Are all measures of liver Kpuu a function of FH, as determined following oral dosing, or have we made a critical error in defining hepatic drug clearance?

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.

An Explanation of Why Dose-Corrected Area Under the Curve for Alternate Administration Routes Can Be Greater than for Intravenous Dosing

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.

Solubility-Permeability Interplay in Facilitating the Prediction of Drug Disposition Routes, Extent of Absorption, Food Effects, Brain Penetration and Drug Induced Liver Injury Potential

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.

The Uses and Advantages of Kirchhoff's Laws vs. Differential Equations in Pharmacology, Pharmacokinetics, and (Even) Chemistry

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.

Using an animal model to predict the effective human dose for oral multiple sclerosis drugs

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.

Review of the application of Kirchhoff's Laws of series and parallel flows to pharmacology: Defining organ clearance

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.

Does Addition of Protein to Hepatocyte or Microsomal In Vitro Incubations Provide a Useful Improvement in In Vitro-In Vivo Extrapolation Predictability?

Accurate prediction of in vivo hepatic clearance is an essential part of successful and efficient drug development; however, many investigators have recognized that there are significant limitations in the predictability of clearance with a tendency for underprediction for primarily metabolized drugs. Here, we examine the impact of adding serum or albumin into hepatocyte and microsomal incubations on the predictability of in vivo hepatic clearance. The addition of protein into hepatocyte incubations has been reported to improve the predictability for high clearance (extraction ratio) drugs and highly protein-bound drugs. Analyzing published data for 60 different drugs and 97 experimental comparisons (with 17 drugs being investigated from two to seven) we confirmed the marked underprediction of clearance. However, we could not validate any relevant improved predictability within twofold by the addition of serum to hepatocyte incubations or albumin to microsomal incubations. This was the case when investigating all measurements, or when subdividing analyses by extraction ratio, degree of protein binding, Biopharmaceutics Drug Disposition Classification System class, examining Extended Clearance Classification System class 1B drugs only, or drug charge. Manipulating characteristics of small data sets of like compounds and adding scaling factors can appear to yield good predictability, but the carryover of these methods to alternate drug classes and different laboratories is not evident. Improvement in predictability of poorly soluble compounds is greater than that for soluble compounds, but not to a meaningful extent. Overall, we cannot confirm that protein addition improves in vitro-in vivo extrapolation predictability to any clinically meaningful degree when considering all drugs and different subsets. SIGNIFICANCE STATEMENT: The addition of protein into microsomal or hepatocyte incubations has been widely proposed to improve hepatic clearance predictions. To date, studies examining this phenomenon have not included appropriate negative controls where predictability is achieved without protein addition and have been conducted with small data sets of similar compounds that don't apply to alternate drug classes. Here, an extensive analysis of published data for 60 drugs and 97 experimental comparisons couldn't validate any relevant clinically improved clearance predictability with protein addition.

State of the Art and Uses for the Biopharmaceutics Drug Disposition Classification System (BDDCS): New Additions, Revisions, and Citation References

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.

Analyzing Potential Intestinal Transporter Drug-Drug Interactions: Reevaluating Ticagrelor Interaction Studies

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.

Can In Vitro-In Vivo Extrapolation Be Successful? Recognizing the Incorrect Clearance Assumptions

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.

Batch Selection via In Vitro/In Vivo Correlation in Pharmacokinetic Bioequivalence Testing

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.

Effects of Single Dose Rifampin on the Pharmacokinetics of Fluvastatin in Healthy Volunteers

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 (AUC0-∞ ) by 255%, mean peak plasma concentration (Cmax ) by 254%, decreased oral volume of distribution by 71%, whereas the mean elimination terminal half-life (T1/2 ), mean absorption time (MAT), and time to peak concentration (Tpeak ) 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.

Examination of Urinary Excretion of Unchanged Drug in Humans and Preclinical Animal Models: Increasing the Predictability of Poor Metabolism in Humans

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.

Tenofovir and emtricitabine concentrations in hair are comparable between individuals on tenofovir disoproxil fumarate versus tenofovir alafenamide-based ART

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.

There is Only One Valid Definition of Clearance: Critical Examination of Clearance Concepts Reveals the Potential for Errors in Clinical Drug Dosing Decisions

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.

Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization

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.

Intestinal Efflux Transporters P-gp and BCRP Are Not Clinically Relevant in Apixaban Disposition

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.

Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways

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.

The Critical Role of Passive Permeability in Designing Successful Drugs

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.

The Necessity of Using Changes in Absorption Time to Implicate Intestinal Transporter Involvement in Oral Drug-Drug Interactions

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_maxvalues, 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.

