GDC-0834, a Bruton's tyrosine kinase inhibitor investigated as a potential treatment of rheumatoid arthritis, was previously reported to be extensively metabolized by amide hydrolysis such that no measurable levels of this compound were detected in human circulation after oral administration. In vitro studies in human liver cytosol determined that GDC-0834was rapidly hydrolyzed with a CL int of 0.511 ml/min per milligram of protein. Aldehyde oxidase (AO) and carboxylesterase (CES) were putatively identified as the enzymes responsible after cytosolic fractionation and mass spectrometry-proteomics analysis of the enzymatically active fractions. Results were confirmed by a series of kinetic experiments with inhibitors of AO, CES, and xanthine oxidase (XO), which implicated AO and CES, but not XO, as mediating GDC-0834 amide hydrolysis. Further supporting the interaction between GDC-0834 and AO, GDC-0834 was shown to be a potent reversible inhibitor of six known AO substrates with IC 50 values ranging from 0.86 to 1.87 mM. Additionally, in silico modeling studies suggest that GDC-0834 is capable of binding in the active site of AO with the amide bond of GDC-0834 near the molybdenum cofactor (MoCo), orientated in such a way to enable potential nucleophilic attack on the carbonyl of the amide bond by the hydroxyl of MoCo. Together, the in vitro and in silico results suggest the involvement of AO in the amide hydrolysis of GDC-0834.

Bosentan (Tracleer®) is an endothelin receptor antagonist prescribed for the treatment of pulmonary arterial hypertension (PAH). Its use is limited by drug-induced liver injury (DILI). To identify genetic markers of DILI, association analyses were performed on 56 Caucasian PAH patients receiving bosentan. Twelve functional polymorphisms in five genes (ABCB11, ABCC2, CYP2C9, SLCO1B1, SLCO1B3) implicated in bosentan pharmacokinetics were tested for associations with ALT, AST and DILI. After adjusting for BMI, CYP2C9*2 was the only polymorphism associated with ALT, AST and DILI (β = 2.16, P = 0.024; β = 1.92, P = 0.016; OR 95% CI = 2.29 - ∞, P = 0.003, respectively). Bosentan metabolism in vitro by CYP2C9*2 was significantly reduced compared to CYP2C9*1 and was comparable to CYP2C9*3. These results suggest that CYP2C9*2 is a potential genetic marker for prediction of bosentan-induced liver injury and warrants investigation for the optimization of bosentan treatment.

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Purpose: To derive the theoretical basis for the extended clearance model of organ elimination following both oral and IV dosing, and critically analyze the approaches previously taken. Methods: We derived from first principles the theoretical basis for the extended clearance concept of organ elimination following both oral and IV dosing and critically analyzed previous approaches. Results: We point out a number of critical characteristics that have either been misinterpreted or not clearly presented in previously published treatments. First, the extended clearance concept is derived based on the well-stirred model. It is not appropriate to use alternative models of hepatic clearance. In analyzing equations, clearance terms are all intrinsic clearances, not total drug clearances. Flow and protein binding parameters should reflect blood measurements, not plasma values. In calculating the AUCR-factor following oral dosing, the AUC terms do not include flow parameters. We propose that calculations of AUCR may be a more useful approach to evaluate drug-drug and pharmacogenomic interactions than evaluating rate-determining steps. Through analyses of cerivastatin and fluvastatin interactions with cyclosporine we emphasize the need to characterize volume of distribution changes resulting from transporter inhibition/induction that can affect rate constants in PBPK models. Finally, we note that for oral doses, prediction of systemic and intrahepatic drug-drug interactions do not require knowledge of fu,H or Kp,uu for substrates/victims. Conclusions: The extended clearance concept is a powerful tool to evaluate drug-drug interactions, pharmacogenomic and disease state variance but evaluating the AUCR-factor may provide a more valuable approach than characterizing rate-determining steps.

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Development of new chemical entities is costly, time-consuming, and has a low success rate. Accurate prediction of pharmacokinetic properties is critical to progress compounds with favorable drug-like characteristics in lead optimization. Of particular importance is the prediction of hepatic clearance, which determines drug exposure and contributes to projection of dose, half-life, and bioavailability. The most commonly employed methodology to predict hepatic clearance is termed in vitro to in vivo extrapolation (IVIVE) that involves measuring drug metabolism in vitro, scaling-up this in vitro intrinsic clearance to a prediction of in vivo intrinsic clearance by reconciling the enzymatic content between the incubation and an average human liver, and applying a model of hepatic disposition to account for limitations of protein binding and blood flow to predict in vivo clearance. This manuscript reviews common in vitro techniques used to predict hepatic clearance as well as current challenges and recent theoretical advancements in IVIVE.

Here we characterize and summarize the pharmacokinetic changes for metabolized drugs when drug-drug interactions and pharmacogenomic variance is observed. Following multiple dosing to steady-state, oral systemic concentration-time curves appear to follow a one-compartment body model, with a shorter rate limiting half-life, often significantly shorter than the single dose terminal half-life. This simplified disposition model at steady-state allows comparisons of measurable parameters (i.e., area under the curve, half-life, maximum concentration and time to maximum concentration) following drug interaction or pharmacogenomic variant studies to be utilized to characterize whether a drug is low versus high hepatic extraction ratio, even without intravenous dosing. The characteristics of drugs based on the ratios of area under the curve, maximum concentration and half-life are identified with recognition that volume of distribution is essentially unchanged for drug interaction and pharmacogenomic variant studies where only metabolic outcomes are changed and transporters are not significantly involved. Comparison of maximum concentration changes following single dose interaction and pharmacogenomic variance studies may also identify the significance of intestinal first pass changes. The irrelevance of protein binding changes on pharmacodynamic outcomes following oral and intravenous dosing of low hepatic extraction ratio drugs, versus its relevance for high hepatic extraction ratio drugs is reemphasized. Keywords Drug-drug interactions; pharmacogenomics; area under the curve; operational half-lives; maximum systemic concentrations Tribute to Dr. Panos Macheras Recently we derived the theoretical basis for the extended clearance model of organ elimination following both oral and intravenous dosing and critically analyzed the approaches previously taken [1]. Here in this special issue of the Journal honoring our friend and colleague, Professor Panos Macheras, we extend these analyses to understand and emphasize specific applications of these concepts, reflecting the approach taken by Professor

Drug dosing decisions in clinical medicine and in introducing a drug to market for the past 60 years are based on the pharmacokinetic/clinical pharmacology concept of clearance. We used chemical reaction engineering models to demonstrate the limitations of presently employed clearance measurements based upon systemic blood concentration in reflecting organ clearance. The belief for the last 49 years that in vivo clearance is independent of the mechanistic model for organ clearance is incorrect. There is only one valid definition of clearance. Defining organ clearance solely on the basis of systemic blood concentrations can lead to drug dosing errors when drug effect sites reside either in an eliminating organ exhibiting incremental clearance or in a non-eliminating organ where intraorgan concentration is governed by transporter actions. Attempts to predict clearance are presently hampered by the lack of recognition that what we are trying to predict is a well-stirred model clearance.