Doxorubicin pharmacokinetics: Macromolecule binding, metabolism, and excretion in the context of a physiologic model

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Doxorubicin Pharmacokinetics: Macromolecule Binding,Metabolism, and Excretion in the Context of aPhysiologic ModelDANIEL L. GUSTAFSON,1 JEFFREY C. RASTATTER,1 TINA COLOMBO,2 MICHAEL E. LONG11Department of Pharmaceutical Sciences, School of Pharmacy, University of Colorado Health Sciences Center,4200 East 9th Avenue, Denver, Colorado 802622Laboratory of Cancer Chemotherapy, Mario Negri Institute for Pharmacological Research, Via Eritrea 62, 20157 Milan, ItalyReceived 19 June 2001; revised 25 September 2001; accepted 25 February 2002ABSTRACT: The studies described herein were designed to determine whether doxo-rubicin (DOX) pharmacokinetics (PKs) could be described by a physiologically based PKmodel that incorporated macromolecule-specific binding and organ-specific metabolismand excretion. Model parameters were determined experimentally, or were gatheredfrom the literature, in a species-specific manner, and were incorporated into a phy-siologically based description of DOX blood and tissue distribution for mice, dogs, andhumans. The resulting model simulation data were compared with experimentallydetermined data using PK parameters calculated using compartmental or noncompart-mental analysis to assess the predictability of the models. The resulting physiologicallybased PK model that was developed could accurately predict blood and tissue PKs ofDOX in mice. When this model was interspecies extrapolated to predict DOX levels indogs and humans undergoing treatment for cancer, predictions in dog plasma or humanserumwere also consistent with the actual clinical data. This model has potential utilityfor predicting the magnitude of PK interactions of DOX with other drugs, and for pre-dicting changes in DOX PKs in any number of clinical situations. 2002 Wiley-Liss, Inc.and the American Pharmaceutical Association J Pharm Sci 91:14881501, 2002Keywords: doxorubicin; pharmacokinetics; physiologically based modeling; simula-tion; PBPKINTRODUCTIONDoxorubicin (DOX) is a naturally occurring an-thracycline that has a broad spectrum of activityfor the treatment of cancer. The five anthracy-clines currently in clinical use worldwide areDOX, daunorubicin, idarubicin, epirubicin, andpirarubicin. Standard combination chemotherapyregimens for the treatment of solid tumors,lymphomas, and leukemias usually contain ananthracycline component.1 The dose-limiting toxi-cities of the two commonly used anthracyclines,DOX and daunorubicin, are myelosuppression,mucositis, and cardiac toxicity.2The anthracyclines can react with numerouscellular components to induce a number of effectsthat are thought to have a role in the antineo-plastic and toxic effects of these compounds. An-thracyclines are capable of DNA intercalation andinhibition of RNA and DNA polymerases,3 inter-action with topoisomerase II,4 and alkylation ofDNA.5 DOX is also capable of generating reactiveoxygen species through quinone redox cycling,6,7and perturbing cellular Ca2 homeostasis throughboth receptor-mediated8,9 and redox-mediated10mechanisms. Other mechanisms of action havealso been investigated, including inhibition of1488 JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002Correspondence to: Daniel L. Gustafson (Telephone: 303-315-0755; Fax: 303-315-6281;E-mail: of Pharmaceutical Sciences, Vol. 91, 14881501 (2002) 2002 Wiley-Liss, Inc. and the American Pharmaceutical Associationthioredoxin reductase11 and interaction with com-ponents of the plasma membrane.12 The role ofeach of these processes in the causation of anti-tumor and side effects is still debated, although itis reasonable to assume that all have some role inthe pharmacology of these compounds.The pharmacokinetics (PKs) of DOX has beenwell studied in many species. After intravenousdosing, DOX blood levels fall dramatically as thedrug distributes into tissues, followed by a slowelimination phase due to renal and biliary clear-ance and metabolism. DOXmetabolism occurs viareduction of a side chain carbonyl group by aldo-keto reductases13 yielding doxorubicinol, and byreductive cleavage of the sugar moiety to form the7-hydroxy aglycone.14 DOX partitioning fromblood to tissues has been shown to correlate withDNA concentration,15 and DOX is also known tobind to anionic lipids, particularly cardiolipin.16,17To relate drug dosage to therapeutic and/ortoxic effects, physiologically based PK (PBPK)models are useful tools that allow for simulationand prediction of target tissue concentrations ofactive drug or metabolites. PBPK models are amathematical representation of a biological sys-tem constructed using known physiologic andbiochemical constants. The body is divided intocompartments that represent individual organsand tissue groupings, and the transport, clearance,andmetabolism of xenobiotics between these com-partments or within these compartments is de-scribed using mass balance ordinary differentialequations.18 Physiologically based modeling hasmany advantages which include: (a) utilization ofa large body of physiologic and physiochemicaldata; (b) extrapolation of results both across spe-cies and