Volume of Distribution is Unaffected by Metabolic Drug-Drug Interactions

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.

A Simple Methodology to Differentiate Changes in Bioavailability From Changes in Clearance Following Oral Dosing of Metabolized Drugs

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.

Are There Any Experimental Perfusion Data that Preferentially Support the Dispersion and Parallel-Tube Models over the Well-Stirred Model of Organ Elimination?

In reviewing previously published isolated perfused rat liver studies, we find no experimental data for high-clearance metabolized drugs that reasonably or unambiguously support preference for the dispersion and parallel-tube models versus the well-stirred model of organ elimination when only entering and exiting drug concentrations are available. It is likely that the investigators cited here may have been influenced by: 1) the unphysiologic aspects of the well-stirred model, which may have led them to undervalue the studies that directly test the various hepatic disposition models for high-clearance drugs (for which model differences are the greatest); 2) experimental assumptions made in the last century, which are no longer valid today, related to the predictability of in vivo outcomes from in vitro measures of drug elimination and the influence of albumin in hepatic drug uptake; and 3) a lack of critical review of previously reported experimental studies, resulting in inappropriate interpretation of the available experimental data. The number of papers investigating the theoretical aspects of the dispersion, parallel-tube, and well-stirred models of hepatic elimination greatly outnumber the papers that actually examine the experimental evidence available to substantiate these models. When all experimental studies that measure organ elimination using entering and exiting drug concentrations at steady state are critically reviewed, the simple but unphysiologic well-stirred model is the only model that can describe all trustworthy published available data. SIGNIFICANCE STATEMENT: Although the dispersion model of hepatic elimination more adequately reflects physiologic reality, there are no convincing experimental data that unambiguously favor this model. The well-stirred model can describe all well-designed perfusion studies with high-clearance drugs and nondrug substrates, but the field has not recognized this because of hesitation to accept a nonphysiologic model and flawed attempts to utilize in vitro-in vivo extrapolation approaches.

Challenging the Relevance of Unbound Tissue-to-Blood Partition Coefficient (Kpuu) on Prediction of Drug-Drug Interactions

PURPOSE

To examine the theoretical/practical utility of the liver-to-blood partition coefficient (Kp_uu) for predicting drug-drug interactions (DDIs), and compare the Kp_uu-approach to the extended clearance concept AUC_R-approach.

METHODS

The Kp_uu relationship was derived from first principles. Theoretical simulations investigated the impact of changes in a single hepatic-disposition process on unbound systemic (AUC_B,u) and hepatic exposure (AUC_H,u) versus Kp_uu. Practical aspects regarding Kp_uu utilization were examined by predicting the magnitude of DDI between ketoconazole and midazolam employing published ketoconazole Kp_uu values.

RESULTS

The Kp_uu hepatic-disposition relationship is based on the well-stirred model. Simulations emphasize that changes in influx/efflux intrinsic clearances result in Kp_uu changes, however AUC_H,u remains unchanged. Although incorporation of Kp_uu is believed to improve DDI-predictions, utilizing published ketoconazole Kp_uu values resulted in prediction errors for a midazolam DDI.

CONCLUSIONS

There is limited benefit in using Kp_uu for DDI-predictions as the AUC_R-based approach can reasonably predict DDIs without measurement of intracellular drug concentrations, a difficult task hindered by experimental variability. Further, Kp_uu changes can mislead as they may not correlate with changes in AUC_B,u or AUC_H,u. The well-stirred model basis of Kp_uu when applied to hepatic-disposition implies that nuances of intracellular drug distribution are not considered by the Kp_uu model.

Predicting Interactions between Rifampin and Antihypertensive Drugs Using the Biopharmaceutics Drug Disposition Classification System

STUDY OBJECTIVE

Lack of blood pressure control is often seen in hypertensive patients concomitantly taking antituberculosis medications due to the complex drug-drug interactions between rifampin and antihypertensive drugs. Therefore, it is of clinical importance to understand the underlying mechanisms of these interactions to help formulate recommendations on the use of antihypertensive drugs in patients taking these medications concomitantly. Our objective was to assess the reliability of the Biopharmaceutics Drug Disposition Classification System (BDDCS) to predict potential interactions between rifampin and antihypertensive drugs and thus provide recommendations on the choice of antihypertensive drugs in patients receiving rifampin.

DESIGN

Evidence-based in vitro and in vivo predictions of drug-drug interactions.

