Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease

Chang, Shih-Yu; Huang, Weize; Chapron, Alenka; Quiñones, Antonio J. López; Wang, Joanne; Isoherranen, Nina; Shen, Danny D.; Kelly, Edward J.; Himmelfarb, Jonathan; Yeung, Catherine K.

doi:10.1007/s11095-023-03594-x

Cited by 2 publications

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“…OAT activity beyond what would be predicted by intact nephron hypothesis may be due to inhibition of these transporters by uremic solutes rather than additional downregulation of their expression (Chang et al, 2023). The impact of uremic solutes on kidney OAT activity and renal clearance of tenofovir in patients with renal impairment was simulated using the mechanistic kidney model (Chang et al, 2023). The importance of understanding the variability and individual changes in kidney blood flow, GFR, and transporter activity in progressive kidney disease was illustrated via use of the mechanistic kidney model to predicting drug clearance in chronic kidney disease in individual patients based on biomarker data of transporter activity in the kidney in the same individuals (Granda et al, 2023).…”

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confidence: 86%

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confidence: 99%

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Physiologically Based Pharmacokinetic Modeling of Small Molecules: How Much Progress Have We Made?

Isoherranen

2024

Drug Metabolism and Disposition

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Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and in academic research. The use of PBPK models is continuously expanding with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiological changes into the models. Due to the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series of gut compartments allowing modeling of physiological blood flow distribution within an organ and zonation of metabolic enzymes, and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This review suggests that awareness of the need for predefined criteria for model acceptance has increased but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance.

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confidence: 86%

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confidence: 99%

Physiologically Based Pharmacokinetic Modeling of Small Molecules: How Much Progress Have We Made?

Isoherranen

2024

Drug Metabolism and Disposition

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Proximal Tubule-on-Chip for Predicting Cation Transport: Dynamic Insights into Drug Transporter Expression and Function

Petit,

Faucher,

Bernard

et al. 2024

Preprint

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Deciphering the sources of variability in drug responses requires to understand the processes modulating drug pharmacokinetics. However, pharmacological research suffers from poor reproducibility across clinical, animal, and experimental models. Predictivity can be improved by using Organs-on-Chips, which are more physiological, human-oriented, micro-engineered devices that include microfluidics. OoC are particularly relevant at the fundamental and preclinical stages of drug development by providing more accurate assessment of key pharmacokinetic events. We have developed a proximal tubule-on-a-chip model combining commercial microfluidic and chip technologies. Using the RPTEC/TERT1 cell line, we set up a dual-flow system with antiparallel flows to mimic the dynamics of blood and urine. We assessed transporters mRNA expression using RT-qPCR, cellular polarization and protein expression via immunofluorescence and confocal microscopy, and monitored the transcellular transport of a list of prototypic xenobiotics by determining their efflux ratios with LC-MS/MS. Our results show that flow exposure significantly modulate mRNA expression of drug membrane transporters compared to static conditions. Dynamic conditions also enhance cell polarization, as evidenced by preferential basal and apical expressions of Na+/K+-ATPase, P-gp, OCT2, and MATE1 , as well as the cellular secretory profile. We demonstrated unidirectional transcellular transport of a cationic substrate (metformin) with a higher efflux than influx ratio, inhibited with a specific OCT2 inhibitor, thus confirming the relevance of our proximal tubule-on-a-chip set up for cation transport investigations. Our proximal tubule-on-a-chip can also be used to explore the interactions between transporters, xenobiotics, and endogenous metabolites, possibly involved in the variability of individual drug responses. This study provides additional evidence that OoC can bridge the gaps between systemic and local pharmacokinetics, i.e., drug concentration close to its target, at the fundamental and preclinical stages.

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Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease

Cited by 2 publications

References 42 publications

Physiologically Based Pharmacokinetic Modeling of Small Molecules: How Much Progress Have We Made?

Physiologically Based Pharmacokinetic Modeling of Small Molecules: How Much Progress Have We Made?

Proximal Tubule-on-Chip for Predicting Cation Transport: Dynamic Insights into Drug Transporter Expression and Function

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