Current PBPK Models: Are They Predicting Tissue Drug Concentration Correctly?

Predictive Performance of Physiologically Based Pharmacokinetic Modelling of Beta-Lactam Antibiotic Concentrations in Adipose, Bone, and Muscle Tissues

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 with 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 humans 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.

Tissue Drug Concentration

Blood flow enables the delivery of oxygen and nutrients to the different tissues of the human body. Drugs follow the same route as oxygen and nutrients; thus, drug concentrations in tissues are highly dependent on the blood flow fraction delivered to each of these tissues. Although the free drug concentration in blood is considered to correlate with pharmacodynamics, the pharmacodynamics of a drug is actually primarily commanded by the concentrations of drug in the aqueous spaces of bodily tissues. However, the concentrations of drug are not homogeneous throughout the tissues, and they rarely reflect the free drug concentration in the blood. This heterogeneity is due to differences in the blood flow fraction delivered to the tissues and also due to membrane transporters, efflux pumps, and metabolic enzymes. The rate of drug elimination from the body (systemic elimination) depends more on the driving force of drug elimination than on the free concentration of drug at the site from which the drug is being eliminated. In fact, the actual free drug concentration in the tissues results from the balance between the input and output rates. In the present paper, we develop a theoretical concept regarding solute partition between intravascular and extravascular spaces; discuss experimental research on aqueous/non-aqueous solute partitioning and clinical research on microdialysis; and present hypotheses to predict in-vivo elimination using parameters of in-vitro metabolism.