Search

Here we present, utilizing universally accepted relationships for hepatic clearance at steady state, that for all models of hepatic elimination the ratio of unbound liver drug concentration to unbound systemic blood concentration, Kpuu, is a function of or related to the hepatic bioavailability for that drug, FH. According to the derivation for the well-stirred model, Kpuu can never exceed unity, can frequently be a function of hepatic blood flow, and is equivalent to the value of FH as determined following oral dosing. For the parallel tube model, Kpuu will not equal FH but will be a function of FH and will also never be a value greater than 1. When hepatic clearance is rate limited by basolateral transporters, Kpuu will be less than 1, and less than FH. We believe that such outcomes are highly unlikely, and that the error arises from a basic assumption concerning hepatic clearance that leads to the mechanistic models of hepatic elimination, the well-stirred, parallel tube and dispersion models. That basic assumption is that the steady-state systemic concentration multiplied by the hepatic systemic clearance is equal to the product of the average unbound liver steady-state concentration and the intrinsic hepatic clearance (Css · CL = CH,u · CLint). Calculations of Kpuu and FH based on present methods of analysis provide a strong argument as to why this universally accepted relationship is not correct. Alternatively, we have shown in recent publications that hepatic clearance may be adequately determined based on Kirchhoff's Laws where no assumption of the above equality concerning hepatic intrinsic clearance is required, and where Kpuu is independent of hepatic extraction ratio and FH.

As explained by the free drug theory, the unbound fraction of drug has long been thought to drive the efficacy of a molecule. Thus, the fraction unbound term, or fu, appears in equations for fundamental pharmacokinetic parameters such as clearance, and is used when attempting in vitro to in vivo extrapolation (IVIVE). In recent years though, it has been noted that IVIVE does not always yield accurate predictions, and that some highly protein bound ligands have more efficient uptake than can be explained by their unbound fractions. This review explores the evolution of fu terms included when implementing IVIVE, the concept of protein-facilitated uptake, and the mechanisms that have been proposed to account for facilitated uptake.

For almost a half-century clearance concepts have been utilized in pharmacokinetics to understand the relationship between the dose administered and the time course of systemic concentrations to predict efficacy and safety, as well as how dosing should be modified in disease states. Various models of organ clearance/elimination have been proposed and tested. Surprisingly, however, the theoretical basis for the appropriate data collection to test these models has never been evaluated. Here we show that in vivo data collection limitations and the extraction ratio concept itself are only consistent with the well-stirred model of hepatic elimination. Evaluating measures of drug concentrations entering and leaving an organ will appear to best fit the well-stirred model, since driving force concentrations within the organ of elimination cannot be measured.

We previously demonstrated pharmacokinetic differences among manufacturing batches of a US Food and Drug Administration (FDA)-approved dry powder inhalation product (Advair Diskus 100/50) large enough to establish between-batch bio-inequivalence. Here, we provide independent confirmation of pharmacokinetic bio-inequivalence among Advair Diskus 100/50 batches, and quantify residual and between-batch variance component magnitudes. These variance estimates are used to consider the type I error rate of the FDA's current two-way crossover design recommendation. When between-batch pharmacokinetic variability is substantial, the conventional two-way crossover design cannot accomplish the objectives of FDA's statistical bioequivalence test (i.e., cannot accurately estimate the test/reference ratio and associated confidence interval). The two-way crossover, which ignores between-batch pharmacokinetic variability, yields an artificially narrow confidence interval on the product comparison. The unavoidable consequence is type I error rate inflation, to ∼25%, when between-batch pharmacokinetic variability is nonzero. This risk of a false bioequivalence conclusion is substantially higher than asserted by regulators as acceptable consumer risk (5%).

We previously demonstrated pharmacokinetic differences among manufacturing batches of a US Food and Drug Administration (FDA)-approved dry powder inhalation product (Advair Diskus 100/50) large enough to establish between-batch bio-inequivalence. Here, we provide independent confirmation of pharmacokinetic bio-inequivalence among Advair Diskus 100/50 batches, and quantify residual and between-batch variance component magnitudes. These variance estimates are used to consider the type I error rate of the FDA's current two-way crossover design recommendation. When between-batch pharmacokinetic variability is substantial, the conventional two-way crossover design cannot accomplish the objectives of FDA's statistical bioequivalence test (i.e., cannot accurately estimate the test/reference ratio and associated confidence interval). The two-way crossover, which ignores between-batch pharmacokinetic variability, yields an artificially narrow confidence interval on the product comparison. The unavoidable consequence is type I error rate inflation, to ∼25%, when between-batch pharmacokinetic variability is nonzero. This risk of a false bioequivalence conclusion is substantially higher than asserted by regulators as acceptable consumer risk (5%).