routes of administration; and (c) predic-tion of PKs and target tissue dosimetry over awiderange of doses.19Previous PBPK models for DOX have beendeveloped,20,21 but these models have used tissuepartitioning as defined by plasma/tissue concen-tration ratios to describe DOX tissue distribution,and have not included specific terms for thevarious metabolic and elimination pathways thathave a role in DOX disposition. The model de-veloped with these studies uses experimentallydefined biochemical parameters for DOX metabo-lism and macromolecule binding, and places themin the context of a physiologic model representingorgans that are targets for toxicity or have a rolein DOX metabolism and excretion. The resultingmodel output describesDOXdistribution inmousetissues and calculatedDOXPKparameters.Whenthe model is scaled to canine or human physiologyand biochemical parameters, the resulting outputagain correlates with DOX serum PKs of patientsreceivingDOX therapy. These results suggest thatthe DOX PBPK model developed herein incorpo-rated the major factors that dictate DOX PK inmammalian species.MATERIALS AND METHODSChemicalsDOX hydrochloride, daunorubicin hydrochloride,calf-thymus DNA, and Hoechst 33258 were pur-chased from Sigma Chemical Co. (St. Louis, MO).All other reagents were of analytical grade.DOX PK Studies in MiceFemale, Balb/c mice (45 weeks old) were pur-chased from Harlan Sprague Dawley (Indiana-polis, IN) and allowed to acclimate for 7 days.Animals were housed (three per cage) in poly-carbonate cages and kept on a 12-h light/darkcycle. Food andwater were given ad libitum. Afteracclimation, mice were randomly assigned to thetime-point groups, with three mice per group. Allstudies were conducted in accordance with theNational Institutes of Health guidelines for thecare and use of laboratory animals, and animalswere housed in a facility accredited by theAmerican Association of Laboratory Animal Care.DOX was administered by intravenous (iv) in-jection into the tail vein at a dose of 6 mg/kg in avolume of 50 mL. Animals were killed by cervicaldislocation after methoxyflurane anesthesia, andtissue and blood samples collected at 5, 10, 30, 60,120, and 480 min after injection. Heart, liver,kidney, small intestine, large intestine, skeletalmuscle, fat, spleen, and bone marrow were collec-ted, rinsed with phosphate buffered saline (pH7.6), and stored at808C until assayed. Blood wascollected by cardiac puncture, placed in hepar-inized vials, and stored at 208C until analyzed.DOX PKs in DogsSerum samples were obtained from client animalsbeing treated for lymphoma with DOX (30 mg/m2)every 3 weeks for five cycles at the VeterinaryTeaching Hospital at Colorado State University(Fort Collins, CO). All samples were obtained fromdogs whose owners had signed a consent agree-ment regarding the inclusion of the patient in aclinical PK study.DOXORUBICIN PHARMACOKINETICS 1489JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002DOX High-Pressure Liquid Chromatography(HPLC) AnalysisAn extraction protocol modified from De Jonget al.22 was used for blood, serum, and tissuesamples. Briefly, tissue was homogenized in waterto give a final concentration of 10 mg/mL. Analiquot of 100 mL homogenate, 50 mL whole blood,or 100 mL serum was transferred to a 1.5-mL poly-propylene microfuge tube; 50 mL 1 mM daunor-ubicin was added as an internal standard, and0.6 mL methanol was added. The samples werevortex mixed for 15 min, 0.25 mL 12 mM phos-phoric acid was added, and then centrifuged at10,000g for 8 min. The resulting supernatant wascollected, the volume adjusted to 1.0 mL, andanalyzed by HPLC with fluorescence detection aspreviously described.22The HPLC system used was a Beckman GoldSystem (Beckman-Coulter, Fullerton, CA) con-sisting of a 126 pump module, 508 autosampler,and a Jasco FP-920 fluorescence detector (JascoCorp., Tokyo, Japan) with excitation and emissionwavelengths set at 480 and 580 nm, respectively.The mobile phase consisted of 15 mM NaH2PO4(pH 4)/acetonitrile in a 2:1 volume-to-volumeratio at a flow rate of 1 mL/min. Separationwas done on an Alltima C18 (5 mm) 250 4.6 mmcolumn (Alltech Associates Inc., Deerfield, IL)fitted with an Alltima C18 guard cartridge (AlltechAssociates).DNA Content AnalysisTissue preparation and DNA analysis weredone using a protocol modified from Downs andWilfinger.23 Mouse tissues were collected as de-scribed above from untreated animals. Dog tis-sues were collected upon necropsy from clientanimals at the Veterinary Teaching Hospital(Colorado State University) and stored at 808C.Human tissues, either surgical or autopsy speci-mens, were acquired through the CooperativeHuman Tissue Network Western Division (CaseWestern Reserve University, Cleveland, OH).Tissues (10 mg per 0.75 mL) were homogenizedin AT extraction solution (1 N NH4OH, 0.2%Triton X-100) and incubated at 378C for 10 min.An aliquot of 100 mL homogenate was then dilutedto 1 mL with Assay Buffer (100 mM NaCl, 10 mMEDTA, 10 mM Tris, pH 7.0) and centrifugedat 2500g for 30 min at room temperature. Thesupernatant was collected and stored on ice untilassayed.The assay mixture consisted of 10 mMTris (pH 7.0), 100 mM NaCl, 10 mM EDTA, and100 ng/mL Hoechst 33258. Fifty microliters ofsample (blank, standards, and unknowns) wasadded to 2 mL of the assay mixture, and thefluorescence determined using a Hitachi F-2000fluorescence spectrophotometer (Hitachi Instru-ments Inc., San Jose, CA) with excitation andemission wavelengths set at 350 and 455 nm,respectively. Blanks, samples, and unknownswere all measured in triplicate, and measure-ments were considered to be valid if replicatesamples differed by less than 10%. The concentra-tion of DNA in unknown samples was calculatedusing a standard curve generated by plottingfluorescence units versus DNA concentration instandards made up using calf thymus DNA.MolarDNA concentration was calculated for each tissueusing a value of 330.9 formula weight for DNAbases and a density of 1 g/mL for all tissues.DOX PBPK Model DevelopmentA PBPK model for DOX was developed incorpor-ating DNA and cardiolipin binding, tissue-specificmetabolism, and biliary and urinary eliminationof DOX into a seven-compartment flow-limitedmodel. A schematic of this model is shown inFigure 1. Physiologic parameters (tissue volumesand blood flows) for mouse, dog, and human aretaken from Brown et al.24 and are presented inTable 1. Bone marrow blood flow parameters wereestimated from studies in rat25 for the mousemodel, and humans26 for the dog and humanmodels. Tissue DNA content was measured inmouse, dog, and human tissues and the resultsare presented in Table 2. Cardiolipin levels inmouse, dog, and human tissues were estimatedfrom measurements made in rat tissues.27 Theuse of the rat cardiolipin values to estimate thelevels in mouse, dog, and human tissues is sup-ported by previous studies that show similartissue levels of cardiolipin, when measured aspercent of total lipid phosphorous, in mouse,human, and other species as compared with therat.28,29Affinity constants for DOXDNA (KDNA) andDOXcardiolipin (KCAL) binding were set at 200and 400 nM, respectively. These values are con-sistent with the in vitro binding characteristics ofDOX to DNA and cardiolipin.17 The concentrationof DNA and cardiolipin in the tissues was modi-fied by a factor that represents the number ofmolecules of DNA or cardiolipin that bind one1490 GUSTAFSON ET AL.JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002DOX molecule. From in vitro studies, it has beenapproximated that the binding site in DNA forDOX is made up of two base pairs (four bases)30;however, in the modeling process, this term wasderived as 500 bases. This discrepancy betweenthe in vitro number of bases constituting a DOXbinding site and the model-derived term can beeasily accounted for because of obvious differencesin naked DNA used in in vitro studies andprotein-coated dynamic DNA that is presentin vivo. From in vitro data with cardiolipin, amolar ratio of 2:1 (DOX/cardiolipin) has beenproposed,17 and the number used in the model forcardiolipin molecules per DOX binding site is two.A generic tissue compartment mass balanceequation is represented by eq. 1:dATdt QTCA CVT 1where AT is the amount of drug in the compart-ment, QT is blood flow to the compartment(Table 1), and CA and CVT are the arterial andvenous blood concentrations of drug being deliv-ered to and exiting from the compartment. Thearterial blood concentration available to all tis-sues, with the exception of liver, is considered tobe the free drug concentration in the blood, andit is assumed that DOX is 70% bound to plasmaprotein.31 For liver, the model assumes that bothfree and bound drugs are available for tissueuptake.32 To account for binding of DOX to DNAand cardiolipin within the respective tissues, theconcentration of DOX leaving in the tissue venousblood flow is modified by eq. 2:CVT ATVT TDNA VTKDNA CVT TCAL VTKCAL CVT2where VT is the volume of the tissue compartment(Table 1), TDNA, and TCAL are the DNA and car-diolipin binding capacity available (DNA or car-diolipin concentration divided by the number ofmolecules per DNA binding site), and KDNA andKCAL are the binding affinities of DOX to DNAand cardiolipin, respectively. This mathematicalrepresentation of saturable chemical-specific bind-ing to macromolecules in tissues is modified fromthose used to describe 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) binding and PKs using a phy-siologic model.33Metabolic and Excretory Model ParametersDOX metabolism to doxorubicinol and the 7-OH-aglycone occurs in hepatic and extrahepatictissues. Km and Vmax values for mice, dogs, andhumans were used as previously reported forDOX metabolism by aldo-keto reductases in liverTable 1. Physiologic Parameters Used in PBPKModel SimulationsMouse Dog Human% of body weightOrgan volumeaLiver 5.5 3.3 2.6Heart 0.5 0.8 0.5Kidney 1.7 0.5 0.4Bone marrow 2.1 2.1 2.1Gut 4.2 3.7 1.7Slowly perfused 70.5 75.8 77.3Rapidly perfused 10.6 5.6 7.5Blood 4.9 8.2 7.9% of cardiac outputOrgan blood flowLiver 2.0 4.6 4.6Heart 6.6 4.6 4.0Kidney 9.1 17.3 17.5Bone marrowb 1.0 3.0 3.0Gut 14.1 25.1 18.1Slowly perfused 40.0 38.0 34.3Rapidly perfused 27.2 7.4 18.5aPhysiologic parameters were obtained from Brown et al.24bFemoral bone marrow blood flow in mice is estimated fromdata in rats by Iversen et al.,25 and dog and human values areestimated from a study by Lahtinen et al.26Figure 1. Schematic representation of a physiologi-cally