MEASUREMENTS AND MAIN RESULTS

We systematically evaluated interactions between rifampin and antihypertensive drugs using the theory of the BDDCS, taking into consideration the role of drug transporters and metabolic enzymes involved in these interactions. We provide recommendations on the selection of antihypertensive drugs for patients with tuberculosis. Antihypertensive drugs approved by the U.S. Food and Drug Administration and the China National Medical Products Administration were included in this study. The drugs were classified into four categories under the BDDCS classification. Detailed information on cytochrome P450 (CYP) enzymes and drug transporters for each antihypertensive drug was searched in PubMed and other electronic databases. This information was combined with the effects of rifampin on CYP enzymes and drug transporters, and the direction and relative extent of the potential interactions between rifampin and antihypertensive drugs were predicted. Recommendations were then made using the theory of BDDCS. A thorough systematic literature review was performed, and data from all published human studies and case reports were summarized for the validation of our predictions. Interventional and observational studies published in PubMed and two Chinese databases (CNKI and WanFang) through December 16, 2019, were included, and data were extracted for validation of the predictions. Using the BDDCS theory, class 3 active drugs were predicted to exhibit minimal interactions with rifampin. On reviewing case reports and pre-post studies, the predictions we made were found to be reliable. When antituberculosis medications that include rifampin are started in patients with hypertension, it is recommended that the use of calcium channel blockers and classes 1 and 2 β-blockers be avoided. Angiotensin-converting enzyme inhibitors, olmesartan, class 3 β-blockers, spironolactone, and hydrochlorothiazide would be preferable because clinically relevant interactions would not be expected.

CONCLUSION

Application of the BDDCS to predict interactions between rifampin and antihypertensive drugs for patients with both tuberculosis and hypertension was found to be reliable. It should be noted, however, that based on the CYP enzyme and drug transporter information we reviewed, the mechanisms of all of the interactions could not be elucidated, and the predictions are only based on theory. The real effects of rifampin on antihypertensive drugs need to be further observed. More studies in both animals and humans are needed in the future.

Can BDDCS illuminate targets in drug design?

The fact that pharmacokinetic (PK) properties of drugs influence their interaction with protein targets is a principle known for decades. The same cannot be said for the opposite, namely that targets influence the PK properties of drugs. Evidence confirming this possibility is introduced here for the first time, as we show that certain protein families have a clear preference for drugs with specific PK properties. We investigate this by cross-referencing 'druggable target' annotations for >1000 US Food and Drug Administration (FDA)-approved drugs with their PK profile, as defined by the Biopharmaceutics Drug Disposition Classification System (BDDCS) criteria, and then examine the BDDCS preference for several major target protein families and therapeutic categories. Our findings suggest a novel way to conduct drug discovery by focusing PK profiles at the very early stage of target selection.

Protein Binding and Hepatic Clearance: Re-Examining the Discrimination between Models of Hepatic Clearance with Diazepam in the Isolated Perfused Rat Liver Preparation

This study re-examined the hepatic extraction for diazepam, the only drug for which isolated perfused rat liver (IPRL) studies have been reported not to be consistent with the well stirred model of organ elimination when only entering and exiting liver concentration measurements are available. First, the time dependency of diazepam equilibrium fraction unbound measurements from 4 to 24 hours was tested, reporting the continuing increases with time. The results showed that the time dependency of equilibrium protein-binding measurements for very highly bound drugs may be an issue that is not readily overcome. When examining C _out/C _in (F _obs) measurements for diazepam when no protein is added to the incubation media, IPRL outcomes were consistent with previous reports showing marked underpredictability of in vivo clearance from in vitro measures of elimination in the absence of protein for very highly bound drugs, which is markedly diminished in the presence of albumin. F _obs for diazepam at additional low concentrations of protein that would allow discrimination of the models of hepatic elimination produced results that were not consistent with the dispersion and parallel-tube models. Therefore, although the outcomes of this study were similar to those reported by Rowland and co-workers, when no protein is added to the perfusion media, these IPRL results for diazepam cannot be reasonably interpreted as proving that hepatic organ elimination is model-independent or as supporting the dispersion and parallel-tube models of organ elimination. SIGNIFICANCE STATEMENT: The only drug experiments for which isolated perfusion rat liver studies do not support hepatic clearance being best described by the well stirred model have been carried out with diazepam at zero protein concentration. This study repeated those studies, confirming the previous results at zero protein concentration, but the addition of low protein-binding conditions capable of differentiating the various models of hepatic elimination are more consistent with the well stirred model of hepatic elimination. These experimental studies do not support the preference for alternate models of hepatic elimination or the proposal that hepatic organ clearance is model-independent.