Assessing treatment adherence and quantifying exposure to anti-tuberculosis drugs among children is challenging. We undertook a 'proof of concept' study to assess the drug concentrations of isoniazid (INH) in hair as a therapeutic drug monitoring tool. Children aged

The biopharmaceutics drug disposition classification system was developed in 2005 by Wu and Benet as a tool to predict metabolizing enzyme and drug transporter effects on drug disposition. The system was modified from the biopharmaceutics classification system and classifies drugs according to their extent of metabolism and their water solubility. By 2010, Benet et al. had classified over 900 drugs. In this paper, we incorporate more than 175 drugs into the system and amend the classification of 13 drugs. We discuss current and additional applications of BDDCS, which include predicting drug-drug and endogenous substrate interactions, pharmacogenomic effects, food effects, elimination routes, central nervous system exposure, toxicity, and environmental impacts of drugs. When predictions and classes are not aligned, the system detects an error and is able to self-correct, generally indicating a problem with initial class assignment and/or measurements determining such assignments.

The biopharmaceutics classification system (BCS) and biopharmaceutics drug distribution classification system (BDDCS) are complementary classification systems that can improve, simplify, and accelerate drug discovery, development, and regulatory processes.

Human induced pluripotent stem cells (iPSCs) have the capability of revolutionizing research and therapy of liver diseases by providing a source of hepatocytes for autologous cell therapy and disease modelling. However, despite progress in advancing the di

This study investigated 2 hypotheses about genotype-phenotype relationships for the efflux transporter, P-glycoprotein: (1) the presence of a synonymous C3435T variant in exon 26 of the MDR1 gene correlates to higher plasma concentrations of a P-glycoprotein substrate, dicloxacillin, and (2) the effects of genotypic differences decrease under conditions of P-glycoprotein induction by rifampin. Eighteen healthy volunteers received two 1-g doses of dicloxacillin, one on the 1st study day and the other on the 11th day of rifampin dosing (600 mg daily). Dicloxacillin and its 5-hydroxymethyl metabolite were analyzed using liquid chromatography/tandem mass spectrometry. Mean dicloxacillin C(max) measurements were 30.5 +/- 13.5, 33.3 +/- 4.7, and 31.1 +/- 12.8 mug/mL in individuals with the CC, CT, and TT genotype at position 3435 in exon 26 of the MDR1 gene. Following rifampin dosing, the mean dicloxacillin C(max) across genotypes decreased from 31.4 +/- 10.8 to 22.9 +/- 7.0 microg/mL (P < .05), whereas the mean oral clearance increased from 235 +/- 82 to 297 +/- 71 mL/min (P < .001), and the mean absorption time increased from 0.71 +/- 0.55 to 1.34 +/- 0.77 h (P < .05). Rifampin treatment increased the formation clearance, C(max), and AUC of the 5-hydroxymethyl metabolite by 135%, 119%, and 59%, respectively. The C3435T variant had no effect on dicloxacillin pharmacokinetics. The data suggested that rifampin induced intestinal P-glycoprotein and increased dicloxacillin metabolism. [ABSTRACT FROM AUTHOR]

Cyclosporine (CyA) is an immunosuppressant metabolized primarily by the liver and small intestine. The pharmacokinetics (PK) of CyA-were studied in 6 patients prior to and 1 to 3 months after liver transplantation (tx). Sixteen blood samples were collected over 24 hours following a 2-3 mg/kg intravenous dose of CyA. PK parameters, presented as mean +/- SD, were estimated using noncompartmental techniques. Pre-tx AUCs (14,540 +/- 5200 micrograms.h/L) were found to be significantly higher than during the post-tx phase (8120 +/- 2870 micrograms.h/L, p = 0.04). CyA clearance values were lower pre-tx as compared to post-tx (0.21 +/- 0.06 L/h/kg vs. 0.38 +/- 0.14 L/h/kg, respectively). There was no change in volume of distribution. End-stage liver disease can markedly decrease hepatic clearance of CyA relative to patients with stable hepatic function post-liver tx. The degree of impairment in clearance is not consistent or predictable based on liver function tests. [ABSTRACT FROM AUTHOR]