based pharmacokinetic model for DOX. Solidarrows represent blood flow, and dotted or dashedarrows represent metabolic or excretory pathways thateliminate the parent drug.DOXORUBICIN PHARMACOKINETICS 1491JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002and kidney.34 Glycosidase activity in liver, kidney,and heart is expressed as a first-order rate con-stant based on measured values in mouse, dog,and human.34 These first-order rate constantswere calculated by transforming published resultsin nanomoles per milligram of protein, to hour1by incorporating the time frame in which theexperiments were performed and using the inte-grated first-order rate expression (AtA0 ekt)and solving for k. Values were converted fromper milligram of protein to per organ volume byusing a conversion of 120mg of protein per gram oftissue inkidney, 180mgof protein per gramof livertissue, and 15 mg of microsomal protein per gramof tissue for kidney, liver, and heart. These con-version valuesweredetermined experimentally byusing known tissue amounts and determining theprotein content. Parameters for fecal and urinaryexcretion of DOXwere optimized within themodelto best describe the tissue distribution data andtaking into account published fecal and urinaryelimination kinetics.35,36 Themetabolic and excre-tory parameters used are shown in Table 3.Data AnalysisThe predictive capability of the model was asses-sed by calculating the median absolute perfor-mance error (MAPE%), the median performanceerror (MPE%), and the root mean squared perfor-mance error (RMSPE%).37 The performance er-rors were calculated as the difference between themeasured values and the predicted values nor-malized to the predicted value as shown in eq. 338:Performance Error PE Cmeasured CpredictedCpredicted 100% 3The MAPE%, which is a measure of the accuracyof the prediction, was calculated as shown in eq. 4where n is the total number of samples for thattissue:MAPE% medianjPE1j; jPE2j; . . . jPEnj 4The MPE%, which is a measure of the bias of theprediction, was calculated as:MPE% median PE1;PE2; . . .PEn 5Table 2. DNA and Cardiolipin Tissue Levels Used in PBPK Model SimulationsOrgan Mouse Dog HumanDNA contentaLiver 26.0 4.0 14.6 0.4 23.7 2.3Heart 20.6 4.0 3.2 1.0 8.3 4.0Kidney 50.2 7.9 13.5 2.7 16.2 2.2Bone marrow 175.1 36.8 23.7 12.7 19.1 13.7Gutb 60 8.1 2.8 25.2 2.3Slowly perfusedc 10 4.5 4.5Rapidly perfusedd 60 15 15Cardiolipin contente Mouse, dog, and humanLiver 44.6Heart 43.8Kidney 52.3Bone marrow 25Gut 25Slowly perfused 15Rapidly perfused 30aValues are expressed in mmol/L, and represent the meanSD of at least three independentdeterminations.bMouse value is based on a proportional average of DNAmeasurements made in large and smallintestine and stomach. Dog and human values are based on measurements made in necropsycollected tissues along the gastrointestinal tract.cMouse value is based on a proportional average of DNAmeasurements made in skeletal muscleand adipose tissue. Dog and human values are based on DNA measurements made in dog skeletalmuscle.dMouse value is based on DNA measurements made in spleen, kidney, and liver.eTissue levels of cardiolipin are expressed in mmol/L assuming a molecular weight of 1300.Mouse, dog, and human tissue cardiolipin levels are estimated based on values obtained in rattissues.271492 GUSTAFSON ET AL.JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002The RMSPE%, which is a measure of the accuracyof the prediction, was calculated as:RMSPE% Pni1PE2invuuut 6Total Protein DeterminationTotal protein was determined using the BCAtotal protein assay reagent (Pierce Chemical,Rockford, IL) with bovine serum albumin as astandard.Computer Simulation and SoftwareThe simulation model was implemented in ad-vanced continuous simulation language (ACSL)Tox version 11.5.2 (Pharsight Corp., MountainView, CA) on a PC-based pentium computer.Compartmental modeling and calculation of PKparameters were done using WinNonlin version3.0 (Pharsight Corp.).RESULTSDOX PKs and Model Simulations in MiceDOX blood and tissue levels were determinedin female Balb/C mice after a single iv dose of6 mg/kg; the resulting blood and tissue levels over8 h are shown in Figure 2. Tissue and serumlevels from CD2F1/Crl BR male mice treated with10 mg/kg DOX via a single iv dose are alsoshown.39 Data from the previously publishedstudy were kindly provided by Dr. MaurizioDIncalci (Mario Negri Institute for Pharmacolo-gical Research, Milan, Italy). Model simulationsat both dose levels (6 and 10 mg/kg) are shownalong with the data points for each tissue. Theresulting model simulations are in agreementwith the actual data for blood and serum at bothdosing levels (Fig. 2A). Levels in all other tissuesare consistent with the predicted values, andthe simulations have the same tissue-specificcharacteristics as the data values. This is mostprominently shown in bone marrow data andsimulations (Fig. 2F), where both the data and theTable 3. Metabolic and Excretory Parameters Used in PBPK Model SimulationsMetabolismMouse Dog HumanKm Vmax Km Vmax Km VmaxAldo-keto reductaseaLiver 97 410 118 4633 275 1804Kidney 172 1080 133 1685 539 3161GlycosidasebLiver 9524 13,295 12,104Kidney 7531 1805 484Heart 883 2061 760Excretory parameters Mouse, dog, and