In Vitro-In Vivo Inaccuracy: The CYP3A4 Anomaly

When predicting hepatic clearance using in vitro to in vivo extrapolation (IVIVE), microsomes or hepatocytes are commonly used. Here, we examine intrinsic clearance values and IVIVE results in human hepatocytes and microsomes for compounds metabolized by a variety of enzymes. The great majority of CYP3A4 substrates examined had higher intrinsic clearance values in microsomes compared with hepatocytes, whereas the values were more similar between the two incubations for substrates of other enzymes. We hypothesize that this may be due to interplay between CYP3A4 and the efflux transporter P-glycoprotein, as they have been shown to exhibit coordinated regulation. When examining the prediction accuracy for substrates of other enzymes between microsomes and hepatocytes, average fold errors as well as overall error were similar, demonstrating once again that IVIVE methods are not adequately defined and understood. SIGNIFICANCE STATEMENT: For CYP3A4 substrates, microsomes give markedly higher predictive in vitro to in vivo extrapolation than for other metabolic enzymes, which is not found for hepatocytes. We hypothesize that this could be a result of CYP3A4-P-glycoprotein interplay or coordinated regulation in hepatocytes that would not be observed in microsomes.

Food, Acid Supplementation and Drug Absorption - a Complicated Gastric Mix: a Randomized Control Trial

PURPOSE

The purpose of this study was to determine the impact of food on gastric pH and the ability of over the counter betaine hydrochloride (BHCl) acid to reacidify gastric pH after food-induced elevations in gastric pH.

METHODS

This open-label cross over clinical study (NCT02758015) included 9 subjects who were randomly assigned to one of 16 possible, 4-period cross-over sequences to determine the impact and relationship of food and gastric pH with acid supplementation. Subjects were administered various doses (1500 mg, 3000 mg and 4500 mg) of betaine hydrochloride (BHCl) to determine the ability of acid supplementation to reacidify gastric pH after the elevation of gastric pH caused by the ingestion of food.

RESULTS

Following the administration of food and the resulting elevation in gastric pH, time to return to baseline gastric pH levels without acid supplementation was 49.7 ± 14.0 min. Administering 4500 mg of BHCl acid in capsules was able to reacidify gastric pH levels back to baseline following the administration of food in approximately 17.3 ± 5.9 min. AUC_pH of each treatment were similar and not statistically different. Mean max pH following the administration of food was 3.20 ± 0.55.

CONCLUSION

The ability of food to elevate and maintain gastric pH levels in the presence of acid supplementation was made evident throughout the study. A 4500 mg dose of BHCl was required to reacidify gastric pH after the administration of food. This study details the difficulty faced by clinicians in dosing a poorly soluble, weakly basic drug to patients receiving acid reducing agents where administration with food is recommended to avoid gastric side effects.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT02758015.

How Transporters Have Changed Basic Pharmacokinetic Understanding

The emergence and continued evolution of the transporter field has caused re-evaluation and refinement of the original principles surrounding drug disposition. In this paper, we emphasize the impact that transporters can have on volume of distribution and how this can affect the other major pharmacokinetic parameters. When metabolic drug-drug interactions or pharmacogenomic variance changes the metabolism of a drug, the volume of distribution appears to be unchanged while clearance, bioavailability, and half-life are changed. When transporters are involved in the drug-drug interactions or pharmacogenomic variance, the volume of distribution can be markedly affected causing counterintuitive changes in half-life. Cases are examined where a volume of distribution change is significant enough that although clearance decreases, half-life decreases. Thus, drug dosing decisions must be made based on CL/F changes, not half-life changes, as such volume of distribution alterations will also influence the half-life results.

The Enhancement of Subcutaneous First-Pass Metabolism Causes Nonlinear Pharmacokinetics of TAK-448 after a Single Subcutaneous Administration to Rats

2-(N-acetyl-D-tyrosyl-trans-4-hydroxy-L-prolyl-L-asparaginyl-L-threonyl-L-phenylalanyl) hydrazinocarbonyl-L-leucyl-Nω-methyl-L-arginyl-L-tryptophanamide monoacetate (TAK-448, RVT-602), a kisspeptin analog, has been developed as a therapeutic agent for prostate cancer. The purpose of the present study is to clarify the mechanism of the less than dose-proportional nonlinear pharmacokinetics of TAK-448 after subcutaneous administration to rats. The plasma pharmacokinetics of TAK-448 and radiolabeled TAK-448 ([¹⁴C]TAK-448) were examined after subcutaneous and intravenous administrations to rats. [¹⁴C]TAK-448 was also subcutaneously injected together with protease inhibitors. The effects of the protease inhibitors on the in vitro metabolism of [¹⁴C]TAK-448 were investigated using rat skin homogenates. In a dose-ascending study, less than dose-proportional nonlinear pharmacokinetics were observed after subcutaneous administration with limited absorption of TAK-448 at the highest dose level contrary to the linear pharmacokinetics following intravenous dosing, indicating enhancement of subcutaneous metabolism with dose escalation. The systemic absorption of unchanged TAK-448 recovered when protease inhibitors were subcutaneously coadministered, suggested the involvement of subcutaneous proteases in the first-pass metabolism. An in vitro metabolism study suggests that serine protease could be responsible for the subcutaneous metabolism of TAK-448. Dose-dependent enhancement of first-pass metabolism appears to contribute to the less than dose-proportional nonlinear pharmacokinetics of TAK-448 after subcutaneous administrations to rats.