When a new molecular entity is predicted to exhibit high clearance in humans, pharmaceutical sponsors almost universally search for similar acting back-up compounds that will demonstrate low clearance. Here we show that, except for oral dosing, there can be marked advantages to developing and commercializing controlled release formulations of high clearance drugs, the expertise of readers of this journal. Our recent publications demonstrate that the universally held pharmacokinetic principle that drug delivery rate has no effect on measured drug clearance is not correct. Rather, we show that if clearance from the drug delivery site is markedly less than the iv bolus clearance of a drug, the in vivo drug clearance can be the drug delivery clearance controlled by the designed dosage form. This approach will be especially advantageous for high hepatic clearance drugs. These advantages include not being concerned with: a) saturable nonlinear kinetics, b) significant pharmacogenomic differences, c) drug-drug induction mechanisms, and d) in many cases drug-drug inhibition interactions. This is due to the ability of a drug sponsor to design clearance, independent of the pharmacokinetic characteristics for high clearance compounds, where clearance from the dosage form becomes the drug clearance from the patient. Recognition of this principle, as described here, results from our development of the use of Kirchhoff's Laws from physics to derive rate-defining clearance and rate constant elimination processes independent of differential equation derivations. The key message for readers of this journal is that high clearance drugs are potentially drugable through formulation design and should not be outright disregarded, since for such drugs the dose-corrected area under the curve can be increased if the release rate from the injection site is controlled and slow resulting in drug clearance from the body controlled by clearance from the dosage form. The concepts presented here describe previously unrecognized advantages of controlled release formulations., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Recently, we have proposed simple methodology to derive clearance and rate constant equations, independent of differential equations, based on Kirchhoff's Laws, a common methodology from physics used to describe rate-defining processes either in series or parallel. Our approach has been challenged in three recent publications, two published in this journal, but notably what is lacking is that none evaluate experimental pharmacokinetic data. As reviewed here, manuscripts from our laboratory have evaluated published experimental data, demonstrating that the Kirchhoff's Laws approach explains (1) why all of the experimental perfused liver clearance data appear to fit the equation that was previously believed to be the well-stirred model, (2) why linear pharmacokinetic systemic bioavailability determinations can be greater than 1, (3) why renal clearance can be a function of drug input processes, and (4) why statistically different bioavailability measures may be found for urinary excretion versus systemic concentration measurements. Our most recent paper demonstrates (5) how the universally accepted steady-state clearance approach used by the field for the past 50 years leads to unrealistic outcomes concerning the relationship between liver-to-blood Kp uu and hepatic availability F H , highlighting the potential for errors in pharmacokinetic evaluations based on differential equations. The Kirchhoff's Laws approach is applicable to all pharmacokinetic analyses of quality experimental data, those that were previously adequately explained with present pharmacokinetic theory, and those that were not . The publications that have attempted to rebut our position do not address unexplained experimental data, and we show here why their analyses are not valid. SIGNIFICANCE STATEMENT: The Kirchhoff's Laws approach to deriving clearance equations for linear systems in parallel or in series, independent of differential equations, successfully describes published pharmacokinetic data that has previously been unexplained. Three recent publications claim to refute our proposed methodology; these publications only make theoretical arguments, do not evaluate experimental data, and never demonstrate that the Kirchhoff methodology provides incorrect interpretations of experimental pharmacokinetic data, including statistically significant data not explained by present pharmacokinetic theory. We demonstrate why these analyses are invalid., (Copyright © 2024 by The Author(s).)

Here we present, utilizing universally accepted relationships for hepatic clearance at steady state, that for all models of hepatic elimination the ratio of unbound liver drug concentration to unbound systemic blood concentration, Kp uu , is a function of or related to the hepatic bioavailability for that drug, F H . According to the derivation for the well-stirred model, Kp uu can never exceed unity, can frequently be a function of hepatic blood flow, and is equivalent to the value of F H as determined following oral dosing. For the parallel tube model, Kp uu will not equal F H but will be a function of F H and will also never be a value greater than 1. When hepatic clearance is rate limited by basolateral transporters, Kp uu will be less than 1, and less than F H . We believe that such outcomes are highly unlikely, and that the error arises from a basic assumption concerning hepatic clearance that leads to the mechanistic models of hepatic elimination, the well-stirred, parallel tube and dispersion models. That basic assumption is that the steady-state systemic concentration multiplied by the hepatic systemic clearance is equal to the product of the average unbound liver steady-state concentration and the intrinsic hepatic clearance (C ss · CL = C H,u · CL int ). Calculations of Kp uu and F H based on present methods of analysis provide a strong argument as to why this universally accepted relationship is not correct. Alternatively, we have shown in recent publications that hepatic clearance may be adequately determined based on Kirchhoff's Laws where no assumption of the above equality concerning hepatic intrinsic clearance is required, and where Kp uu is independent of hepatic extraction ratio and F H ., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

