Absorption and Drug Development

Name: Absorption and Drug Development | Solubility, Permeability, and Charge State
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Solubility, Permeability, and Charge State

Alex Avdeef(Autor*in)

Wiley (Verlag)

2. Auflage

Erschienen am 11. April 2012

544 Seiten

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Intro
ABSORPTION AND DRUG DEVELOPMENT
CONTENTS
PREFACE
PREFACE TO THE FIRST EDITION
ABBREVIATIONS
NOMENCLATURE
COMMERCIAL TRADEMARKS
INTRODUCTION
1.1 BULLDOZER SEARCHING FOR A NEEDLE IN A HAYSTACK?
1.2 AS THE PARADIGM TURNS
1.3 SCREEN FOR THE TARGET OR ADME FIRST?
1.4 ADME AND MULTIMECHANISM SCREENS
1.5 ADME AND THE MEDICINAL CHEMIST
1.6 THE "ABSORPTION" IN ADME
1.7 IT IS NOT JUST A NUMBER, IT IS A MULTIMECHANISM
REFERENCES
2: TRANSPORT MODEL
2.1 PERMEABILITY-SOLUBILITY-CHARGE STATE AND
2.2 PROPERTIES OF THE GASTROINTESTINAL TRACT (GIT)
2.3 PH MICROCLIMATE
2.4 INTRACELLULAR
2.5 TIGHT JUNCTION COMPLEX
2.6 STRUCTURE OF OCTANOL
2.7 BIOPHARMACEUTICS CLASSIFICATION SYSTEM
REFERENCES
3: pKa DETERMINATION
3.1 CHARGE STATE AND THE pKa
3.2 METHODS OF CHOICE FOR THE DETERMINATION OF THE pKa
3.3 TITRATION WITH A GLASS-MEMBRANE
3.4 EQUILIBRIUM EQUATIONS AND THE IONIZATION CONSTANT
3.5 "PURE SOLVENT" ACTIVITY SCALE
3.6 IONIC STRENGTH AND DEBYE-HÜCKEL/ DAVIES EQUATION
3.7 "CONSTANT IONIC MEDIUM" ACTIVITY SCALE
3.7.1 Constant Ionic Medium Activity Scale, fX?
3.7.2 Example of the Constant Ionic Medium Activity Scale Treatment
3.8 TEMPERATURE DEPENDENCE OF pKa VALUES
3.8.1 Thermodynamics of Temperature Dependence of pKa
3.8.2 Predicting pKa at 37°C from Measured Values at 25°C
3.9 ELECTRODE CALIBRATION AND STANDARDIZATION
3.9.1 Overview: From Millivolts to pH to pcH
3.9.2 One-Buffer Operational Calibration of Electrode and Automatic Temperature Compensation
3.9.3 Four-Parameter Procedure for Standardizing pH Electrode:
3.9.3.1 Blank Titration
3.9.3.2 Buffer-Capacity Enhanced Standardization Titrations
3.9.4 Blank Titrations Assess the State of the Measurement System
3.9.5 Frequency of Electrode Standardizations
3.9.6 Effects of Ionic Strength on
3.9.7 Effects of Temperature on
3.10 BJERRUM PLOT: MOST USEFUL GRAPHICAL TOOL IN pKa ANALYSIS
3.10.1 Derivation of the Bjerrum Function
3.10.2 Diagnostic Uses of the Bjerrum Plots
3.10.2.1 Confirming the Number of pKa and the Value of nH
3.10.2.2 Correcting Residual Acidity/Basicity Error
3.10.2.3 Correcting Sample Concentration Error
3.10.2.4 Recognizing Electrode Calibration Errors
3.10.2.5 Errors in Titrant Concentration
3.10.2.6 Consequences of Errors in Ionic Strength
3.10.2.7 Evidence of Precipitation
3.10.2.8 pKa "Ghosts"