Interlaboratory Variability in Human Hepatocyte Intrinsic Clearance Values and Trends with Physicochemical Properties

PURPOSE

To examine the interlaboratory variability in CL_int values generated with human hepatocytes and determine trends in variability and clearance prediction accuracy using physicochemical and pharmacokinetic parameters.

METHODS

Data for 50 compounds from 14 papers were compiled with physicochemical and pharmacokinetic parameter values taken from various sources.

RESULTS

Coefficients of variation were as high as 99.8% for individual compounds and variation was not dependent on the number of prediction values included in the analysis. When examining median values, it appeared that compounds with a lower number of rotatable bonds had more variability. When examining prediction uniformity, those compounds with uniform in vivo underpredictions had higher CL_{int, in vivo} values, while those with non-uniform predictions typically had lower CL_{int, in vivo} values. Of the compounds with uniform predictions, only a small number were uniformly predicted accurately. Based on this limited dataset, less lipophilic, lower intrinsic clearance, and lower protein binding compounds yield more accurate clearance predictions.

CONCLUSIONS

Caution should be taken when compiling in vitro CL_int values from different laboratories as variations in experimental procedures (such as extent of shaking during incubation) may yield different predictions for the same compound. The majority of compounds with uniform in vitro values had predictions that were inaccurate, emphasizing the need for a better mechanistic understanding of IVIVE. The non-uniform predictions, often with low turnover compounds, reaffirmed the experimental challenges for drugs in this clearance range. Separating new chemical entities by lipophilicity, intrinsic clearance, and protein binding may help instill more confidence in IVIVE predictions.

Measures of BSEP Inhibition In Vitro Are Not Useful Predictors of DILI

Inhibition of the bile salt export pump (BSEP) by a drug has been implicated as a risk factor for a drug's potential to cause drug-induced liver injury (DILI) and is thought to be an important mechanism leading to DILI. For a wide variety of drugs a correlation has been observed between the potency of in vitro BSEP inhibition and its propensity to cause DILI in humans. These findings were interpreted to suggest that BSEP inhibition could be an important mechanism to help explain how some drugs initiate DILI. Because the Biopharmaceutics Drug Disposition Classification System (BDDCS) can be useful in characterizing and predicting some important transporter effects in terms of drug-drug interactions, we evaluated the information provided by BDDCS in order to understand the inhibition propensity of BSEP. Here we analyze the relationship between a compound's ability to inhibit BSEP function and cause liver injury in humans using a compilation of published DILI datasets that have screened for BSEP inhibitors, other hepatic transporters and other mechanism-based toxicity key events. Our results demonstrate that there is little support for in vitro BSEP inhibition being universally DILI predictive. Rather we show that most potent BSEP inhibitors are BDDCS class 2 drugs, which we have demonstrated previously is the BDDCS class most likely to be DILI related. Since BDDCS class is not related to any proposed DILI mechanistic hypotheses, we maintain that if measures of BSEP inhibition alone or together with inhibition of other transporters cannot be differentiated from class 2 assignment, there is no support for in vitro BSEP inhibition being DILI predictive.

In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction

Accurately predicting the hepatic clearance of compounds using in vitro to in vivo extrapolation (IVIVE) is crucial within the pharmaceutical industry. However, several groups have recently highlighted the serious error in the process. Although empirical or regression-based scaling factors may be used to mitigate the common underprediction, they provide unsatisfying solutions because the reasoning behind the underlying error has yet to be determined. One previously noted trend was intrinsic clearance-dependent underprediction, highlighting the limitations of current in vitro systems. When applying these generated in vitro intrinsic clearance values during drug development and making first-in-human dose predictions for new chemical entities though, hepatic clearance is the parameter that must be estimated using a model of hepatic disposition, such as the well-stirred model. Here, we examine error across hepatic clearance ranges and find a similar hepatic clearance-dependent trend, with high clearance compounds not predicted to be so, demonstrating another gap in the field.