It is generally believed that bioavailability (F) calculated based on systemic concentration area under the curve (AUC) measurements cannot exceed 1.0, yet some published studies report this inconsistency. We teach and believe, based on differential equation derivations, that rate of absorption has no influence on measured systemic clearance following an oral dose, i.e., determined as available dose divided by AUC. Previously, it was thought that any difference in calculating F from urine data versus that from systemic concentration AUC data was due to the inability to accurately measure urine data. A PubMed literature search for drugs exhibiting F > 1.0 and studies for which F was measured using both AUC and urinary excretion dose-corrected analyses yielded data for 35 drugs. We show and explain, using Kirchhoff's Laws, that these universally held concepts concerning bioavailability may not be valid in all situations. Bioavailability, determined using systemic concentration measurements, for many drugs may be overestimated since AUC reflects not only systemic elimination but also absorption rate characteristics, which is most easily seen for renal clearance measures. Clearance of drug from the absorption site must be significantly greater than clearance following an iv bolus dose for F(AUC) to correctly correspond with F(urine). The primary purpose of this paper is to demonstrate that studies resulting in F > 1.0 and/or greater systemic vs urine bioavailability predictions may be accurate. Importantly, these explications have no significant impact on current regulatory guidance for bioequivalence testing, nor on the use of exposure (AUC) measures in making drug dosing decisions., (© 2024. The Author(s).)

Here I detail the use of measures of permeability rate and solubility in predicting drug disposition characteristics through the utilization of the Biopharmaceutics Drug Disposition Classification System (BDDCS) and the Extended Clearance Classification System (ECCS) as well as the accuracy of the systems in predicting the major route of elimination and the extent of oral absorption of a new small molecule therapeutics. I compare the BDDCS and ECCS with the FDA Biopharmaceutics Classification System (BCS). I also detail the use of the BCS in predicting food effects and the BDDCS in predicting brain disposition of small molecule therapeutics and in validating DILI predictive metrics. This review provides an update of the current status of these classification systems and their uses in the drug development process., Competing Interests: Declaration of Competing Interest The author declares that he has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 American Pharmacists Association. Published by Elsevier Inc. All rights reserved.)

In chemistry, rate processes are defined in terms of rate constants, with units of time -1 , and are derived by differential equations from amounts. In contrast, when considering drug concentrations in biological systems, particularly in humans, rate processes must be defined in terms of clearance, with units of volume/time, since biological volumes, which are highly dependent on drug partition into biological tissues, cannot be easily determined. In pharmacology, pharmacokinetics, and in making drug dosing decisions, drug clearance and changes in drug clearance are paramount. Clearance is defined as the amount of drug eliminated or moved divided by the exposure driving that elimination or movement. Historically, all clearance derivations in pharmacology and pharmacokinetics have been based on the use of differential equations in terms of rate constants and amounts, which are then converted into clearance equations when multiplied/divided by a hypothesized volume of distribution. Here, we show that except for iv bolus dosing, multiple volumes may be relevant. We have recently shown that clearance relationships, as well as rate constant relationships, may be derived independent of differential equations using Kirchhoff's Laws from physics. Kirchhoff's Laws may be simply translated to recognize that when two or more rate-defining processes operate in parallel, the total value of the overall reaction parameter is equal to the sum of those rate-defining processes. In contrast, when two or more rate-defining processes operate in series, the inverse of the total reaction parameter is equal to the sum of the inverse of those rate-defining steps., (© 2023. The Author(s).)

The objective of this study was to determine the potential usefulness of an animal model to predict the appropriate dose of newly developed drugs for treating relapsing remitting multiple sclerosis (RRMS). Conversion of the lowest effective dose (LEffD) for mice and rats in the experimental autoimmune encephalomyelitis (EAE) model was used to predict the human effective dose utilizing the body surface area correction factor found in the 2005 US Food and Drug Administration (FDA) Guidance for Industry in selecting safe starting doses for clinical trials. Predictions were also tested by comparison with doses estimated by scaling up the LEffD in the model by the human to animal clearance ratio. Although initial proof-of-concept studies of oral fingolimod tested the efficacy and safety of 1.25 and 5 mg in treating RRMS, the EAE animal model predicted the approved dose of this drug, 0.5 mg daily. This approach would have also provided useful predictions of the approved human oral doses for cladribine, dimethyl fumarate, ozanimod, ponesimod, siponimod, and teriflunomide, drugs developed with more than one supposed mechanism of action. The procedure was not useful for i.v. dosed drugs, including monoclonal antibodies. We maintain that drug development scientists should always examine a simple allometric method to predict the therapeutic effective dose in humans. Then, following clinical studies, we believe that the animal model might be expected to yield useful predictions of other drugs developed to treat the same condition. The methodology may not always be predictive, but the approach is so simple it should be investigated., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Dosing rate decisions for drugs and changes in dosing in a patient due to disease states, drug interactions and pharmacogenomics are all based on clearance, a measure of the body's ability to eliminate drug. The primary organs of elimination are the liver and the kidney. Clearance for each of these organs is a summative composition of biologic processes. In 1857, Gustav Kirchhoff first developed his laws to describe the "motion of electricity in conductors... [and] ...in wires", recognizing that summative processes occur either in parallel or in series. Since then, Kirchhoff's Laws have also been applied to heat transfer, diffusion and drag force on falling objects, but not to pharmacology. Although not previously recognized, renal clearance always follow Kirchhoff's Laws, as does hepatic clearance for drugs where basolateral transporters are not clinically relevant. However, when basolateral transporters are clinically relevant, we demonstrate that the present accepted approach is inconsistent with recognized drug disposition processes. However, this clearance relationship can be easily corrected using Kirchhoff's Laws. The purpose of this review is to demonstrate that Kirchhoff's Laws, which define how to approach rate processes that occur in parallel versus processes that occur in series, can be applicable to pharmacology in addition to the over 160-year recognition of their use in physical sciences. We anticipate that the application to clearance will be only the first of many such pharmacological analyses., Competing Interests: Declaration of Competing Interest The authors declare that there are no conflicts of interest., (Copyright © 2022 Elsevier Inc. All rights reserved.)

