies, a three-compartment model in two studies, and a one-compartment model in one study. Three studies additionally assessed PK parameters in monocytes, leukocytes, and cerebrospinal fluid (CSF). Among all tested covariates, total body weight (TBW) was identified as a significant predictor for clearance (CL) and volume of distribution in the central compartment (Vc) in three studies. In one study evaluating PK parameters in CFS, age-based scaling was applied instead of weight-based allometric scaling to improve model fit. PopPD models were limited, with exposure-response relationships described either by an inhibitory maximal effect (Imax) model or by a longitudinal logistic regression model with a first-order Markov element. PopPK modeling of therapeutic enzymes in LSDs is relatively well established. However, progress in popPD modeling remains limited. Existing models support the use of indirect response and maximum effect (Emax) models to describe the delayed and saturable effects of ERT, and innovative approaches such as intracellular PK assessment and Markov modeling illustrate the potential of advanced pharmacometric methods. Nevertheless, there remains a need to further clarify the role of drug concentration measurements in target cells, to characterize CNS distribution in LSDs affecting the brain following intrathecal administration of ERTs and intravenous administration of a novel fusion protein, and to identify robust PD biomarkers in defining exposure-response relationships of therapeutic enzymes in LSDs.