Characterization of Fasiglifam-Related Liver Toxicity in Dogs

Fasiglifam, a potent and highly selective agonist of G protein-coupled receptor 40, was developed for the treatment of type 2 diabetes mellitus. However, phase III clinical programs were terminated owing to liver safety concerns. Fasiglifam-related liver toxicity was also observed in repeat-dose dog toxicology studies, characterized by granulomatous inflammation with crystal formation in the liver and/or bile ducts. These histopathological changes were not observed in rat toxicology studies. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis of dog liver sections obtained from a repeat-dose toxicology study indicated that the crystalline material in the affected dog liver contained fasiglifam and fasiglifam glucuronide (fasiglifam-G). Nonclinical mechanistic studies indicated that after 14 days of repeated oral dosing with [¹⁴C]fasiglifam at 200 mg/kg per day to dogs, the concentrations of fasiglifam and fasiglifam-G in the bile exceeded the solubility limit of these compounds in the bile (approximately 3000 µg/ml). After single oral 2- and 200-mg/kg doses administered to rats and dogs, fasiglifam and fasiglifam-G concentrations in dog bile were 5- to 10-fold higher than those in rat bile for the same dose of fasiglifam, while the bile flow rate adjusted by body weight was 4- to 8-fold lower in dogs than in rats. High fasiglifam and fasiglifam-G concentrations in dog bile together with lower bile flow rate could cause crystal formation in dog bile, resulting in secondary granulomatous inflammation in the dog liver.

The Presence of a Transporter-Induced Protein Binding Shift: A New Explanation for Protein-Facilitated Uptake and Improvement for In Vitro-In Vivo Extrapolation

Accurately predicting hepatic clearance is an integral part of the drug-development process, and yet current in vitro to in vivo (IVIVE) extrapolation methods yield poor predictions, particularly for highly protein-bound transporter substrates. Explanations for error include inaccuracies in protein-binding measurements and the lack of recognition of protein-facilitated uptake, where both unbound and bound drug may be cleared, violating the principles of the widely accepted free drug theory. A new explanation for protein-facilitated uptake is proposed here, called a transporter-induced protein binding shift High-affinity binding to cell-membrane proteins may change the equilibrium of the nonspecific binding between drugs and plasma proteins, leading to greater cellular uptake and clearance than currently predicted. The uptake of two lower protein-binding organic anion transporting polypeptide substrates (pravastatin and rosuvastatin) and two higher binding substrates (atorvastatin and pitavastatin) were measured in rat hepatocytes in incubations with protein-free buffer versus 100% plasma. Decreased unbound K _m values and increased intrinsic clearance values were seen in the plasma incubations for the highly bound compounds, supporting the new hypothesis and mitigating the IVIVE underprediction previously seen for highly bound transporter substrates.

An examination of protein binding and protein-facilitated uptake relating to in vitro-in vivo extrapolation

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 f_u, 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 f_u terms included when implementing IVIVE, the concept of protein-facilitated uptake, and the mechanisms that have been proposed to account for facilitated uptake.

Development and Validation of an Immunoassay for Tenofovir in Urine as a Real-Time Metric of Antiretroviral Adherence

BACKGROUND

Pharmacologic adherence measures were critical to the interpretation of the tenofovir (TFV)-disoproxil-fumarate/emtricitabine (TDF/FTC) PrEP trials. These measures are being incorporated into PrEP demonstration projects, but currently-available metrics in plasma, cells, hair or urine involve expensive and time-intensive mass-spectrometry (MS)-based methods. No point-of-care method to assess PrEP adherence in real-time has yet been implemented. Antibody-based tests allow for low-cost, easy-to-perform, point-of-care drug detection. In this study, we developed an antibody-based TFV immunoassay and evaluated its test characteristics among individuals taking TDF/FTC.

METHODS

We synthesized possible immunogens based on TFV's molecular structure, injected rabbits with the conjugated derivatives, and bled them monthly for subsequent ELISA-testing for TFV-specific antibodies. We purified an antibody with specific TFV binding and created dose-response curves for ELISA-quantification. We then quantified TFV in urine from human participants not taking TDF/FTC and from individuals taking daily TDF/FTC 300 mg/200 mg for 7 days with a 7-day washout period using ELISA with this TFV-specific antibody. ELISA results were compared with the gold-standard test for TFV detection/quantification using liquid-chromatography-tandem-MS (LC-MS/MS).