For a number of years, our laboratory has been investigating the underlying reasons for the published poor in vitro-in vivo extrapolation (IVIVE) predictability of human clearance both from a theoretical and from an experimental perspective. Here, we critically examine clearance concepts and commonly employed IVIVE approaches, concluding that there is no theoretical reason that IVIVE should work, just as it does not. Our analysis, however, has identified 10 misconceptions and/or poorly understood aspects of clearance that are listed in the Conclusion section of this manuscript. Chief among these are that all published human drug clearance values are arterial clearances-clearance calculated as organ blood flow multiplied by the extraction ratio is the arterial clearance of the organ of elimination (and not the published drug clearance value)-and that the well-stirred model equation taught in all pharmacokinetic courses that relates organ blood flow, fraction unbound in blood, and intrinsic clearance has no validity. We further list 10 conclusions relating to the IVIVE process. The primary IVIVE-related conclusions are that the intrinsic clearance value determined from an in vitro incubation is an arterial intrinsic clearance, there is no theoretical basis upon which an arterial intrinsic clearance can be related to a whole-body arterial clearance to accomplish IVIVE, there are no published data demonstrating that in vitro intrinsic metabolic clearance can predict in vivo organ clearance as IVIVE assumes, and the scientific basis for the hypothesized albumin-mediated hepatic uptake phenomenon is invalid. We further propose three IVIVE process recommendations., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

The Biopharmaceutics Drug Disposition Classification system (BDDCS) is a four-class approach based on water solubility and extent of metabolism/permeability rate. Based on the BDDCS class to which a drug is assigned, it is possible to predict the role of metabolic enzymes and transporters on the drug disposition of a new molecular entity (NME) prior to its administration to animals or humans. Here, we report a total of 1475 drugs and active metabolites to which the BDDCS is applied. Of these, 379 are new entries, and 1096 are revisions of former classification studies with the addition of references for the approved maximum dose strength, extent of the systemically available drug excreted unchanged in the urine, and lowest solubility over the pH range 1.0-6.8 when such information is available in the literature. We detail revised class assignments of previously misclassified drugs and the literature analyses to classify new drugs. We review the process of solubility assessment for NMEs prior to drug dosing in humans and approved dose classification, as well as the comparison of Biopharmaceutics Classification System (BCS) versus BDDCS assignment. We detail the uses of BDDCS in predicting, prior to dosing animals or humans, disposition characteristics, potential brain penetration, food effect, and drug-induced liver injury (DILI) potential. This work provides an update on the current status of the BDDCS and its uses in the drug development process., (© 2022. The Author(s).)

Purpose: Previous studies evaluating ticagrelor drug-drug interactions have not differentiated intestinal versus systemic mechanisms, which we do here., Methods: Using recently published methodologies from our laboratory to differentiate metabolic- from transporter-mediated drug-drug interactions, a critical evaluation of five published ticagrelor drug-drug interactions was carried out to investigate the purported clinical significance of enzymes and transporters in ticagrelor disposition., Results: The suggested CYP3A4 inhibitors, ketoconazole and diltiazem, displayed unchanged mean absorption time (MAT) and time of maximum concentration (T max ) values as was expected, i.e., the interactions were mainly mediated by metabolic enzymes. The potential CYP3A4/P-gp inhibitor cyclosporine also showed an unchanged MAT value. Further analysis assuming there was no P-gp effect suggested that the increased AUC and unchanged t 1/2 for ticagrelor after cyclosporine administration were attributed to the inhibition of intestinal CYP3A4 rather than P-gp. Rifampin, an inducer of CYP3As after multiple dosing, unexpectedly showed decreased MAT and T max values, which cannot be completely explained. In contrast, grapefruit juice, an intestinal CYP3A/P-gp/OATP inhibitor, significantly increased MAT and T max values for ticagrelor, which may be due to activation of P-gp or inhibition of OATPs expressed in intestine., Conclusions: This study provides new insight into the role of transporter pathways in ticagrelor intestinal absorption by examining potential MAT and T max changes mediated by drug-drug interactions., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Pharmacokinetic differences between manufacturing batches, well established for inhaled drug products, preclude control of patient risk in the customary two-way (single batch) pharmacokinetic bioequivalence crossover design if batches are randomly chosen. European regulators have recommended selecting a "typical" in vitro batch to represent each product in pharmacokinetic bioequivalence testing. We explored the feasibility of this approach to control patient risk (the "false equivalence", or Type I, error rate). The probability of achieving a Test/Reference 90% confidence interval within (0.80, 1.25) for a true (non-equivalent) value of 1.25 was simulated for a two-way crossover design using the median in vitro batch across a range of number of in vitro batches, in vitro/in vivo correlation (IVIVC) quality (correlation coefficient, r, of zero to one), and within-subject between-batch pharmacokinetic variability. Even under extremely optimistic conditions, e.g., r=0.95 and >100 batches per product screened in vitro, patient risk for typical between-batch variability levels remained at least threefold higher than the 5% regulatory expectation for the significance level (the false equivalence error rate) of the pharmacokinetic bioequivalence test. This elevated error rate in bioequivalence decision-making occurs because of incomplete confidence that the true product average has been identified, and, importantly, omission of this uncertainty from the bioequivalence confidence interval., (© 2021. American Association of Pharmaceutical Scientists.)