humanKm VmaxFecal eliminationcBiliary transport 10 300Gut transport 0.2 80Urinary eliminationdActive secretion 10 100Fraction renal bloodflow cleared0.1aAldo-keto reductase activities are expressed as Km (mM) and Vmax (mmol h1 kg tissue1) and were calculated from in vitro databy Loveless et al.34bGlycosidase activity is expressed as a first-order rate constant (h1 kg tissue1) as calculated from in vitro data by Lovelesset al.34cBiliary transport and gut transport of DOX into the gut lumen is expressed as Km (mM) and Vmax (mmol h1 kg tissue1). Theseparameters were optimized in the model using available mouse tissue data.dUrinary elimination of DOX is expressed as both glomerular filtration and active secretion from arterial blood flowing to thekidney. Glomerular filtration is estimated to be equal to 10% of renal blood flow, and active secretion is expressed as Km (mM) andVmax (mmol h1 kg tissue1).DOXORUBICIN PHARMACOKINETICS 1493JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002simulation show a slow accumulation of drug inthe tissue over the time frame of the sampling.Predictive performance of the model was anal-yzed in mouse tissues by calculating the MAPE%,MPE%, and RMSPE%, as described previously,and the results are shown in Table 4. The predic-tive accuracy, as measured by MAPE%, variedbetween 16.7 and 40.9%, with a majority of thetissues having MAPE% values of approximately20. The median percent variability in the actualtissue data sets for the 6 mg/kg dose varied from16.4 to 65.7%. Therefore, model predictions weregenerally within the variance of the data. Thepredictive simulations showed no consistent biastoward over or under prediction as shown by theMPE%. These values ranged from22.3 to 12.8%,with four of the tissues showing a negative MPE%and two having positive MPE%.Whole blood and serum PK parameters werecalculated using a two-compartment descrip-tion and the results were compared with model-generated values taken at the same time points.This allowed for a more direct comparison of theactual and model-generated data; the results areshown in Table 5. PK parameters estimated fromactual time-course data were similar to para-meters estimated from data points generated bythe PBPK model at the sampling time points.Tissue PK parameters, area under the curve(AUC), and terminal half-life, were also calcu-lated in tissues for both the measured and thesimulated data, and the results are shown inTable 6. From these data, the ratios (measured/simulated) for each parameter, at each dose, werecalculated to compare the measured and thesimulated values. These results show that forAUCs, the simulated data compared very well tothe measured data at both 6 and 10 mg/kg doses,with the largest discrepancy being 54%. Themeasured data used to calculate the tissue PKparameters had coefficients of variation (CV%) of42.8 32.7 and 17.5 13.0 for the 6 mg/kg and10 mg/kg determinations at each time-point,respectively. The terminal half-life ratios weresimilar in most cases, except for kidney at 6 mg/kgand heart at 10 mg/kg, where the measured andsimulated determinations were different by ap-proximately three-fold. Because this parameteris calculated from the slope of a putative linearTable 4. Measures of Predictive Performance forPBPK Model Simulations in Mice and Canine andHuman Cancer PatientsSpecies Tissue MAPE%a MPE%b RMSPE%cMouse Blood/Plasma 16.7 3.2 57.9Liver 20.8 11.6 45.9Kidney 22.3 22.3 25.2Gut 40.9 13.5 48.2Heart 21.0 7.1 31.6Bone marrow 24.2 12.8 25.3Canine Serum 11.2 0.7 25.2Human Patient 1 17.2 6.5 25.4Patient 2 51.8 49.7 98.9Patient 3 46.9 22.4 61.7Patient 4 30.1 14.2 40.5Patient 5 21.7 20.8 28.3aMAPE% represents the median absolute performanceerror, which is a measure of accuracy and is calculated asdescribed in the text.bMPE% represents the median performance error, which isa measure of bias and is calculated as described in the text.cRMSPE% represents the root mean squared performanceerror, which is a measure of accuracy and is calculated asdescribed in the text.Figure 2. Tissue levels and PBPKmodel simulationsin mouse (A) whole blood or serum, (B) liver, (C) gut, (D)kidney, (E) heart, and (F) bone marrow after iv treat-ment with 6 or 10 mg/kg DOX. Filled symbols representthe 6 mg/kg dose and open symbols the 10 mg/kg dose.Solid lines are model simulations of a 6 mg/kg dose, anddashed lines are model simulations of a 10 mg/kg dose.The two filled symbol sets in gut (C) are from measure-ments made in the large (squares) and small (circles)intestine.1494 GUSTAFSON ET AL.JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002terminal elimination phase, discrepancies inindividual points can have a large impact on thisparameter. As shown in Figure 2D with the 1-hpoint, and 2E with the 12-h, this seems to be thecase with the calculation of terminal half-life inthese tissues at the respective doses.DOX PKs and Model Simulations in DogsTime course samples were collected from clientdogs being treated with DOX (30 mg/m2) forlymphoma at the Veterinary Teaching Hospital atColorado State University, and plasma levels ofTable 5. DOXPharmacokinetic Parameters inMice Calculated FromWhole Blood (6 mg/kg) and Serum (10mg/kg)Data and PBPK Model SimulationsaPK Parameters 6 