Physiologically based pharmacokinetic (PBPK) models consist of compartments representing different tissues. As most models are only verified based on plasma concentrations, it is unclear how reliable associated tissue profiles are. This study aimed to assess the accuracy of PBPK predicted beta-lactam antibiotic concentrations in different tissues and assess the impact of using effect site concentrations for evaluation of target attainment. Adipose, bone and muscle concentrations of five beta-lactams (piperacillin, cefazolin, cefuroxime, ceftazidime and meropenem) in healthy adults were collected from literature and compared to PBPK predictions. Model performance was evaluated with average fold errors (AFEs) and absolute AFEs (AAFEs) between predicted and observed concentrations. In total, 26 studies were included, 14 of which reported total tissue concentrations and 12 unbound interstitial fluid (uISF) concentrations. Concurrent plasma concentrations, used as baseline verification of the models, were fairly accurate (AFE: 1.14, AAFE: 1.50). Predicted total tissue concentrations were less accurate (AFE: 0.68, AAFE: 1.89). A slight trend for underprediction was observed but none of the studies had AFE or AAFE values outside threefold. Similarly, predictions of microdialysis-derived uISF concentrations were less accurate than plasma concentration predictions (AFE: 1.52, AAFE: 2.32). uISF concentrations tended to be overpredicted and two studies had AFEs and AAFEs outside threefold. Pharmacodynamic simulations in our case showed only a limited impact of using uISF concentrations instead of unbound plasma concentrations on target attainment rates. The results of this study illustrate the limitations of current PBPK models to predict tissue concentrations and the associated need for more accurate models. Significance Statement Clinical inaccessibility of local effect site concentrations precipitates a need for predictive methods for the estimation of tissue concentrations. This is the first study in which the accuracy of PBPK predicted tissue concentrations of beta-lactam antibiotics in man were assessed. Predicted tissue concentrations were found to be less accurate than concurrent predicted plasma concentrations. When using PBPK models to predict tissue concentrations this potential relative loss of accuracy should be acknowledged when clinical tissue concentrations are unavailable to verify predictions.

The volume of distribution at steady state (Vss) in neonates is still often estimated through isometric scaling from adult values, disregarding developmental changes beyond body weight. This study aimed to compare the accuracy of two physiologically based pharmacokinetic (PBPK) Vss prediction methods in neonates (Poulin & Theil with Berezhkovskiy correction (P&T+) and Rodgers & Rowland (R&R)) with isometrical scaling. PBPK models were developed for 24 drugs using in-vitro and in-silico data. Simulations were done in Simcyp (V22) using predefined populations. Clinical data from 86 studies in neonates (including preterms) were used for comparison, and accuracy was assessed using (absolute) average fold errors ((A)AFEs). Isometric scaling resulted in underestimated Vss values in neonates (AFE: 0.61), and both PBPK methods reduced the magnitude of underprediction (AFE: 0.82–0.83). The P&T+ method demonstrated superior overall accuracy compared to isometric scaling (AAFE of 1.68 and 1.77, respectively), while the R&R method exhibited lower overall accuracy (AAFE: 2.03). Drug characteristics (LogP and ionization type) and inclusion of preterm neonates did not significantly impact the magnitude of error associated with isometric scaling or PBPK modeling. These results highlight both the limitations and the applicability of PBPK methods for the prediction of Vss in the absence of clinical data.

Background/Objectives: Paclitaxel (PTX), a commonly used chemotherapy for breast cancer (BC), is associated with dose-limiting toxicities (DLTs) such as peripheral neuropathy and neutropenia. These toxicities frequently lead to dose reductions, treatment delays, or therapy discontinuation, negatively affecting patients’ quality of life and clinical outcomes. Current dosing strategies based on body surface area (BSA) fail to account for individual variations in body composition (skeletal muscle mass (SMM) and adipose tissue (AT) mass) and physical activity (PA), which can influence drug metabolism and toxicity. This study aims to explore the relationships between PTX pharmacokinetics, body composition, and PA to predict DLTs. Methods: This single-group observational cohort study will recruit 40 female BC patients undergoing PTX treatment. Data collection will include plasma PTX concentrations, body composition assessments (using dual X-ray absorptiometry and bioelectrical impedance analysis), PA measurements (via accelerometers), and questionnaires to assess BC-related health-related quality of life, chemotherapy-induced peripheral neuropathy, and neutropenia during the PTX schedule using validated questionnaires. Dose-limiting toxicities will be graded according to the Common Terminology Criteria for Adverse Events v5.0 (grade 3 or higher). This protocol is designed to develop a population-based PK-PD model that predicts the occurrence of chemotherapy-induced peripheral neuropathy and neutropenia in women with stage II or III BC undergoing PTX therapy, focusing on explanatory outcomes related to SMM, AT mass, and PA.

Cystic fibrosis (CF) has been linked to altered drug disposition in various studies. However, the magnitude of these changes, influencing factors, and underlying mechanisms remain a matter of debate. The primary aim of this work was therefore to quantify changes in drug disposition (top‐down) and the pathophysiological parameters known to affect pharmacokinetics (PKs; bottom‐up). This was done through meta‐analyses and meta‐regressions in addition to theoretical PK simulations. Volumes of distribution and clearances were found to be elevated in people living with CF. These increases were larger in studies which included patients with pulmonary exacerbations. Differences in clearance were smaller in more recent studies and when results were normalized to body surface area or lean body mass instead of body weight. For the physiological parameters investigated, measured glomerular filtration rate and serum cytokine concentrations were found to be elevated in people living with CF, whereas serum albumin and creatinine levels were decreased. Possible pathophysiological mechanisms for these alterations relate to renal hyperfiltration, increases in free fraction, and inflammation. No differences were detected for cardiac output, body fat, fat free mass, hematocrit, creatinine clearance, and the activity of drug metabolizing enzymes. These findings imply that, in general, lower total plasma concentrations of drugs can be expected in people living with CF, especially when pulmonary exacerbations are present. Given the potential effect of CF on plasma protein binding and the variability in outcome observed between studies, the clinical relevance of adapting existing dosage regimens should be evaluated on a case‐by‐case basis.