The objective of this study was to determine the effects of the OATP inhibitor rifampin on pharmacokinetic of Biopharmaceutics Drug Disposition Classification System Class 1 compound fluvastatin. A crossover study was carried out in 10 healthy subjects who were randomized to 2 phases to receive fluvastatin 20 mg orally alone and following a 30-minute 600 mg i.v. infusion of rifampin. The results demonstrated that i.v. rifampin increased the mean area under the plasma fluvastatin concentration-time curve (AUC 0-∞ ) by 255%, mean peak plasma concentration (C max ) by 254%, decreased oral volume of distribution by 71%, whereas the mean elimination terminal half-life (T 1/2 ), mean absorption time (MAT), and time to peak concentration (T peak ) of fluvastatin did not significantly change. The study demonstrated that rifampin exhibited a significant drug interaction with fluvastatin. The mechanism of the increased plasma concentrations is likely due to inhibition of OATP transporters in hepatocytes., (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)

Tenofovir disoproxil fumarate (TDF) in combination with emtricitabine (FTC) is the backbone for both human immunodeficiency virus (HIV) treatment and pre-exposure prophylaxis (PrEP) worldwide. Tenofovir alafenamide (TAF) with FTC is increasingly used in HIV treatment and was recently approved for PrEP among men-who-have-sex-with-men. TDF and TAF are both metabolized into tenofovir (TFV). Antiretrovirals in plasma are taken up into hair over time, with hair levels providing a long-term measure of adherence. Here, we report a simple, robust, highly sensitive, and validated high-performance liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS)-based analytical method for analyzing TFV and FTC from individuals on either TDF/FTC or TAF/FTC in small hair samples. TFV/FTC are extracted from ~5 mg hair and separated on a column using a gradient elution. The lower quantification limits are 0.00200 (TFV) and 0.0200 (FTC) ng/mg hair; the assay is linear up to 0.400 (TFV) and 4.00 (FTC) ng/mg hair. The intra-day and inter-day coefficients of variance (CVs) are 5.39-12.6% and 6.40-13.5% for TFV and 0.571-2.45% and 2.45-5.16% for FTC. TFV concentrations from participants on TDF/FTC-based regimens with undetectable plasma HIV RNA were 0.0525 ± 0.0295 ng/mg, whereas those from individuals on TAF/FTC-based regimens were 0.0426 ± 0.0246 ng/mg. Despite the dose of TFV in TDF being 10 times that of TAF, hair concentrations of TFV were not significantly different for those on TDF versus TAF regimens. Pharmacological enhancers (ritonavir and cobicistat) did not boost TFV concentrations in hair. In summary, we developed and validated a sensitive analytical method to analyze TFV and FTC in hair and found that hair concentrations of TFV were essentially equivalent among those on TDF and TAF., (© 2021 John Wiley & Sons, Ltd.)

Purpose: A dataset of fraction excreted unchanged in the urine (fe) values was developed and used to evaluate the ability of preclinical animal species to predict high urinary excretion, and corresponding poor metabolism, in humans., Methods: A literature review of fe values in rats, dogs, and monkeys was conducted for all Biopharmaceutics Drug Disposition Classification System (BDDCS) Class 3 and 4 drugs (n=352) and a set of Class 1 and 2 drugs (n=80). The final dataset consisted of 202 total fe values for 135 unique drugs. Human and animal data were compared through correlations, two-fold analysis, and binary classifications of high (fe ≥30%) versus low (<30%) urinary excretion in humans. Receiver Operating Characteristic curves were plotted to optimize animal fe thresholds., Results: Significant correlations were found between fe values for each animal species and human fe (p<0.05). Sixty-five percent of all fe values were within two-fold of human fe with animals more likely to underpredict human urinary excretion as opposed to overpredict. Dogs were the most reliable predictors of human fe of the three animal species examined with 72% of fe values within two-fold of human fe and the greatest accuracy in predicting human fe ≥30%. ROC determined thresholds of ≥25% in rats, ≥19% in dogs, and ≥10% in monkeys had improved accuracies in predicting human fe of ≥30%., Conclusions: Drugs with high urinary excretion in animals are likely to have high urinary excretion in humans. Animal models tend to underpredict the urinary excretion of unchanged drug in humans., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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.