FINDINGS

None of the urine samples from 115 participants not taking TDF/FTC showed ELISA- reactivity, indicating 100% specificity (95% CI 97-100%) of the immunoassay. Among participants taking TDF/FTC, 67 of 70 samples positive by LC-MS/MS were positive by the ELISA-immunoassay for an estimated diagnostic sensitivity of 96% (95% CI 88-99%). The precision of the assay was high (coefficient of variationb15%). The rank correlation between ELISA and LC-MS/MS values in the 70 quantitative urine TFV levels positive by LC-MS/MS across a wide range of concentrations among participants on TDF/FTC was high (r = 0.96).

INTERPRETATION

Our antibody-based immunoassay for measuring TFV in urine performed well compared to the gold-standard of LC-MS/MS among individuals taking TDF/FTC. A sensitive and specific immunoassay paves the way for real-time monitoring/feedback on recent adherence to TFV-based regimens, which should optimize interpretation and outcomes during PrEP and ART roll-out.

Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review of In Vitro Methodologies vs BDDCS Classification

Drug-induced liver injury (DILI) is a major safety concern; it occurs frequently; it is idiosyncratic; it cannot be adequately predicted; and a multitude of underlying mechanisms has been postulated. A number of experimental approaches to predict human DILI have been proposed utilizing in vitro screening such as inhibition of mitochondrial function, hepatobiliary transporter inhibition, reactive metabolite formation with and without covalent binding, and cellular health, but they have achieved only minimal success. Several studies have shown total administered dose alone or in combination with drug lipophilicity to be correlated with a higher risk of DILI. However, it would be best to have a predictive DILI methodology early in drug development, long before the clinical dose is known. Here we discuss the extent to which Biopharmaceutics Drug Disposition Classification System (BDDCS) defining characteristics, independent of knowing actual drug pharmacokinetics/pharmacodynamics and dose, can be used to evaluate prior published predictive proposals. Our results show that BDDCS Class 2 drugs exhibit the highest DILI severity, and that all of the short-lived published methodologies evaluated here, except when daily dose is known, do not yield markedly better predictions than BDDCS. The assertion that extensively metabolized compounds are at higher risk of developing DILI is confirmed, but can be enhanced by differentiating BDDCS Class 2 from Class 1 drugs.

CONCLUSION

Our published analyses suggest that comparison of proposed DILI prediction methodologies with BDDCS classification is a useful tool to evaluate the potential reliability of newly proposed algorithms, although BDDCS classification itself is not sufficiently predictive. Almost all of the predictive DILI metrics do no better than just avoiding BDDCS Class 2 drugs, although some early data with microliver platforms enabling long-enduring metabolic competency show promising results.

Development and validation of an assay to analyze atazanavir in human hair via liquid chromatography/tandem mass spectrometry

RATIONALE

Assays to quantify antiretrovirals in hair samples are increasingly used to monitor adherence and exposure in both HIV prevention and treatment studies. Atazanavir (ATV) is a protease inhibitor used in combination antiretroviral therapy (ART). We developed and validated a liquid chromatography/tandem mass spectrometry (LC/MS/MS)-based method to quantify ATV in human hair, per the NIH Division of AIDS Clinical Pharmacology Quality Assurance (CPQA) program and the FDA bioanalytical method validation guidelines.

METHODS

ATV was extracted from hair using optimized methods and the extracts were injected onto a BDS C-18 column (5 μm, 4.6 × 100 mm), followed by isocratic elution via a mobile phase composed of 55% acetonitrile, 45% water, 0.15% acetic acid, and 4 mM ammonium acetate, at a flow rate of 0.8 mL/min prior to analysis by MS/MS. Levels were quantified using positive electrospray ionization by multiple reaction monitoring (MRM) for the transitions MH⁺ m/z 705.3 to m/z 168.0 and MH⁺ m/z 710.2 to m/z 168.0 for ATV and ATV-d5 (internal standard), respectively.

RESULTS

Our assay demonstrated a linear standard curve (r = 0.99) over the concentration range of 0.0500 ng ATV/mg hair to 20.0 ng/mg hair. The inter- and intraday accuracy of ATV quality control (QC) samples was -1.33 to 4.00% and precision (% coefficient of variation (%CV)) was 1.75 to 6.31%. The %CV for ATV levels in hair samples from highly adherent patients (incurred samples) was less than 10%. No significant endogenous peaks or crosstalk were observed in the specificity test with other HIV drugs. The overall extraction efficiency of ATV from incurred hair samples was greater than 95%.

CONCLUSIONS

This highly sensitive, highly specific and validated assay can be considered for therapeutic drug monitoring for HIV-infected patients on ATV-based ART.

