A myth of the well-stirred model: Is the well-stirred model good for high clearance drugs?

Understanding the rationale of the well-stirred model (WSM), borrowed from chemical engineering, has been ongoing through the history of pharmacokinetics (PK) as an independent discipline. Extensive arguments around the WSM and 1977's lidocaine data re-emerged recently. It was proposed that Pang and Rowland's lidocaine data analysis was confounded by four intermingled confounding factors which may lead to contradictory conclusions or inconclusive dilemma. This re-visit of 1977's lidocaine data analysis was challenged by Pang and coauthors. This commentary is our responses to their comments focusing on the lidocaine data analysis and the IVIVE by the WSM. In addition, the disadvantage of applying the well-stirred model in drug-drug interaction (DDI) prediction and a theoretical dilemma in the commonly used whole-body physiologically based pharmacokinetic (PBPK) models were discussed.

Identification of cyclophilin-40-interacting proteins reveals potential cellular function of cyclophilin-40.

Cyclophilin-40 (CyP40) is part of the immunophilin family and is found in Hsp90-containing protein complexes. We were interested in identifying proteins that interact with CyP40. CyP40-interacting proteins in HeLa cells were identified using the tandem affinity purification approach. Adenovirus expressing human CyP40 protein (Ad-CyP40), fused with streptavidin and calmodulin binding peptides at the N terminus, was generated. Proteins were separated on a sodium dodecyl sulfate-polyacrylamide gel electrophoresis gel after tandem affinity purification. Here 10 silver-stained protein bands that were enriched in the Ad-CyP40-infected lysate and the corresponding regions in the control lysate were excised, digested by trypsin, and identified by tandem mass spectrometric analysis. Of 11 interacting proteins that were identified, 4 (RACK1, Ku70, RPS3, and NF45) were expressed in rabbit reticulocyte lysate, bacteria, and MCF-7 cells. We confirmed that these proteins interact with CyP40. We observed that RACK1 suppressed the cobalt chloride-induced, hypoxia response element-dependent luciferase activity in MCF-7 cells but not in MCF-7 stable cells expressing approximately 10% of the cellular CyP40 content. In addition, RACK1 reduced the HIF-1α protein accumulation after cobalt chloride treatment, which was not observed when the CyP40 content was down-regulated. Collectively, we conclude that reduction of the HIF-1 α protein by RACK1 is CyP40-mediated.

Time effect of rutaecarpine on caffeine pharmacokinetics in rats.

Rutaecarpine is reported as a potent inducer of CYP1A2 enzyme in rats. There are natural herbal supplements containing rutaecarpine that are designed to enhance the CYP1A2-dependent removal of caffeine from blood so that people can have coffee later in the day without causing sleep interference. This study aimed to determine the minimum amount of time needed from oral rutaecarpine administration until the observed effect of rutaecarpine on caffeine pharmacokinetics (PK) in 15 male Sprague-Dawley rats. PK parameters for caffeine and its metabolites in the control and rutaecarpine groups were calculated using WinNonlin®. Results showed that orally administered rutaecarpine at 100 mg/kg dose as early as 3 h before oral caffeine administration significantly decreased the oral systemic exposure and mean residence time of caffeine and its metabolites due to decreased caffeine bioavailability (by up to 75%) and increased clearance. The systemic exposure of caffeine and its metabolites were also decreased when caffeine was given intravenously, though this effect was less pronounced than when caffeine was given orally. Although plasma level of rutaecarpine was undetectable (less than 10 ng/mL), rutaecarpine still induced hepatic CYP1A2 activity. Results from 7-methoxyresorufin O-demethylation activity, which is specific to CYP1A2, showed that 3 h after one rutaecarpine oral dose, CYP1A2 activity in rat liver tissue was increased by 3- fold. This finding suggested that rutaecarpine effectively induced CYP1A2 activity in the liver.

Discussions on the hepatic well-stirred model: Re-derivation from the dispersion model and re-analysis of the lidocaine data.