Purpose: The involvement of the intestinally expressed xenobiotic transporters P-glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) have been implicated in rivaroxaban disposition based on in vitro studies, similar to what had previously been proposed for apixaban. We recently showed that these efflux transporters were not clinically relevant for apixaban disposition and examine here their relevance for this second Factor Xa inhibitor., Methods: Using recently published methodologies to discern metabolic- from transporter- mediated drug interactions, a critical evaluation was undertaken of 9 rivaroxaban studies reporting 12 DDIs, one study of food effects and one study of hepatic function., Results: Rationale examination of these clinical studies using basic pharmacokinetic theory finds little support for the clinical significance of intestinal efflux transporters in rivaroxaban disposition. Drug-drug interactions are most likely adequately predicted based on the level of CYP 3A metabolism., Conclusion: These analyses indicate that inhibition of efflux transporters appears to have negligible, clinically insignificant effects on the rivaroxaban absorption process, which is consistent with the concern that predictions based on in vitro measures may not translate to a clinically relevant interaction in vivo. We emphasize the need to evaluate gastric emptying, dissolution and other processes related to absorption when using MAT changes to indicate efflux transporter inhibition.

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.

Introduction: It has been recognized that significant transporter interactions result in volume of distribution changes in addition to potential changes in clearance. For drugs that are not clinically significant transporter substrates, it is expected that drug-drug interactions would not result in any changes in volume of distribution., Methods: An evaluation of this hypothesis proceeded via an extensive analysis of published intravenous metabolic drug-drug interactions, based on clinically recommended index substrates and inhibitors of major cytochrome P450 (CYP) isoforms., Results: Seventy-two metabolic drug interaction studies were identified where volume of distribution at steady-state (V ss ) values were available for the CYP index substrates caffeine (CYP1A2), metoprolol (CYP2D6), midazolam (CYP3A4), theophylline (CYP1A2), and tolbutamide (CYP2C9). Changes in exposure (area under the curve) up to 5.1-fold were observed; however, ratios of V ss changes have a range of 0.70-1.26, with one outlier displaying a V ss ratio of 0.57., Discussion: These results support the widely held founding tenant of pharmacokinetics that clearance and V ss are independent parameters. Knowledge that V ss is unchanged in metabolic drug-drug interactions can be helpful in discriminating changes in clearance from changes in bioavailability (F) when only oral dosing data are available, as we have recently demonstrated. As V ss remains unchanged for intravenous metabolic drug-drug interactions, following oral dosing changes in V ss /F will reflect changes in F alone. This estimation of F change can subsequently be utilized to assess changes in clearance alone from calculations of apparent clearance. Utilization of this simple methodology for orally dosed drugs will have a significant impact on how drug-drug interactions are interpreted from drug development and regulatory perspectives.

Passive permeability is a key property in drug disposition and delivery. It is critical for gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance mechanisms and drug-drug interactions. Passive diffusion rate is translatable across tissues and animal species, while the extent of absorption is dependent on drug properties, as well as in vivo physiology/pathophysiology. Design principles have been developed to guide medicinal chemistry to enhance absorption, which combine the balance of aqueous solubility, permeability and the sometimes unfavorable compound characteristic demanded by the target. Permeability assays have been implemented that enable rapid development of structure-permeability relationships for absorption improvement. Future advances in assay development to reduce nonspecific binding and improve mass balance will enable more accurately measurement of passive permeability. Design principles that integrate potency, selectivity, passive permeability and other ADMET properties facilitate rapid advancement of successful drug candidates to patients., (© 2020 Wiley-VCH GmbH.)

