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A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations.

ABSTRACT: Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics-informed in vitro-in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics-informed bottom-up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine-trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle-out optimization of mechanistic models.

SUBMITTER: Scotcher D

PROVIDER: S-EPMC7306622 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations.

Scotcher Daniel D Arya Vikram V Yang Xinning X Zhao Ping P Zhang Lei L Huang Shiew-Mei SM Rostami-Hodjegan Amin A Galetin Aleksandra A

CPT: pharmacometrics & systems pharmacology 20200522 6

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), prot ...[more]

PMID: 32441889

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Project description:Minimal physiologically based pharmacokinetic (mPBPK) models provide a simple and sensible approach that incorporates physiological elements into pharmacokinetic (PK) analysis when only plasma data are available. With this modeling concept, a second-generation mPBPK model was further developed with specific accommodations for the unique PK properties of monoclonal antibodies (mAb). This study applied this model to extensively survey mAb PK in man in order to seek general perspectives on mAb distributional and elimination features. Profiles for 72 antibodies were successfully analyzed with this model. The model results provide assessment regarding: (1) predominant clearance site, in plasma or interstitial fluid (ISF); (2) mAb ISF concentrations in two groups of lumped tissues with continuous (V(tight)) or fenestrated (V(leaky)) vascular endothelium; (3) Transcapillary escape rate (TER), an indicator of systemic vascular permeability. For 93% of surveyed mAbs, the model assuming clearance from plasma (CL) produced better or at least equivalent model performance than the model with clearance from ISF and yielded most consistent values of vascular reflection coefficients (σ1 and σ2) among all antibodies. The average mAb ISF concentration in V(tight) and V(leaky) at equilibrium was predicted to be about 6.8 and 37.9% of that in plasma. A positive correlation was detected between plasma clearance and TER among most mAbs, which could be interpreted as both parameters having common determinants related to ISF tissue distribution in this model context. The mAbs with relative higher plasma clearance (>0.035 L/h/70 kg) did not reveal such positive correlation between clearance and TER, implying that the factors contributing to high clearance may not necessarily increase tissue distribution and penetration. In conclusion, this mPBPK model offers a more mechanistic approach for analyzing plasma mAb PK than compartment models and generates parameters providing useful intrinsic distributional and elimination insights for a large number of mAbs that were examined in man.

Project description:Elevated serum creatinine (SCr ) caused by the inhibition of renal transporter(s) may be misinterpreted as kidney injury. The interpretation is more complicated in patients with chronic kidney disease (CKD) due to altered disposition of creatinine and renal transporter inhibitors. A clinical study was conducted in 17 patients with CKD (estimated glomerular filtration rate 15-59 mL/min/1.73 m2 ); changes in SCr were monitored during trimethoprim treatment (100-200 mg/day), administered to prevent recurrent urinary infection, relative to the baseline level. Additional SCr -interaction data with trimethoprim, cimetidine, and famotidine in patients with CKD were collated from the literature. Our published physiologically-based creatinine model was extended to predict the effect of the CKD on SCr and creatinine-drug interaction. The creatinine-CKD model incorporated age/sex-related differences in creatinine synthesis, CKD-related glomerular filtration deterioration; change in transporter activity either proportional or disproportional to glomerular filtration rate (GFR) decline were explored. Optimized models successfully recovered baseline SCr from 64 patients with CKD (geometric mean fold-error of 1.1). Combined with pharmacokinetic models of inhibitors, the creatinine model was used to simulate transporter-mediated creatinine-drug interactions. Use of inhibitor unbound plasma concentrations resulted in 66% of simulated SCr interaction data within the prediction limits, with cimetidine interaction significantly underestimated. Assuming that transporter activity deteriorates disproportional to GFR decline resulted in higher predicted sensitivity to transporter inhibition in patients with CKD relative to healthy patients, consistent with sparse clinical data. For the first time, this novel modelling approach enables quantitative prediction of SCr in CKD and delineation of the effect of disease and renal transporter inhibition in this patient population.

Dataset Information

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations.

Publications

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations.

Similar Datasets

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