Volume of Distribution Prediction: Physiologically Based ...

AAPSVolume of Distribution Prediction:Physiologically Based MethodologiesPatrick PoulinConsultant, Québec city, CanadaLos Angeles - November 11, 2009patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009

Number of Publicationpatrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Publications on Tissue Distribution PredictionA Shift from Environmental to Pharmaceutical Sciences3025Publications (1970-2009)EnvironmentalToxicologyPharmaceuticalContribution (1970-2009)Others20Sawada et al.15Abraham et al.Poulin, Krishnan, Theil10Lombardo et al.5Rowland et al.01970-1999 2000-2009Year

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPSOutline1Distribution Parameters: Introduction234Physiologically-Based Prediction:Presenting the methodsCross-Validation ExercisesFurther Developments5 Conclusion6 Acknowledgements and References

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS1. Distribution Parameters: Introduction

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009DistributionDistributionThe distribution of xenobiotics inthe body after their absorptionExtent of DistributionDetermined by:• partitioning across various membranes.• non-specific binding to tissue components.• specific binding to proteins.• physiological volumes.

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Distribution Parameters EstimationMETHOD XMETHOD YKpEssential inputParameters ofPBPK modelsTissueVolumesVdssVdssVdss = volume of distribution at steady-stateKp = tissue:plasma (blood) ratios at steady-state

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Distribution Parameters:How can we estimated it?In vivo StudiesBolus: Statistical momenttheory (Vdss)Infusion: measurement inanimal tissues (Kp)Prediction MethodsDiverse correlationsAlgorithms"Hybrid" modelsPrediction: knowing Vdss earlier would reduce time, cost and animals.Physiologically-based prediction: knowing that we may lackknowledge to facilitate more rationale decisions.

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS2. Physiologically-Based Prediction:Presenting the methods

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009First Mechanistic/PhysiologicalPrediction method of DistributionVolatile Organic Chemicals (VOCs) in the EnvironmentMETHOD YNeutral VOCsLipophilicityNeutral lipidsKp(tissue:air PC)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Starting Point of Tissue CompositionModels (TC) – Reconstituting the tissueExperimental work of Lowe & Hagler, 1969 for VOCs:Triglyceride:air PCTissuecomponentsCholesterol:air PCPhospholipid:air PCWater:air PCKp ( tissue:air)PC : air * VcComponentvolume fractions

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009In-vitro Distribution of Neutral VOCsSupporting the Concept of Lowe & HaglerPoulin and Krishnan & de Jongh et al.

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Predicting Distribution for DrugsNeutral VOCsBasesacidic phospholipids,cation transportersAcids, Neutralsalbumin, lipoproteinsIonizationPlasma proteinsbindingDrugs

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Existing Prediction methods of Kpand/or Vdss based on PhysiologyTissue compositionmodels/algorithmsAll in vitro-basedLowe and HaglerPaterson and MackayPoulin et alBerezhkovskiyRodgers & RowlandGastroPlus®Correlation-HybridmodelsPoulin & Theil (in vitro-based)Bjorkman (in vivo-based)Janssen et al (in vivo-based)Arundel modelAstra Zeneca (in vivo-based)Oie-Tozer modelLombardo et al (in vitro-based)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Prediction Methods of Kp (Vdss)PrincipleDrug-SpecificInputsTISSUECOMPOSITION (TC)- Kp’s were calculated as the ratioof the sum of free and bound drug(i.e., nonspecific & specific) in tissuecomponents (intracellular &interstitial spaces) to that in plasma.- Lipophilicity (Log P, Log D)- Plasma proteins binding (fup)- Blood:plasma ratioARUNDEL- Kp’s were calculated from therelationships between Vdss anddisappearance rate constantsobserved in 5 groups of tissues.- Lipophilicity (Log D)- Plasma proteins binding (fup)- Rat Vdss in vivoData - In vitro based (All classes of drugs) - In vivo based (All classes of drugs)Number ofpublishedversions- 4 (Poulin, Krishnan & Theil, 1995-2002)(Rodgers & Rowland, 2007) (GastroPlus®)- 1 (Astrazeneca, 1997)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Prediction Methods of Kp (Vdss)CORRELATIONSHYBRIDS &OIE TOZERPrincipleDrug-SpecificInputs- Kp’s were predicted with correlations.- Kp muscle is correlated with Kp ofother lean tissues for in vivo data.- Kp fat is correlated with Kp muscleadjusted for lipophilicity.- Kp in vivo of muscle- Rat Vdss in vivo- Lipophilicity (log P)- Kp’s were predicted with correlations.- Kp of lean tissues and fat (or Vdss)are correlated with in vitro data(blood:plasma PC or physicochem.).- Some Relations with Physiology.- Lipophilicity (Log p)- Plasma proteins binding (fup)- Blood:Plasma ratioData - In vivo based (All classes of drugs) - In vitro based (Basic drugs only)Number ofpublishedversions- 3 (Poulin & Theil 2000) (Bjorkman 2004)(Janssen et al. 2008)- 3 (Poulin & Theil 2009 A,B)(Lombardo 2004)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS3. Cross-Validation Exercises