3.10.2.9 Overlapping pKa Values
3.10.3 More Than One Substance: Subtracting Effects of Dissolved Carbon Dioxide
3.10.4 Case Examples
3.10.5 Bjerrum's Lasting Contribution
3.11 COSOLVENT METHODS FOR pKa DETERMINATION OF PRACTICALLY INSOLUBLE SUBSTANCES
3.11.1 Traditional Cosolvent Extrapolation Procedure: psKa versus wt% Cosolvent
3.11.2 Yasuda-Shedlovsky Cosolvent Extrapolation Procedure: psKa + log[H2O] versus 1/e
3.11.3 Which Method Is Better to Use: Traditional or Yasuda-Shedlovsky?
3.11.4 Precipitation in Mixed-Solvent Titration
3.11.5 Electrode Standardization in Mixed Solvents
3.11.6 Yasuda-Shedlovsky Ancillary Data
3.11.7 Recommended psKa Titration Protocol
3.11.8 Use of Cosolvents for Water-Soluble Molecules
3.12 OTHER METHODS FOR pKa MEASUREMENT
3.12.1 Spectrophotometric Measurements
3.12.2 Capillary Electrophoresis (CE) Measurements
3.12.3 Chromatographic pKa Measurement
3.12.4 pKa Measurement by PAMPA (Parallel Artificial Membrane Permeability Assay)
3.12.5 pKa Determination from Shake-Flask log DOCT versus pH Profiles
3.12.6 Comparison of Methods
3.13 pKa MICROCONSTANTS
3.14 pKa COMPILATIONS
3.15 pKa PREDICTION PROGRAMS
3.16 DATABASE OF pKa (25°C AND 37°C)
APPENDIX 3.1 QUICK START: DETERMINATION OF THE pKa OF CODEINE
A3.1.1 Data Collection
A3.1.2 Data Processing
APPENDIX 3.2 TUTORIAL FOR MEASUREMENTS WITH GLASS-MEMBRANE PH ELECTRODE
A3.2.1 The pH Electrode Is an Electrochemical Sensor
A3.2.2 Calibration of Glass-Membrane pH Electrodes Requires Standard Buffers
A3.2.3 Sources of Error in the Most Accurate pH Determinations
A3.2.4 Interlaboratory Comparison of pH Measurement Using Glass-Membrane pH Electrodes
A3.2.5 Three pH Scales in Use
APPENDIX 3.3 PH CONVENTION ADOPTED BY IUPAC AND SUPPORTED BY NIST
APPENDIX 3.4 LIQUID-JUNCTION POTENTIALS (LJP)
A3.4.1 LJP Minimized with Equi-ionic Cell Design (Best Case, but Inconvenient)
A3.4.2 Constant but Small LJP with Constant Ionic Medium Cell (Practical Case)
A3.4.3 Largest LJP Errors with Zero Ionic Strength Media (Worst Case)
A3.4.4 Summary
APPENDIX 3.5 pKa REFINEMENT BY WEIGHTED NONLINEAR REGRESSION
A3.5.1 Function Minimized in the Weighted Nonlinear Regression Analysis
A3.5.2 Overview of the Refinement Procedure
A3.5.3 Weighting Scheme and Goodness-of-Fit (GOF)
A3.5.4 Mass Balance Equations and "Local" Refinement
A3.5.4.1 Sample Calculation of the Initial Point Prior to Titrant Addition
A3.5.4.2 Sample Calculation of the Titration Curve after Volume of Titrant Addition