Purpose: The involvement of the intestinally expressed xenobiotic transporters P-glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) have been implicated in apixaban disposition based on in vitro studies. Recommendations against co-administration of apixaban with inhibitors of these efflux transporters can be found throughout the literature as well as in the apixaban FDA label. However, the clinical relevance of such findings is questionable due to the high permeability and high solubility characteristics of apixaban., Methods: Using recently published methodologies to discern metabolic- from transporter- mediated drug-drug interactions, a critical evaluation of all published apixaban drug-drug interaction studies was conducted to investigate the purported clinical significance of efflux transporters in apixaban disposition., Results: Rational examination of these clinical studies using basic pharmacokinetic theory does not support the clinical significance of intestinal efflux transporters in apixaban disposition. Further, there is little evidence that efflux transporters are clinically significant determinants of systemic clearance., Conclusions: Inhibition or induction of intestinal CYP3A4 can account for exposure changes of apixaban in all clinically significant drug-drug interactions, and lack of intestinal CYP3A4 inhibition can explain all studies with no exposure changes, regardless of the potential for these perpetrators to inhibit intestinal or systemic efflux transporters.

Extensive studies have been conducted to predict in vivo metabolic clearance from in vitro human liver metabolism parameters (i.e., in vitro-in vivo extrapolation (IVIVE)) with little success. Here, deriving IVIVE from first principles, we show that the product of fraction unbound in the blood and the predicted in vivo intrinsic clearance determined from hepatocyte or microsomal incubations is the lower boundary condition for in vivo hepatic clearance and the prerequisite for IVIVE predictions to be valid, regardless of extraction ratio. For 60-80% of drugs evaluated here, this product is markedly less than the in vivo measured clearance, a result that violates the lower boundary of the predictive relationship. This can only be explained by (a) suboptimal in vitro metabolic stability assay conditions, (b) significant error in the assumption that in vitro intrinsic clearance determinations will predict in vivo intrinsic clearance simply by scaling-up the amount of enzyme (in vitro incubation to in vivo liver), and/or (c) the methods of determining fraction unbound are incorrect. We further suggest that widely employed organ blood flow values underpredict the effective blood flow within the organ by approximately 2.5-fold, thus impacting IVIVE of high clearance compounds. We propose future pathways that should be investigated in terms of the relationship to experimentally measured clearance values, rather than model-dependent intrinsic clearance. IVIVE outcome can be improved by estimating the ratio of unbound drug concentration in the liver tissue to the liver plasma, examining the assumption of the free drug theory (i.e., there are no transporter effects at the blood cell membrane) and the finding that the upper limit of organ clearance may be greater than blood flow entering the organ.

Introduction: In drug discovery and development, it is of high interest to characterize the potential for intestinal drug-drug interactions to alter bioavailability of a victim drug. For drugs that are substrates of both intestinal transporters and enzymes, estimating the relative contribution of each process has proved challenging, especially since the susceptibility of drug to uptake or efflux transporters in vitro does not always translate to clinically significant in vivo involvement. Here we introduce a powerful methodology to implicate intestinal transporters in drug-drug interactions based on the theory that clinically relevant intestinal transporter interactions will result in altered rate of absorption of victim drugs., Methods and Materials: We present exemplary clinical drug-drug interaction studies that utilize well-characterized clinical substrates and perpetrators to demonstrate how mean absorption time (MAT) and time to maximum concentration (t max ) are expected to change (or remain unchanged) when either intestinal transporters or metabolic enzymes were/are altered. Apixaban was also selected to demonstrate the utility of the methodology, as the purported involvement of both intestinal enzymes and transporters has been suggested in its FDA package insert., Results and Discussion: Acute inhibition of gut efflux transporters resulted in decreased MAT and t max values, induction increased these values, while inhibition of intestinal metabolic enzymes did not result in altered MAT or t max . Involvement of intestinal efflux transporters in apixaban disposition is unlikely., Conclusion: Utilization of this simple but powerful methodology to implicate intestinal transporter involvement will have significant impact on how drug-drug interactions are interpreted.

Accurately discriminating changes in clearance (CL) from changes in bioavailability (F) following an oral drug-drug interaction is difficult without carrying out an intravenous interaction study. This may be true for drugs that are clinically significant transporter substrates; however, for interactions that are strictly metabolic, it has been recognized that volume of distribution remains unchanged between both phases of the interaction study. With the understanding that changes in volume of distribution will be minimal for metabolized drugs, the inverse of the change in apparent volume of distribution can provide adequate estimates of the change in bioavailability alone. Utilization of this estimate of F change in tandem with the observed apparent clearance (CL/F) change in an oral drug-drug interaction can provide an estimate of the change in clearance alone. Here, we examine drug-drug interactions involving five known inhibitors and inducers of cytochrome P450 3A4 isozyme on victim drugs midazolam and apixaban for which the interaction was carried out both orally and intravenously, allowing for evaluation of this methodology. Predictions of CL and F changes based on oral data were reasonably close to observed changes based on intravenous studies, demonstrating that this simple yet powerful methodology can reasonably differentiate changes in F from changes in CL for oral metabolic drug interactions when only oral data are available. Utilization of this relatively simple methodology to evaluate DDIs for orally dosed drugs will have a significant impact on how DDIs are interpreted from a drug development and regulatory perspective., (© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.)