mg/kgb 6 mg/kgc 10 mg/kgb 10 mg/kgcAUC (nmolh/L) 4243 1394 3297 226 8351 1621 9116 566T1/2a (h) 0.036 0.005 0.118 0.035 0.067 0.045 0.22 0.076T1/2b (h) 10.3 4.0 10.3 0.9 7.3 1.8 8.4 0.7Vss (L) 0.734 0.073 0.987 0.019 0.456 0.033 0.486 0.011CL (L/h) 0.052 0.017 0.067 0.005 0.044 0.009 0.040 0.003aPK parameters were calculated using a two-compartment model. Values represent the parameter estimates estimatedstandard error.bPK parameters are calculated from measured DOX levels in mouse whole blood or serum after a single iv dose.cPK parameters are calculated from PBPK model-predicted DOX levels in mouse whole blood or serum after a single iv dose.Table 6. Tissue Pharmacokinetic Parameters From Mouse DOX Pharmacokinetic Data and PBPK ModelSimulationsaSample AUCtb AUCinfc t1/2d AUCt Ratioe AUCinf Ratioe t1/2 RatioeLiver6 mg/kg 74.3 112.7 5.96 mg/kg sim 65.0 95.7 4.7 1.14 1.18 1.2610 mg/kg 166.3 251.9 7.810 mg/kg sim 128 212.5 9.9 1.30 1.19 0.79Kidney6 mg/kg 133.6 465.5 18.16 mg/kg sim 210.2 353.3 6.2 0.64 1.32 2.9210 mg/kg 387.1 676.3 9.210 mg/kg sim 398.2 739.8 11.5 0.97 0.91 0.80Gut6 mg/kg 73.3 113.5 5.56 mg/kg sim 83.7 116.6 4.5 0.88 0.97 1.2210 mg/kg 229.2 405.1 9.810 mg/kg sim 169.4 262.7 9.3 1.35 1.54 1.05Heart6 mg/kg 78.6 174.6 9.86 mg/kg sim 97.5 222.9 9.9 0.81 0.78 0.9910 mg/kg 220.5 255.5 4.610 mg/kg sim 199.5 412.4 13 1.11 0.62 0.35Bone marrow6 mg/kg 71.8 6 mg/kg sim 58.8 1.22 aTissue pharmacokinetic parameters (AUCs and t1/2) were calculated using noncompartmental analysis with extravascular inputof drug.bAUCt represents the calculated AUC from time 0 to time 8 or 12 h for the 6 mg/kg and 10 mg/kg data sets, respectively.cAUCinf represents the calculated AUC extrapolated to infinity.dt1/2 represents the estimated half-life in hours for DOX elimination from the tissue as estimated from linear regression of theterminal elimination phase.eRatio of the value generated for that parameter from the measured versus the simulated data sets.DOXORUBICIN PHARMACOKINETICS 1495JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002DOX were determined. The mouse PBPK modelused above was scaled to dog physiologic (Table 1)and metabolic parameters (Table 3), and DNAmeasurements were made in dog tissues for use inthe model (Table 2). The model was also modifiedby adding an iv infusion component that allowsfor the delivery of the dose, at a constant rate,over the course of an infusion time period. Modelsimulations were then performed, and the result-ing model output was compared with mean valuesfrom four animals (Fig. 3). The predictive perfor-mance of the simulation is shown in Table 4, witha MAPE% of 11.2% and a MPE% of 0.7%.Plasma PK parameters were calculated fromthe individual plasma time-course data using athree-compartment description. The resulting PKparameters were compared with PK parametersthat had been estimated from simulated plasmalevels in which weight and dose were matched tothe client dogs from which the plasma sampleoriginated. Because many of the model para-meters are scaled to body weight, it is importantto take this source of variability into account. Theresulting comparison is shown in Table 7, with theactual and simulated-data-generated parametersshowing good agreement. One potential source ofdifference in the measured and simulated data isthe fact that the end-of-infusion measurementis generally much greater in the simulated versusmeasured values. This is probably because anydelay in sampling between the actual end-of-infusion and the drawing of the blood samplewill lead to large changes in DOX concentrationbecause of the very steep slope of the initial dis-tribution phase for this drug. For this reason, tobetter compare our model output to the actualmeasured data, we included an evaluation of thesimulated data set using measured end-of-infu-sion values, and the resulting PK parameters arealso included in Table 7.DOX PKs and Model Simulations in HumansA human PBPK model was generated usinghuman parameters for organ size and blood flow(Table 1), tissue DNA content (Table 2), andmetabolism (Table 3). Excretory parameters andcardiolipin content values used were the sameas those used in the mouse and dog models, butwere scaled relative to the size of the organ. Theresulting model outputs were compared withhuman DOX PK data sets kindly provided byDr. Leonard Liebes (New York University Schoolof Medicine, New York, NY) from a previouslypublished study.40 Individual model simulationswere performed to match patient weight, totaldose, and length of infusion, and the results areshown in Figure 4. The accuracy of the predic-tions for each patient was determined from theMAPE%, and ranged from 17.2 to 51.8%. Therewas no trend toward over-prediction or under-prediction, because the MPE% ranged from 20.8to 49.7%, with three of the patients having nega-tive values and two of the patients having positivevalues.PK parameters were estimated from actual andsimulated data for each patient using a three-compartment model, and the results are summar-ized in Table 8. The simulated data showedsignificant differences from the actual data whencomparing AUC, CL (clearance), and Vss (steady-state volume of distribution). However, thesedifferences were attributable to the magnitudeof