A3.5.4.3 Jacobian Method in "Local" Refinement
A3.5.5 Normal Equations and "Global" Refinement
A3.5.6 Automatic Ionic Strength Compensation
A3.5.7 Reactant and Titrant Concentration Factor Refinement
A3.5.8 Multisubstance Refinement
A3.5.9 In situ Standardization of the pH Electrode
APPENDIX 3.6 MOLALITY TO MOLARITY CONVERSION
REFERENCES
4: OCTANOL-WATER PARTITIONING
4.1 OVERTON-HANSCH MODEL
4.2 TETRAD OF EQUILIBRIA
4.3 CONDITIONAL CONSTANTS
4.4 log
4.5 log
4.6 ION-PAIR PARTITIONING
4.6.1 Partitioning of Quaternary Ammonium Drugs
4.6.2 Common-Ion Effect and log
4.6.3 Summary of Charged-Species Partitioning in Octanol-Water
4.6.4 Ion-Pair Absorption of Ionized Drugs: Fact or Fiction?
4.7 MICRO-log
4.8 METHODS FOR log P DETERMINATION
4.8.1 HPLC Methods
4.8.2 High-Throughput Methods
4.8.3 OTHER log
4.9 DYRSSEN DUAL-PHASE TITRATION log P METHOD
4.9.1 Brief History of the Dual-Phase Titration Method
4.9.2 Dual-Phase Method
4.9.3 Dual-Phase Bjerrum Plots
4.9.3.1 Monoprotic Molecules
4.9.3.2 Multiprotic Molecules
4.9.4 Validation
4.10 IONIC STRENGTH DEPENDENCE OF log P
4.11 TEMPERATURE DEPENDENCE OF log P
4.12 CALCULATED VERSUS MEASURED log P OF RESEARCH COMPOUNDS
4.13 log D VERSUS PH CASE STUDY: PROCAINE STRUCTURAL ANALOGS
4.14 DATABASE OF OCTANOL-WATER log PN, log PI, AND log D7.4
REFERENCES
5: LIPOSOME-WATER PARTITIONING
5.1 BIOMIMETIC LIPOPHILICITY
5.2 TETRAD OF EQUILIBRIA AND SURFACE ION-PAIRING (SIP)
5.3 DATA SOURCES
5.4 LOCATION OF DRUGS PARTITIONED INTO BILAYERS
5.5 THERMODYNAMICS OF PARTITIONING: ENTROPYOR ENTHALPY-DRIVEN?
5.6 ELECTROSTATIC AND HYDROGEN BONDING IN A LOW DIELECTRIC MEDIUM
5.7 WATER WIRES, H+/OHCURRENTS, AND PERMEABILITY OF AMINO ACIDS AND PEPTIDES
5.8 PREPARATION METHODS: MLV, SUV, FAT, LUV, ET
5.9 EXPERIMENTAL METHODS
5.10 PREDICTION OF log PMEM FROM log POCT
5.11 log DMEM, DIFF log PMEM, AND PREDICTION OF log MEM PSIP FROM log POICT
5.12 THREE INDICES OF LIPOPHILICITY: LIPOSOMES, IAM, AND OCTANOL
5.13 GETTING IT WRONG FROM ONE-POINT log DMEM MEASUREMENT
5.14 PARTITIONING INTO CHARGED LIPOSOMES
5.15 pKaMEM SHIFTS IN CHARGED LIPOSOMES AND MICELLES
5.16 PREDICTION OF ABSORPTION FROM LIPOSOME PARTITION STUDIES?
5.17 DATABASE OF log PMEM AND log MEM PSIP
6: SOLUBILITY
6.1 IT'S NOT JUST A NUMBER
6.2 WHY IS SOLUBILITY MEASUREMENT DIFFICULT?
6.2.1 Poor Wettability
6.2.2 Formation of Aggregates and Micelles
6.2.3 Equilibration Time and Metastable Gel States
6.2.4 Polymorphism and Amorphous States
6.3 MATHEMATICAL MODELS FOR SOLUBILITY-
6.3.1 Monoprotic Weak Acid, HA (or Base, B)
6.3.2 Diprotic Ampholyte, XH2 +
6.3.3 Gibbs pKa ("pHmax") and the Tetrad of Equilibria
6.3.4 Aggregation Reactions in Solubility Measurement
6.3.4.1 Sample Derivation of Ionic Aggregation of a Weak Acid
6.3.4.2 Solubility Equations for Other Cases Involving Aggregation Reactions
6.3.5 Complexation Reactions in Solubility Measurement (Phase-Solubility Method)
6.3.5.1 Simple 1:1 Complexation
6.3.5.2 Simple 2:1 Ligand-Drug Complexation
6.3.5.3 Simple 1:1 Complexation with Deprotonation of the Complex
6.3.5.4 Summary of Complexation Equations
6.3.6 Micellar Binding Reactions in Solubility Measurement
6.4 EXPERIMENTAL METHODS
6.4.1 Saturation Shake-Flask ("Gold Standard" SSF Method)
6.4.2 Turbidimetric (DMSO-Containing "Kinetic" Ranking Methods)
6.4.3 Micro-Dissolution for Solubility Measurement (DMSO-Free
6.4.4 DMSO-Containing Thermodynamic 96and 384-Well Plate Methods