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Validation of Prediction Methods of VdssValidation Articles and InitiativeRodgers & RowlandDe Buck et al. (2007)Pharm. Res. (24):918 ; DMD (35):649Janssen et al.(2008)J. Pharm. Sci. (97):2324Poulin & Theil(2009)J. Pharm. Sci. (98):4941PhRMAInitiative2007-2010Two tissuecompositionmodelsOnecorrelationmodelSixIn vitro- based &hybrid modelsNineteentypes ofmodel142 drugs22 drugs61 drugs108 drugsValidation with Diverse Datasets:Rat and/or Human Vdss (Kp)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Validation of Prediction Methods of VdssCurrent initiative of PhRMA/PISC on Predictive ModelsMain focus is on the predictability of human PK based on preclinical data usinga novel and blinded dataset (n=108 drugs).First head-to-head evaluation of models. Publications expected in 2010.PART 1Allometry & OthersCalculation MethodAllometric Wajima(Dedrick)PART 2PhysiologicallyBased (PBPK)Assessment of several methodsused for predicting parametersof ADME (Vdss, CL, AUC, F).Direct validation of 19 differentprediction methods of human Vdss(mechanistic vs. empirical)Assessment of several methods used forpredicting plasma concentration-time profilesby integrating predicted ADME parametersobtained from Part 1.Indirect validation of predictionmethods of Vdss

Additional Validation of this StudyCROSS-VALIDATION OF ALL DISTRIBUTION MODELSPREDICTION METHODSIN VITRO-BASED MODELSTC1 : Poulin & Theil (2002)TC2 : Berezhkovskiy (2004)TC3 : Rodgers & Rowland (2007)TC4 : GastroPlus®Oie-Tozer : Lombardo (2004)Correlation-Hybrid : Poulin & Theil (2009)IN VIVO-BASED MODELSArundel : Astrazeneca (1997)Correlation : Janssen et al. (2008)Literature-based dataThree datasets:A. 39 drugsB. 61 drugsC. 64 drugsLog P (-0.09 to 5)fup: 0.009 to 1pKa 2 to 11ALLOMETRYSA : bound and unbound drugsHuman VdssRat Kp’spatrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Reported Predictive Performance for Kp and Vdssusing diverse Datasets and Methods% Within 2-FoldError Window100%Rat Kp’s*81%Rat Vdss85%Human Vdss94%50%39%35%14%0%* : 13 tissues

% WITHIN 2-FOLD ERRORPredictive Performance in HumanIn vitro & In vivo models - Dataset on Vdss of 39 drugsHuman Vdss100STRONG ACIDS ALL & NEUTRALS DRUGS BASES (n=39) (n=16) (n=23)755025 250TC1 (Poulin)TC1 (Poulin)TC3 (Rodgers)TC3 (Rodgers)TC4 (GastroPlus)TC1 (Poulin, 2002)TC2 (Berezhkovskiy)TC3 (Rodgers)TC2 (Berezhkovskiy)TC2 (Berezhkovskiy)Oie-Tozer (Lombardo)TC4 (GastroPlus)Correlation (Janssen)Arundel (AZ)Correlation (Janssen)Arundel (AZ)Correlation (Janssen)Arundel (AZ)TC4 (GastroPlus)Hybrid (Poulin, 2009)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Predictive Performance in HumanIn vitro models - Dataset on Vdss of 61 Basic drugsHuman VdssPERCENTAGE WITHIN 2 FOLD-ERRORHybrid (Poulin)10080Oie-Tozer (Lombardo)6040200TC1 (Poulin)TC4 (GastroPlus)TC2 (Berezhkovskiy)TC3 (Rodgers)Poulin and Theil, 2009AB, JPS(A:accepted, B:submitted)

% WITHIN 2-FOLD ERRORpatrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Predictive Performance in RatIn vitro & In vivo models - Dataset on rat Kp’s of 64 drugsChoosing the more accurate method for each class of drugsRat Kp’s (13 tissues) (n=600)1007550TC1 (Poulin)TC3 (Rodgers)TC4 (GastroPlus)Correlation (Janssen)250Neutrals Acids Bases Zwiterions

