There is growing evidence that active tubular secretory clearance (CL s ) may not decline proportionally with the glomerular filtration rate (GFR) in chronic kidney disease (CKD), leading to the overestimation of renal clearance (CL r ) when using solely GFR to approximate disease effect on renal elimination. The clinical pharmacokinetic data of 33 renally secreted OAT1/3 substrates were collated to investigate the impact of mild, moderate, and severe CKD on CL r , tubular secretion and protein binding (f u,p ). The f u,p of the collated substrates ranged from 0.0026 to 1.0 in healthy populations; observed CKD-related increase in the f u,p (up to 2.7-fold) of 8 highly bound substrates (f u,p ≤ 0.2) was accounted for in the analysis. Use of prediction equation based on disease-related changes in albumin resulted in underprediction of the CKD-related increase in f u,p of highly bound substrates, highlighting the necessity to measure protein binding in severe CKD. The critical analysis of clinical data for 33 OAT1/3 probes established that decrease in OAT1/3 activity proportional to the changes in GFR was insufficient to recapitulate effects of severe CKD on unbound tubular secretion clearance. OAT1/3-mediated CL s was estimated to decline by an additional 50% relative to the GFR decline in severe CKD, whereas change in active secretion in mild and moderate CKD was proportional to GFR. Consideration of this additional 50% decline in OAT1/3-mediated CL s is recommended for physiologically-based pharmacokinetic models and dose adjustment of OAT1/3 substrates in severe CKD, especially for substrates with high contribution of the active secretion to CL r .

Lopinavir/ritonavir, originally developed for treating HIV, is currently undergoing clinical studies for treating the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although recent reports suggest that lopinavir exhibits in vitro efficacy against SARS-CoV-2, it is a highly protein-bound drug and it remains unknown if it reaches adequate in vivo unbound (free) concentrations in lung tissue. We built a physiologically-based pharmacokinetic model of lopinavir/ritonavir in white and Chinese populations. Our aim was to perform pharmacokinetic/pharmacodynamic correlations by comparing simulated free plasma and lung concentration values achieved using different dosing regimens of lopinavir/ritonavir with unbound half-maximal effective concentration (EC 50,unbound) and unbound effective concentration 90% values of lopinavir against SARS-CoV-2. The model was validated against multiple observed clinical datasets for single and repeated dosing of lopinavir/ritonavir. Predicted pharmacokinetic parameters, such as the maximum plasma concentration, area under the plasma concentration-time profile, oral clearance, half-life, and minimum plasma concentration at steady-state were within twofold of clinical values for both populations. Using the current lopinavir/ritonavir regimen of 400/100 mg twice daily, lopinavir does not achieve sufficient free lung concentrations for efficacy against SARS-CoV-2. Although the Chinese population reaches greater plasma and lung concentrations as compared with whites, our simulations suggest that a significant dose increase from the current clinically used dosing regimen is necessary to reach the EC 50,unbound value for both populations. Based on safety data, higher doses would likely lead to QT prolongation and gastrointestinal disorders (nausea, vomiting, and diarrhea), thus, any dose adjustment must be carefully weighed alongside these safety concerns.

Perfluorooctanoic acid (PFOA) is an environmental toxicant exhibiting a years-long biological half-life (t 1/2 ) in humans and is linked with adverse health effects. However, limited understanding of its toxicokinetics (TK) has obstructed the necessary risk assessment. Here, we constructed the first middleout physiologically based toxicokinetic (PBTK) model to mechanistically explain the persistence of PFOA in humans. In vitro transporter kinetics were thoroughly characterized and scaled up to in vivo clearances using quantitative proteomics-based in vitro-to-in vivo extrapolation. These data and physicochemical parameters of PFOA were used to parameterize our model. We uncovered a novel uptake transporter for PFOA, highly likely to be monocarboxylate transporter 1 which is ubiquitously expressed in body tissues and may mediate broad tissue penetration. Our model was able to recapitulate clinical data from a phase I doseescalation trial and divergent half-lives from clinical trial and biomonitoring studies. Simulations and sensitivity analyses confirmed the importance of renal transporters in driving extensive PFOA reabsorption, reducing its clearance and augmenting its t 1/2 . Crucially, the inclusion of a hypothetical, saturable renal basolateral efflux transporter provided the first unified explanation for the divergent t 1/2 of PFOA reported in clinical (116 days) versus biomonitoring studies (1.3−3.9 years). Efforts are underway to build PBTK models for other perfluoroalkyl substances using similar workflows to assess their TK profiles and facilitate risk assessments.

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In the consumer care, cosmetics and chemical industries, there is a growing need for alternatives to animal testing to derive biokinetic data to evaluate both efficacy and safety of chemicals. One promising alternative is bottom‐up physiologically‐based biokinetic (PBK) modeling, which utilizes in vitro‐to‐in vivo extrapolation (IVIVE) for prediction of biokinetic parameters. The main challenges of IVIVE lie in suboptimal biokinetic predictions, particularly when using in vitro transporter data which often requires empirical fitting to human biokinetic data. As part of an Organization for Economic Cooperation and Development (OECD) case study, the primary objective of this work is to develop and validate quantitative proteomics‐based bottom‐up PBK models using a set of chemicals rich with in vitro and human in vivo data. Three HMG‐CoA reductase inhibitors that undergo differential elimination processes were chosen: rosuvastatin (transporter‐dependent), fluvastatin (metabolism‐dependent) and pitavastatin (mixed‐mode). PBK models were built using the Simcyp® Simulator by incorporating: (1) in vitro transporter and metabolism data (Vmax, Jmax, Km and CLint) and (2) animal tissue distribution data from literature to inform tissue‐to‐plasma equilibrium distribution ratio (Kp). Simulations were performed for single intravenous, single oral and multiple oral dosing of these chemicals. The successful prediction was based on a two‐fold criterion when compared against human biokinetic parameters. Our results showed that predicted systemic exposure (AUC0‐∞h), maximum plasma concentration (Cmax), plasma clearance (CL) and time to reach Cmax (Tmax) were within two‐fold of the observed data, with the exception of parameters associated with multiple oral pitavastatin dosing and Tmax of single oral fluvastatin dosing. The use of animal Kp data improved the predicted plasma‐concentration time profiles but did not significantly alter predicted biokinetic parameters (Figure 1). Our study demonstrated that quantitative proteomics‐based mechanistic IVIVE could account for differences in transporter and metabolic enzyme expression levels between in vitro systems and in vivo organs, allowing the prediction of whole organ clearances without any empirical scaling. We conclude that bottom‐up PBK modeling incorporating mechanistic IVIVE could be a viable alternative to animal testing in obtaining predictions of human biokinetics of chemicals.Support or Funding InformationThis work was supported by the Innovations in Food and Chemical Safety Programme [Grant number H18/01/a0/C14] and NUS Department of Pharmacy [Grant number C‐148‐000‐003‐001]. Travel funding for this conference was provided by the Innovations in Food and Chemical Safety Programme and the Skin Research Institute of Singapore.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.