the end-of-infusion point in the simulated data,as shown in Table 8, when the simulated end-of-infusion value is substituted with an actual value.From our simulations, it can be estimated that thelarge differences that we see in the simulated andFigure 3. Plasma levels of DOX in dogs after a20-min iv infusion at a dose of 30 mg/m2. Pointsrepresent the mean standard deviation of four ani-mals treated at this dose. The solid line represents thePBPK model-predicted values using dog physiologicand biochemical parameters. Themodel simulation wasdone using the mean body weight of the four animalswhose time-course data are shown.1496 GUSTAFSON ET AL.JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002the measured end-of-infusion values can occur ina span of minutes. Therefore, it seems reasonablethat our simulated values would be much higherthan the measured values because of a time lag insampling, or from sampling at a distant site. Theend-of-infusion corrected values are consistentwith the PK parameters that we calculated fromthe data set, as well as previously publishedliterature values on DOX PKs in which a three-compartment model was applied.41DISCUSSIONPBPK models have been developed for a numberof chemotherapeutic agents4245 includingDOX.20,21,46 Most of these models have beenflow-limited models that describe tissue-compart-ment distribution of drugs based on blood/tissuepartitioning and include metabolic and excretoryparameters that are optimized to fit the data sets.An exception to this is the PBPK methotrexatemodels42,47 that incorporated specific binding tomacromolecules and enterohepatic circulation inthe description of methotrexate PKs. The utility ofthese models has been limited to describing tissuelevels in model systems, with the predictive na-ture of these models being largely ignored.The PBPK model described herein is unique inthat it relies on macromolecule-specific bindingto describe the tissue distribution of DOX, and in-corporates measured physiochemical parametersTable 7. DOX Pharmacokinetic Parameters in Canine Patients and Canine PBPKModel SimulationsPK Parametersa Actual Datab Simulated Datac Simulated Datadt1/2 a (h) 0.043 0.013 0.035 0.003 0.049 0.015t1/2 b (h) 0.44 0.20 0.24 0.01 0.26 0.04t1/2 g (h) 19.8 22.3 25.1 6.0 28.3 11.4AUC (nmolh/L)e 66.7 66.1 92.6 11.5 66.1 10.4CL (L/h) 46.5 28.5 20.2 0.7 28.4 3.0Vss (L) 496 223 318 79 803 453aPharmacokinetic parameters were derived using a three-compartment model with iv infusioninput and first-order elimination. All parameters are calculated in a model-dependent manner andrepresent the meanSD from four patient data sets and model simulations.bTime-course DOX serum data were generated from samples obtained from four client dogsbeing treated for lymphoma at a dose of 30 mg/m2 at the Veterinary Teaching Hospital at ColoradoState University.cTime-course data for DOX were generated using our PBPK model with patient weight, dose,and infusion time set in the model to match that from the actual data.dThe simulated end-of-infusion DOX plasma concentration was replaced by the actualdetermined value to compensate for real-time versus delayed sampling in the actual data sets.eAUC values were normalized for dose (per mg/m2).Figure 4. Serum levels of DOX in human patientsfollowing (A) 13-min, (B) 6-min, (C) 5-min, and (D)10-min iv infusions. Panel C contains simulations anddata from patients receiving doses of 30 (open symbols,dashed line) and 60 (closed symbol, solid line) mg/m2.All other data and simulations are from patientsreceiving a dose of 60 mg/m2. Points represent thedetermined value for the patient at that time point.Lines represent the PBPK model-predicted value usinghuman physiologic and biochemical parameters. Modelsimulations were done using the weight of the indivi-dual patients and using dosing that delivered the exactamount of drug the patient received over the infusionperiod.DOXORUBICIN PHARMACOKINETICS 1497JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002into this description. The relationship betweenDOX tissue partitioning and DNA content hasbeen previously established.15 The binding ofDOX to cardiolipin has also been well estab-lished,17 and the relative and absolute affinities ofDOX for these macromolecules have been stud-ied.17,30 The use of this information, coupledwith the flow dynamics and tissue compartmentsof a PBPK model, enables prediction of thedistribution of DOX to mouse tissues. The addi-tion of organ-specific metabolism that is based onin vitro metabolic studies,34 and biliary and uri-nary elimination that are mechanistic in nature,produces a model based on fundamental physiol-ogy and physio- and biochemical properties ofDOX.DOX is one of the most widely used agents inthe treatment of cancer, and studies that deter-mine potential interactions of this agent withother drugs that are given concurrently to cancerpatients are continuously being performed. Amodel of DOX disposition that includes termsthat describe process-specific excretion and meta-bolism is potentially very useful for predictingthe impact of various agents on DOX PKs. Forexample, this model could be used to predict andquantify some of the sequence-dependent PK ef-fects that have been seen when