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009PHYSIOLOGY VS ALLOMETRYHuman Vdss% Within 2-FoldError Window100%PHYSIOLOGICALIN VITRO-BASED94%25 DRUGS OUF OF THOSE THREE DATASETSIN VIVO-BASED85%COMMON EMPIRICAL75%ALLOMETRY(SA BOUND & UNBOUND DRUGS)*65%50%30%33%*Rat, dog + mouse and/or monkey0%

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS4. Further Developments

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Unified Algorithm for Predicting PartitionCoefficients (PCs) (Kp)Environmental Chemicals and DrugsThe objective was to develop a unified algorithm such that the PCsfor both drugs and environmental chemicals could be predicted.PCs were calculated as the ratio of the sum of free and bound chemical(i.e., nonspecific and specific) in tissue components (intracellular &interstitial spaces) to that in blood (plasma & erythrocyte).A total of 455 PCs (muscle, liver, fat) were calculated for several classesof drugs (n=68) and environmental chemicals (n=80).The level of prediction accuracy is identical to that of the previouslypublished algorithms for specific sub-set of drugs or chemicals.First attempt towards the computation of macro and micro level PCs fordeveloping organ and cellular-based PBPK models for diverse molecules.

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009Comparison of Prediction Methods of DistributionPeyret T, Poulin P, Krishnan K. Toxicological Sciences (2010)MECHANISTICEQUATIONSENVIRONMENTAL CHEMICAL PCsPHARMACEUTICAL PCsTISSUE:AIR BLOOD:AIR BLOOD:AIR TISSUE:BLOOD TISSUE:PLASMA UNBOUNDALL VOCsLIPOPHILICVOCsHYDROPHILICVOCsPoulin & Krishnan (1996) A X X X XCONTAMINANTS BASES ACIDS, NEUTRALS,ZWITERRIONSHaddad et al. (2000) BXPoulin & Theil (2002) C X X XRodgers et al. (2005) DXRodgers & Rowland (2006) EXSchmitt (2008) F X XSUGGESTED UNIFIEDALGORITHMX X X X X XA: Toxicol Appl Pharmacol 136: 126-130 and 131-137.B: Chemosphere 40: 839-843..C: J Pharm Sci 91:129-156.D: Pharm Res 24:918-933.E: J Pharm Sci 95:1238-1249.F: Toxicol In Vitro 22: 457-67

Estimating Drug Permeation Limitation forTissue Partition Coefficients (PCs) (Kp)• There is an evident lack of tools to predict tissuepermeation for drugs in PBPK models.• Must always optimize permeability-area product.• Challenges:– Predictions from physicochemical properties.– Predictions from in vitro data.– Estimating tissue area subjected to exposure.Hantash J, Millipore (St. Charles, MO)Haddad S, Université du Québec à Montréal (Montréal, Canada)patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009

Cell permeability (cm/s)Cell permeability (cm/s)Estimating Drug Permeation Limitation forTissue Partition Coefficients (PCs) (Kp)PAMPACellsbased1000MDCK100CACO21001010.10.011.E-06 1.E-04 1.E-02 1.E+00 1.E+02PAMPA permeability (cm/s)1010.10.010.0011.E-06 1.E-04 1.E-02 1.E+00 1.E+02PAMPA permeability (cm/s)• A dataset of 67 compounds is investigated (acids, bases, neutrals)• 7 types of tissue are studied• Outliers –> identified as actively transported compoundsHantash J, Millipore (St. Charles, MO)Haddad S, Université du Québec à Montréal (Montréal, Canada)

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS5. Conclusion

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009ConclusionPrediction of DistributionSeveral in vitro and in vivo based models are availablein the literature only for rat and human.In vitro models may provide similar degree of predictionaccuracy compared to in vivo-based models and allometry.There is a need to come up with generic models morepredictive since no models were perfect with all classes ofdrugs and all parameters (Vdss, Kp).Main inaccuracies were observed for zwitterions.Drug permeation limitation and transports are not yetaccounted for in prediction models of distribution.

patrick-poulin@videotron.ca P. Poulin. April, 2007.Distribution Prediction AAPS – November 11, 2009AAPS6. AcknowledgementsNamesInstitutionsDr. Zhang Hua LillianDr. Jennifer ShengDr. Michael HagemanPhRMA membersProf. Kannan KrishnanThomas PeyretProf. Sami HaddadFDA, Washington DCAstrazeneca, USABMS, USAPhRMA, Washington DCUniversité de MontréalUniversité de MontréalUQAM, MontréalDr. Thierry LavéHoffmann-La Roche, BaselDr. Frank-P Theil Genentech, San FranciscoThank you!

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