ABSTRACT
BACKGROUND: Caspofungin is an echinocandin antifungal agent commonly used as the first-line therapy for invasive candidiasis, salvage therapy for invasive aspergillosis, and empirical therapy for presumed fungal infections. Pharmacokinetic (PK) variabilities and suboptimal exposure have been reported for caspofungin, increasing the risk of insufficient efficacy. OBJECTIVE: This work aimed to develop a caspofungin population pharmacokinetic (popPK) library and demonstrate its utility by assessing the probability of target attainment across diverse settings. METHODS: We established a caspofungin popPK model library following a rigorous literature review, re-implementing selected models in R with rxode2. Quality control procedures included a comparison of different studies and assessing covariate impacts. Model libraries were primarily used to perform Monte Carlo simulations to estimate target attainment and guide personalized dosing in Candida infections. RESULTS: A total of 13 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area), liver function, and albumin level. The results show that children and adults showed considerable differences in pharmacokinetics. For C. albicans and C. parapsilosis, none of the populations achieved a PTA of ≥90% at their respective susceptible MIC values. In contrast, for C. glabrata, 70% of the adult studies reached a PTA of ≥90%, while all pediatric studies achieved the same PTA level. CONCLUSION: At the recommended dosage, adult patients showed notably lower exposure to caspofungin compared to pediatric patients. Considering body size, liver function, and serum albumin is crucial when determining caspofungin dosage regimens. Furthermore, further research is required to comprehensively understand the pharmacokinetics of caspofungin in pediatric patients.
ABSTRACT
GPCR crystal structures have become more readily accessible in recent years. However, homology models of GPCRs continue to play an important role as many GPCR structures remain unsolved. The new crystal structures now available provide not only additional templates for homology modelling but also the opportunity to assess the performance of homology models against their respective crystal structures and gain insight into the performance of such models. In this study we have constructed homology models from templates of various transmembrane sequence identities for eight GPCR targets to better understand the relationship between transmembrane sequence identity and model quality. Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening. Crystal structures significantly outperformed homology models in both assessments. Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking. In virtual screening using homology models still conferred significant enrichment compared to random selection, with a clear benefit also observed in using models optimized through induced fit docking. Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications.
