A GFR-Based Method to Predict the Effect of Renal Impairment on the Exposure or Clearance of Renally Excreted Drugs: A Comparative Study Between a Simple GFR Method and a Physiologically Based Pharmacokinetic Model

Abstract

Objective The objective of this study was to compare the predictive performances of a glomerular filtration rate (GFR) model with a physiologically based pharmacokinetic (PBPK) model to predict total or renal clearance or area under the curve of renally excreted drugs in subjects with varying degrees of renal impairment. Methods From the literature, 11 studies were randomly selected in which total or renal clearance or area under the curve of drugs in subjects with different degrees of renal impairment were predicted by PBPK models. In these published studies, drugs were given to subjects intravenously or orally. The PBPK model was generally a whole-body model whereas the GFR model was as follows: Predicted total clearance (CL T ) = CL T in healthy subjects × (GFR in RI/GFR in H), Predicted AUC = AUC in healthy subjects × (GFR in H/GFR in RI), where H is the healthy subjects and RI is renal impairment. The predicted clearance or area under the curve values using PBPK and GFR models were compared with the observed (experimental pharmacokinetic) values. The acceptable prediction error was within the 0.5- to 2-fold or 0.5- to 1.5-fold prediction error. Results There were 33 drugs with a total number of 101 observations (area under the curve, total and renal clearance in subjects with mild, moderate, and severe renal impairment). From PBPK and GFR models, out of 101 observations, 94 (93.1%) and 96 (95.0%) observations were within the 0.5- to 2-fold prediction error, respectively. Conclusions This study indicates that the predictive power of a simple GFR model is similar to a PBPK model for the prediction of clearance or area under the curve in subjects with renal impairment. The GFR method is simple, robust, and reliable and can replace complex empirical PBPK models.

Drug–Drug Interactions in People Living With HIV at Risk of Hepatic and Renal Impairment: Current Status and Future Perspectives

“…The clinical assessment of potential DDIs between ARVs and commonly used co‐medications in people living with HIV and renal impairment is vital to prevent the development of ESRD, AKI, and CKD, as well as to prevent ineffective ARV treatment 58 . Although outside the scope of this review, renal impairment has been reported to impact the glomerular filtration rate, affecting overall drug clearance and, in turn, potential DDI magnitudes through changes in perpetrator and/or victim concentrations 59 . Furthermore, a previous review highlighted the impact of kidney disease on drug metabolism and transport 60 .…”

“… 58 Although outside the scope of this review, renal impairment has been reported to impact the glomerular filtration rate, affecting overall drug clearance and, in turn, potential DDI magnitudes through changes in perpetrator and/or victim concentrations. 59 Furthermore, a previous review highlighted the impact of kidney disease on drug metabolism and transport. 60 Experimental models of ESRD demonstrated decreased activity and downregulation of hepatic and intestinal metabolic enzymes and transporters.…”

Predicting transporter mediated drug–drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

“…(2012) studied the same phenomena by considering the impact of CKD on the metabolic and transporter‐mediated clearance of sildenafil, repaglinide, and telithromycin. Apart from these, few modeling attempts were also made with regard to changes in GFR as per severity, stage of disease, and by integrating the effect of CKD on tubular reabsorption and tubular adaptations (Huang & Isoherranen, 2020; Mahmood, 2020; Rasool et al., 2021; Zhou et al., 2019). Upcoming work in this area would be to incorporate changes in the expression and abundance of DMETs within renal or extrarenal tissues (Butrovich et al., 2022; Imaoka et al., 2021) along with the effect of other comorbidities such as age and lifestyle along with CKD (Scotcher & Galetin, 2022).…”

Spreadsheet‐Based Minimal Physiological Models for the Prediction of Clearance of Therapeutic Proteins in Pediatric Patients

“…Recently, Mahmood 19 compared a whole‐body PBPK model with a simple glomerular filtration rate model for the prediction of total and renal clearances of extensively renally excreted drugs in subjects with renal impairment (mild, moderate, and severe) and found that both models provided similar results. The study indicates that to predict total and renal clearances of drugs in subjects with renal impairment, a PBPK model is unnecessary and a simple model that uses just one physiological parameter (glomerular filtration rate) is enough to achieve similar objectives.…”