Skip to main content
eScholarship
Open Access Publications from the University of California

Scholarly Works (25 results)

  • Article
  • Peer Reviewed
UC San Francisco Previously Published Works (2020)
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.
    Cover page: Investigating the Theoretical Basis for In Vitro–In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways
    • Thesis
    • Peer Reviewed
    UC San Francisco Electronic Theses and Dissertations (2020)

    Complex drug-drug interactions are defined as those in which both metabolic enzymes and xenobiotic transporters are implicated as clinically significant determinants of drug disposition. Both metabolic enzymes and xenobiotic transporters have the potential to contribute to clearance pathways (i.e. metabolic, renal or biliary elimination) and bioavailability-related processes (i.e. drug absorption, intestinal metabolism, or first pass hepatic elimination). Transporters have the unique ability to influence the distribution of drug throughout the body, in addition to influencing intestinal drug absorption or drug clearance via renal or biliary routes. Thus, characterization of the contributions of metabolic enzymes and xenobiotic transporters is crucial in anticipating any potential alterations in drug exposure due to a drug-drug interaction, pharmacogenomic or disease state variance of activity or expression of relevant metabolic enzymes or transporters.

    Predictions of drug-drug interactions are routinely conducted based on results of in vitro metabolic enzyme or xenobiotic transporter inhibition studies. However, translating such results to clinical significance continues to challenge the field, particularly for transporter-mediated interactions since the susceptibility of a drug to transporters in vitro does not always translate to clinically significant in vivo involvement and due to a lack of specific and clinically validated index substrates, inhibitors and inducers for major xenobiotic transporters. The objective of this research was to provide a framework for recognizing transporter involvement in clinical drug-drug interactions, grounded in basic pharmacokinetic theory.

    Since xenobiotic transporters can allow (or disallow) substrates access to various tissues throughout the body, it was recognized that significant xenobiotic transporter interactions are accompanied by changes in volume of distribution, in addition to potential changes in clearance, which can result in counterintuitive changes in mean residence time and terminal half-life. Metabolic interactions are not expected to result in any volume of distribution changes and this hypothesis was extensively evaluated via examination of 72 intravenous metabolic drug-drug interaction studies with clinically recommended index substrates and inhibitors. The results indicate that volume of distribution is almost always unchanged in strictly metabolic interactions with marked exposure changes, resulting in changes in mean residence time and half-life that are equal but opposite to clearance changes, further highlighting that volume and clearance are indeed independent parameters.

    Understanding that metabolic interactions do not result in volume of distribution changes can allow for estimation of bioavailability changes in oral drug-drug interactions, where the extent of change in apparent volume of distribution will reflect changes in bioavailability alone due to unchanged volume of distribution. Such estimates of changes in bioavailability can subsequently be utilized to differentiate changes in clearance alone from measures of apparent clearance following oral dosing. This approach can also be utilized to predict if an overall exposure change for oral drug-drug interactions is primarily due to changes in systemic clearance versus bioavailability.

    To identify clinically significant intestinal transporter interactions, it was demonstrated that alteration of intestinal transporter activity or expression will result in significant changes in absorption rate, and such changes should always be used to implicate transporter involvement in vivo. Inhibition of apical efflux transporters result in decreased absorption time, as efflux transporter-mediated drug cycling between the enterocyte and gut lumen is prevented, while efflux transporter induction results in prolonged absorption time, as reflected in values of mean absorption time and time to maximum concentration.

    Analyses of clinical data, such as examining changes in volume of distribution following intravenous dosing, changes in absorption rate following oral dosing, and examining the relationship between clearance changes and half-life and mean residence time changes, can confirm transporter involvement of purported complex drug-drug interactions. Such an approach was utilized to critically evaluate the purported clinical significance of the efflux transporters P-glycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) in the disposition of apixaban, as has been indicated throughout the literature and even on the apixaban FDA label. Rational examination of all published apixaban clinical drug-drug interaction studies, using the proposed basic clinical pharmacokinetic methodologies, does not support the clinical significance of the efflux transporters P-gp nor BCRP in apixaban disposition. In fact, inhibition or induction of intestinal metabolism via cytochrome P450 3A4 (CYP3A4) can account for all exposure changes of clinically significant drug-drug interactions, and lack of intestinal CYP3A4 inhibition can explain all studies with no exposure changes.

    Understanding the utility and limitations of experimental systems, as well as the inherent assumptions of the pharmacokinetic equations utilized to translate such results, is crucial in translating in vitro or in situ experimental information to an in vivo prediction of drug disposition. For instance, there is limited benefit to using measurements of unbound liver-to-blood partitioning (Kpuu) to improve predictions of drug-drug interactions, as DDIs can adequately be predicted by the Extended Clearance Model without any measurements of intracellular drug concentrations, a difficult task hindered by experimental variability. Further, the recognition that Kpuu has inherently assumed the well-stirred model implies that such approaches cannot account for the nuances of intracellular drug distribution. Finally, recognition that clearance calculations based on extraction ratio have inherently assumed the well-stirred model further highlights the importance of understanding the assumptions inherent in basic pharmacokinetic relationships that are universally utilized to characterize clinical drug disposition.

      Cover page: Identifying Xenobiotic Transporter Involvement in Complex Drug-Drug Interactions
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2023)
      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.
        Cover page: The Uses and Advantages of Kirchhoff’s Laws vs. Differential Equations in Pharmacology, Pharmacokinetics, and (Even) Chemistry
        • Article
        • Peer Reviewed
        UC San Francisco Previously Published Works (2020)
        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.
          Cover page: A Simple Methodology to Differentiate Changes in Bioavailability From Changes in Clearance Following Oral Dosing of Metabolized Drugs
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2020)
          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.
            Cover page: A Simple Methodology to Differentiate Changes in Bioavailability From Changes in Clearance Following Oral Dosing of Metabolized Drugs
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2022)
            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.
              Cover page: Can In Vitro–In Vivo Extrapolation Be Successful? Recognizing the Incorrect Clearance Assumptions
              • Article
              • Peer Reviewed
              UC San Francisco Previously Published Works (2020)

              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 (tmax) 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 tmaxvalues, induction increased these values, while inhibition of intestinal metabolic enzymes did not result in altered MAT or tmax. 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.
                Cover page: The Necessity of Using Changes in Absorption Time to Implicate Intestinal Transporter Involvement in Oral Drug-Drug Interactions
                • Article
                • Peer Reviewed
                UC San Francisco Previously Published Works (2021)
                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.
                  Cover page: Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization
                  • Article
                  • Peer Reviewed
                  UC San Francisco Previously Published Works (2024)
                  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 Kpuu and hepatic availability FH , 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.
                  • 1 supplemental PDF
                  • 1 supplemental ZIP
                  Cover page: Commentary Pharmacokinetic Theory Must Consider Published Experimental DataCreative Commons 'BY' version 4.0 license
                  • Article
                  • Peer Reviewed
                  UC San Francisco Previously Published Works (2024)
                    Cover page: For hepatically cleared drugs, liver to blood KPUU at steady-state is always equal to FH , which exposes the deficiency of the present extended clearance concept equationCreative Commons 'BY' version 4.0 license
                    Top