Roberts and Rowland explained the well-stirred model as an extreme case of the dispersion model when the dispersion number is infinity. However, the inconsistency within and discrepancy between the theoretical explanation and experimental observations of the well-stirred model are discovered. In this paper, the well-stirred model is examined from both mathematical and physiological points of view. The well-stirred model is re-derived from the convection-elimination equation using the finite difference method. The well-stirred model is a subset of the parallel-tube model when the dispersion number is zero and concentration gradient is ignored. The relative errors and sensitivities of the well-stirred and the parallel-tube models are compared using numerical simulations. The well-stirred model should not be used to estimate in vivo apparent intrinsic clearance from hepatic extraction ratio for high extraction ratio drugs and predicting availability is not recommended for high extraction ratio drugs with either the well-stirred or the parallel-tube models. Based on our theoretical derivation and numerical simulations, we found lidocaine data analysis in Pang and Rowland's 1977 paper was based on an unfair comparison of these two models at two different efficiency number ranges. The high sensitivity of the parallel-tube model at a relatively lower efficiency number range versus the lack of sensitivity of the well-stirred model at an extremely high efficiency number range leads one to believe that the well-stirred model fit the data of high extraction ratio drugs such as lidocaine better. However, the intrinsic clearance values estimated by the parallel-tube model are much more consistent with both in vitro data and those estimated by the dispersion model than those by the well-stirred model. In addition, a key assumption used in the data analysis that the intrinsic clearance is independent of changes in blood flow may not be true. Both theoretical discussions and experimental results indicate that apparent intrinsic clearance and intrinsic clearance could be affected by blood flow and protein binding. Moreover, the lidocaine data analysis in 1977 paper could be control condition dependent and misleading when it is applied to data from other drugs, such as diazepam and diclofenac. The distinction between the well-stirred and parallel-tube models is a result of the mathematical treatment of concentration gradient rather than the flow pattern or extent of physical mixing. The well-stirred model is not likely better than the parallel-tube model. One should be cautious of using the well-stirred model for comparing in vitro intrinsic clearance and estimated in vivo "intrinsic clearance" for high clearance drugs.

Is Ciprofloxacin a Substrate of P-glycoprotein?

INTRODUCTION: Studies using MDCKII and LLC-PK1 cells transfected with MDR1 cDNA indicate that ciprofloxacin is not a substrate of P-glycoprotein. However, our data has shown that transport studies done using different P-gp overexpressing cell lines (MDCKI-MDR1, MDCKII-MDR1 and L-MDR1), could lead to contradictory conclusion on whether a compound is a substrate of P-gp. The aim of our study was to determine if ciprofloxacin is indeed not a P-glycoprotein substrate using MDCKI cells transfected with human MDR1 cDNA. METHODS: Semi-quantitative RT-PCR was used to determine the mRNA level of MDR1 while Western blot was performed to determine the protein expression level of P-gp, MRP1 and MRP2 in various cells. Ciprofloxacin bidirectional transport studies were performed in MDCKI, MDCKI-MDR1, MDCKII, MDCKII-MDR1, MDCKII-MRP2, LLC-PK1, L-MRP1 and L-MDR1 cells. RESULTS: Ciprofloxacin showed net secretion in MDCKI-MDR1 but net absorption in MDCKI cells. Various P-gp inhibitors decreased the B to A and increased the A to B transport of ciprofloxacin in MDCKI-MDR1 cells while having no effect in MDCKI cells. The B to A transport of ciprofloxacin in MDCKI-MDR1 cells was not affected by non-P-gp inhibitors. In the presence of indomethacin, ciprofloxacin showed net secretion instead of net absorption in MDCKI cells while in the presence of probenecid and sulfinpyrazone, there was no net secretion and absorption. There was no difference in ciprofloxacin transport between MDCKII and MDCKII-MDR1, LLC-PK1 and L-MDR1, LLC-PK1 and L-MRP1 and MDCKII and MDCKII-MRP2. CONCLUSIONS: Transport data in MDCKI and MDCKI-MDR1 cells indicate that ciprofloxacin is a substrate of P-gp but data from MDCKII, MDCKII-MDR1, LLC-PK1 and L-MDR1 cells indicate that ciprofloxacin is not a substrate of P-gp. Vinblastine, a well-known P-gp substrate, also did not show differences between LLC-PK1 and L-MDR1 cells. Further studies need to be performed to characterize these P-gp overexpressing cell lines and the transport of ciprofloxacin.

Benzo[a]pyrene increases the Nrf2 content by downregulating the Keap1 message.

We employed the suppressive subtractive hybridization to identify 41 up- and downregulated transcripts in Jurkat cells after benzo[a]pyrene (BaP) treatment. Among the 21 downregulated transcripts, we found that BaP suppresses the Keap1 transcript by 7.5-fold. Subsequent analyses revealed that BaP significantly suppresses the Keap1 message and protein levels to about 40 and 60%, respectively, of the vehicle controls in Jurkat cells without reactive oxygen species involvement. In addition, the nuclear Nrf2 (nuclear factor erythroid 2-related factor) protein content is significantly increased by 2.6-fold. The same BaP treatment to Hepa1c1c7 cells also downregulates the Keap1 message and protein levels to a similar extent. When we treated Jurkat cells with 3-(4-morpholinyl)propyl isothiocyanate, which is known to increase the amount of the Nrf2 content, we found that there is no change in the Keap1 message, but the amount of the Keap1 (kelch-like ECH-associated protein 1) protein is reduced to 75% of the vehicle controls. Although both Nrf2 target messages nqo1 and gstp1 are upregulated by BaP in Jurkat cells, only GSTP1 is upregulated at the protein level. Unlike Hepa1c1c7 cells, Jurkat cells have no detectable aryl hydrocarbon receptor and BaP metabolites, minimal CYP1A1 activity, and no quinone oxidoreductase 1 (NQO1) activity. We concluded that BaP, but not its metabolites, increases the amount of the nuclear Nrf2 protein by downregulating the Keap1 message in Jurkat cells.