anthracyclineshave been used in combination with taxanes,48,49or to predict the effects that drug vehicles mayhave on DOX disposition.50This model may also be coupled to Monte Carlosimulation that will allow for the incorporationof variability across the model parameters.51Because of the limited number of patients thatare used in phase I trials of new drug combina-tions, the use of a model that can generate popu-lation-based data would be useful for identifyingsubsets of individuals that may be susceptibleto alterations in DOX PKs that are detrimental.This type of approach could be very useful in pre-dicting the variation in DOX PKs that could beexpected because of induction of P-glycoproteinby concurrent taxane treatment.52 Preliminarystudies using this model coupled to Monte Carlosimulation have shown that when parametervariability is incorporated into the model, themodel generates DOX PK variability that is verysimilar to that seen in the population (data notshown).In summary, we have developed a model forDOX distribution in animals that incorporatesmacromolecule-specific binding, metabolism, andbiliary and urinary excretion in the context of aflow-based physiologic model. This model is uni-que from previous physiologically based modelsof DOX distribution in that it relies on knowninteractions of DOX with tissue macromoleculesrather than measured tissue to blood concentra-tion differences to determine DOX tissue uptakeand release. The resulting model was able to bescaled from mice to dogs to humans, and predictDOX PKs in each species. This model has utilityin the prediction of potential drug interactionsand predicting PK alterations in special patientpopulations.Table 8. DOX Pharmacokinetic Parameters in Human Patients and Human PBPK Model SimulationsPK Parametersa Actual Datab Simulated Datac Simulated Datad Literature Dataet1/2 a (h) 0.034 0.014 0.035 0.003 0.056 0.027 t1/2 b (h) 0.64 0.46 0.32 0.01 0.38 0.12 t1/2 g (h) 23.0 5.6 26.0 4.3 27.0 6.4 28.5 10.7AUC (nmolh/L)f 63.4 13.1 94.7 3.7 66.4 7.0 79.4 29.8CL (L/h) 43.5 6.9 28.4 1.0 41.0 5.5 44.5 18.1Vss (L) 1091 307 533 85 1230 601 1758 850aPharmacokinetic parameters were derived using a three-compartment model with iv infusion input and first-order elimination.All parameters were calculated in a model-dependent manner and represent the meanSD from five patient data sets and modelsimulations.bHuman time-course data for DOX were kindly provided by Dr. Leonard Liebes (New York University School of Medicine,New York, NY).cTime-course data for DOXwere generated using our PBPKmodel with patient weight, dose, and infusion time set in themodel tomatch that from the actual human data.dThe simulated end-of-infusion DOX plasma concentration was replaced by the actual determined value to compensate for real-time versus delayed sampling in the actual data sets.eDOX pharmacokinetic parameters as determined after the first course of therapy in cancer patients from a previously publishedstudy.41fAUC values were normalized for dose (per mg/m2).1498 GUSTAFSON ET AL.JOURNAL OF PHARMACEUTICAL SCIENCES, VOL. 91, NO. 6, JUNE 2002NOMENCLATUREQ Blood flow (L/h)A Amount of drug (moles)V Tissue volume (L)CA Arterial blood concentration of free DOX(M)CV Venous blood concentration of total DOXleaving tissues (M)CBL Arterial blood concentration of total DOX(M)FB Fraction of DOX bound to plasma proteinsTDNA Tissue-specific DNA binding capacity forDOX (M)TCAL Tissue-specific cardiolipin binding capa-city for DOX (M)KDNA Binding affinity of DOX for DNA (M)KCAL Binding affinity of DOX for cardiolipin (M)AM Amount metabolized (moles)AE Amount excreted (moles)VMAX Maximum rate of activity (moles/hr/Ltissue)KM Michaelis constant (M)KMET First ordermetabolic rate constant (h1 kgtissue1)FFILT Fraction renal blood flow filtered at theglomerulusSubscriptsT Generic tissue compartmentC Total cardiac outputL LiverK KidneyG GutB BloodAKR Aldo-keto reductaseAG AglyconePGP P-glycoproteinACKNOWLEDGMENTSWe are grateful for the help of Dr. Kim Selting,Dr. Greg Ogilvie, Dr. Wendy Pott, andMrs. LauraChubb (College of Veterinary Medicine and Bio-medical Sciences, Colorado State University, FortCollins, CO) for their help in performing thesestudies. We also thank Drs. Melvin E. Andersenand Russell S. Thomas for helpful discussions.APPENDIXThe mathematical equations used to simulate themodel structure shown in Figure 1 are shownbelow. The complete model code as written inACSL is available by contacting the correspond-ing author.Tissue compartment mass balancedATdt QTCA CVTCVT ATVT TDNA VTKDNA CVT TCAL VTKCAL CVTBlood compartment mass balancedABdtXQT CVT QC QL CA QL CBLCA ABVB 1 FBCBL ABVBDOX metabolism by aldo-keto reductasesdAMAKRdt VMAXAKT CVTKMAKT CVTDOX metabolism to aglyconedAMAGdt KMETAG CVT VTAmount of DOX eliminated in urinedAEUdt FFILT QK CA VMAXPGPK CBLKMPGPK CBLAmount of DOX eliminated in fecesdAEFdt VMAXPGPL CVLKMPGPL CVL VMAXPGPG CVGKMPGPG CVGREFERENCES1. Robert J. 1998. Anthracyclines. In: Grochow LB,Ames MM, editors. A clinicians guide to chemo-therapy pharmacokinetics and pharmacodynamics.Baltimore: Williams & Wilkins, pp 93173.2. Young RC, Ozols RF, Myers CE. 1981. The anthra-cycline neoplastic drugs. 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