6.4.5 DMSO-Free Thermodynamic 96and 384-Well Plate Methods
6.4.6 Facilitated Dissolution Method (FDM)
6.4.7 Can Solubility Depend on the Amount of Excess Solid?
6.4.8 Excipient and Solubilizing Agent Screening
6.4.9 Need for Accurate pKa Determinations
6.5 CORRECTION FOR THE DMSO EFFECT BY THE "
SHIFT" METHOD 6.5.1 DMSO Binding to the Uncharged Form of a Compound
6.5.2 Ionizable Compound Binding by Nonionizable Excipients
6.5.3 Results of Aqueous Solubility Determined from the
6.6 CASE STUDIES (SOLUBILITY-PH PROFILES)
6.6.1 Carboxylic Weak Acids
6.6.1.1 Diclofenac
6.6.1.2 Gemfibrozil
6.6.1.3 Ibuprofen
6.6.1.4 Ketoprofen
6.6.1.5 Mefenamic Acid
6.6.1.6 Naproxen
6.6.1.7 Prostaglandin F2a
6.6.2 Noncarboxylic Weak Acids
6.6.2.1 Glibenclamide
6.6.2.2 Phenytoin
6.6.3 Weak Bases
6.6.3.1 Dipyridamole
6.6.3.2 Papaverine
6.6.3.3 Terfenadine
6.6.4 High-Throughput Excipient/Solubilizer Screening
6.6.4.1 Excipient/Solubilizer Concentrations
6.6.4.2 Excipient/Solubilizer Solubility Profiles
6.6.4.3 Drug Effects
6.6.4.4 Summary
6.6.5 Additional Case Studies of Excipient/Solubilizer Effects on Solubility of Sparingly Soluble Drugs
6.6.5.1 Ketoprofen with Sodium Lauryl Sulfate (SLS)
6.6.5.2 Mefenamic Acid and Hydroxypropyl-ß-Cyclodextrin (HP-ß-CD)
6.6.5.3 Mefenamic Acid and Sodium Taurocholate (NaTC)
6.6.6 Salt Solubility: Amount of Excess Solid Can Determine Solubility
6.6.6.1 Chlordiazepoxide
6.6.6.2 Flurbiprofen
6.6.6.3 Terfenadine
6.7 LIMITS OF DETECTION-PRECISION VERSUS ACCURACY
6.8 DATA SOURCES AND THE "IONIZABLE-DRUG PROBLEM"
6.9 DATABASE OF LOG S0
REFERENCES
7: PERMEABILITY-PAMPA
7.1 PERMEABILITY IN THE GASTROINTESTINAL TRACT
7.2 HISTORICAL DEVELOPMENTS IN PERMEABILITY MODELS
7.2.1 Lipid Bilayer Concept
7.2.2 Black Lipid Membranes (BLM)
7.2.3 Microfilter as Supports
7.2.4 Octanol-Impregnated Filters with Controlled Water Pores
7.2.5 Relationship Between Permeability and Partition Coefficients
7.3 RISE OF PAMPA-A USEFUL TOOL IN EARLY DRUG DISCOVERY
7.3.1 The Original Egg Lecithin Model: PAMPA-EGG
7.3.2 Dioleyoylphosphatidylcholine Model: PAMPA-DOPC
7.3.3 Hexadecane Model: PAMPA-HDM
7.3.4 Biomimetic Model: PAMPA-BM
7.3.5 Hydrophilic Filter Membrane Model: PAMPA-HFM
7.3.6 Double-Sink PAMPA MODEL: PAMPA-DS
7.4 PAMPA-HDM, -DOPC, -DS MODELS COMPARED
7.4.1 In Combo Approach for Relating PAMPA Models, Using Abraham Descriptors
7.4.2Intrinsic Permeability of the Test Compounds by the pKaFLUX Method
7.4.3 DS & DOPC & HDM Permeability Ranking
7.4.4 Abraham Analysis of PAMPA-HDM, -DOPC, and -DS Models
7.4.5 In Combo Analysis of the Differences Between the Three PAMPA Models
7.4.6 Practical Considerations in Using HDM and DS Models
7.5 MODELING BIOLOGICAL MEMBRANES
7.5.1 Lipid Compositions in Biological Membranes
7.5.2 Permeability-pH Considerations
7.5.3 Membrane Retention (Iso-pH without Chemical Sink)
7.5.4 Role of Serum Proteins
7.5.5 Effects of Cosolvents, Bile Acids, and Other Surfactants
7.5.6 Ideal Model
7.6 PERMEABILITY-PH RELATIONSHIP AND THE MITIGATING EFFECT OF THE AQ UEOUS BOUNDARY LAYER
7.6.1 Permeability-pH (Iso-pH DOPC Model)
7.6.2 Permeability-pH (Gradient-pH Double-Sink Model)
7.6.3 Stirring with Orbital Shakers
7.6.4 Individual-Well Stirring
7.6.5 Relationship Between Membrane and ABL Permeability
7.6.6 pH-Dependence of Permeability: Correcting PAMPA Permeability for the ABL and Charge Effects by the pKaFLUX Method