Why Drugs Fail in Late Stages of Development: Case Study Analyses from the Last Decade and Recommendations

New drug development is both resource and time intensive, where later clinical stages result in significant costs. We analyze recent late-stage failures to identify drugs where failures result from inadequate scientific advances as well as drugs where we believe pitfalls could have been avoided. These can be broadly classified into two categories: 1) where science is mature and the failures can be avoided through rigorous and prospectively determined decision-making criteria, scientific curiosity, and discipline to follow up on emerging findings; and 2) where problems encountered in Phase 3 failures cannot be explained at this time, as the science is not sufficiently advanced and companies/investigators need to recognize the possibility of deficiency of our knowledge. Through these case studies, key themes critical for successful drug development emerge-understanding the therapeutic pathway including receptor and signaling biology, pharmacological responses related to safety and efficacy, pharmacokinetics of the drug and exposure at target site, optimum dose, and dosing regimen; and identification of patient sub-populations likely to respond and will have a favorable benefit-risk profile, design of clinical trials, and a quantitative framework that can guide data-driven decision making. It is essential that the right studies are conducted early in the development process to answer the key questions, with the emphasis on learning in the early stages of development, whereas Phase 3 should be reserved for confirming the safety and efficacy. Utilization of innovative technology in identifying patients based on molecular signature of their disease, rapid assessment of pharmacological response, mechanistic modeling of emerging data, seamless operational processes to reduce start-up and wind-down time for clinical trials through use of electronic health records and data mining, and development of novel and objective clinical efficacy endpoints are some concepts for improving the success rate.

Isoniazid hair concentrations in children with tuberculosis: a proof of concept study

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 <12 years initiated on a thrice-weekly treatment regimen including INH (10 mg/kg) for newly diagnosed tuberculosis were enrolled. INH concentrations in hair were measured using liquid chromatography-tandem mass spectrometry at 1, 2, 4 and 6 months after initiating anti-tuberculosis treatment. We found that INH hair concentrations in all children on thrice-weekly INH were detectable and displayed variability across a dynamic range.

Local delivery of hormonal therapy with silastic tubing for prevention and treatment of breast cancer

Broad use of germline testing has identified an increasing number of women at risk for breast cancer with a need for effective chemoprevention. We report a novel method to selectively deliver various anti-estrogens at high drug levels to the breast tissue by implanting a device comprised of silastic tubing. Optimized tubing properties allow elution of otherwise poorly bioavailable anti-estrogens, such as fulvestrant, into mammary tissue in vitro and in vivo with levels sufficient to inhibit estrogen receptor activation and tumor cell proliferation. Implantable silastic tubing delivers fulvestrant selectively to mouse mammary fat tissue for one year with anti-tumor effects similar to those achieved with systemic fulvestrant exposure. Furthermore, local delivery of fulvestrant significantly decreases cell proliferation, as assessed by Ki67 expression, most effectively in tumor sections adjacent to tubing. This approach may thereby introduce a potential paradigm shift and offer a promising alternative to systemic therapy for prevention and early interception of breast cancer.

Comparison of Measures of Adherence to Human Immunodeficiency Virus Preexposure Prophylaxis Among Adolescent and Young Men Who Have Sex With Men in the United States

Background

Young men-who-have-sex-with-men (MSM) are disproportionately impacted by human immunodeficiency virus (HIV). Preexposure prophylaxis (PrEP) could reduce HIV acquisition among youth, but suboptimal adherence threatens effectiveness. Optimal metrics of PrEP adherence among adolescents have remain undefined.

Methods

The Adolescent Trials Network 110/113 studies provided daily oral PrEP with tenofovir (TFV) disoproxil fumarate/emtricitabine over 48 weeks to a diverse population of MSM (aged 15-22 years). Self-reported adherence was assessed and PrEP drug concentrations measured from hair and dried blood spot (DBS) samples; 23% of participants received Wisepill electronic monitoring devices. The average number of PrEP doses per week taken was estimated, and concordance between measures assessed.

Results

Among 243 participants, hair samples were collected at 1186/1238 (96%) person-visits. The concordance of TFV levels in hair and TFV-diphosphate in DBS around thresholds consistent with taking ≥4 and 7 PrEP doses/week was high (76% and 80%). Hair and DBS concentrations correlated poorly with self-report and Wisepill metrics. Through week 12, 40%-60% of participants (by hair and DBS), ≤31% (Wisepill), and >85% (self-report) were estimated to have taken ≥4 PrEP doses/week (a threshold associated with protection among MSM). For all measures except self-report, adherence declined over time, with half of participants taking <2 doses/week by week 48.

Conclusions

Among youth on PrEP, adherence waned over time. Self-report overestimated adherence, and use of Wisepill was limited. Hair collection was highly acceptable and provided similar interpretations to DBS. Incorporation of either metric in future PrEP studies among youth could identify suboptimal adherence and trigger interventions.