7.6.6.1 Membrane-Limiting Permeation (Hydrophilic Molecules)
7.6.6.2 ABL-Limiting Permeation (Lipophilic Molecules): pKaFLUX Method
7.6.6.3 Analysis of Stirring Effects Using the pKaFLUX Method
7.6.7 ABL Hydrodynamic Model Commonly Used in Cellular Studies
7.6.8 Thickness of the ABL
7.6.9 Why Is the Empirical Hydrodynamic Model a-Factor Not Equal to 0.5?
7.6.10 Determining P0 of Nonionizable Molecules or in Membrane-Limited Permeation
7.6.11 Determination of ABL Permeability from Permeability of Lipid-Free Microfilters
7.6.12 Estimation of hABL from pH Measurements Near the Surface of Membranes
7.6.13Errors in the Determination of P0 by the pKaFLUX Method
7.7 pKaFLUX-OPTIMIZED DESIGN (POD)
7.8 COSOLVENT PAMPA
7.8.1 pKaFLUX Method in Cosolvent Media
7.8.2 Acid-Base In Combo Permeability Model
7.8.3 Cosolvent Extrapolation Method
7.9 UV VERSUS LC/MS DETECTION
7.9.1 UV Data
7.9.2 LC/MS Data
7.10 ASSAY TIME POINTS
7.11 BUFFER EFFECTS
7.12 APPARENT FILTER POROSITY
7.12.1 Apparent Porosity
7.12.2 Apparent Porosity in PAMPA-DS and PAMPA-HDM
7.12.3 Recalculation Using the Apparent Porosity
7.13 PAMPA ERRORS: INTRA-PLATE AND INTER-PLATE REPRODUCIBILITY
7.14 HUMAN INTESTINAL ABSORPTION (HIA) AND PAMPA
7.14.1 MAX-PAMPA Binning Methods
7.14.2 SUM-PAMPA Binning Methods
7.14.3 Human Jejunal Permeability to Predict Human Intestinal Absorption
7.14.4 MAD-PAMPA Method Integrating Solubility and Permeability
7.15 PERMEATION OF PERMANENTLY CHARGED MOLECULES
7.15.1 Charged-Species Transport from Cellular and Liposomal Models
7.15.2 The PAMPA Evidence for the Permeation of Charged Drugs
7.16 PERMEATION OF ZWITTERIONS/AMPHOLYTES-IN COMBO PAMPA
7.16.1 An In Combo PAMPA Model Incorporating Paracellular Contribution
7.16.1.1 Paracellular Permeability Analysis (Pore Radius, Porosity- Pathlength, Electric Potential Gradient)
7.16.1.2 Zwitterion/Neutral Intrinsic Permeability
7.16.1.3 Absorption Prediction with In Combo PAMPA
7.16.2 Absorption Curve as a Function of Pe INT
7.17 PAMPA IN FORMULATION: SOLUBILIZING EXCIPIENT EFFECTS
7.17.1 In Vivo Absorption as a Function of pH
7.17.2 Nonlinear Weighted Regression Reanalysis of Rat Absorption-pH Curves
7.17.3 Solubility and Permeability in Flux
7.17.4 Absorption-Excipient-pH Classification Gradient Map, a Flux Function
7.17.5 The Conversion of Intrinsic Data to Intestinal pH 5.0, 6.2, and 7.4 Conditions
7.17.6 Absorption and the Underlying Permeability and Solubility
7.17.6.1 PAMPA-Excipient-pH CGM
7.17.6.2 Solubility-Excipient-pH CGM
7.17.6.3 Solubility-Product "Salt Ceiling"
7.17.7 Absorption-Excipient-pH CGM
7.17.8 HP-ß-CD Effects
7.17.9 pH-Partition Hypothesis "Inversion"
7.17.10 Comparisons with Drug-Cyclodextrin
7.18 DATABASE OF DOUBLE-SINK PAMPA log P0, log Pm. 6 5, AND log Pm. 7 4
APPENDIX 7.1 QUICK START: DOUBLE-SINK PAMPA OF METOPROLOL
A7.1.1 Optimizing Assay Protocol
A7.1.2 PAMPA-DS (Gradient-pH) Assay
A7.1.3 Data Processing
APPENDIX 7.2 PERMEABILITY EQUATIONS
A7.2.1 Thin-Membrane Model (without Retention)
A7.2.2 Iso-pH Equations with Membrane Retention
A7.2.2.1 Without Precipitate in Donor Wells and Sink Condition in Receiver Wells
A7.2.2.2 Sink Condition in Receiver Wells
A7.2.2.3 Precipitated Sample in the Donor Wells
A7.2.3 Gradient-pH Equations with Membrane Retention
A7.2.3.1 Single-Sink: Eq. (A7.28), in Absence of Chemical Sink (Serum Protein or Surfactant in Receiver Wells)
A7.2.3.2 Double-Sink: Eq. (A7.28) in the Presence of Chemical Sink (Serum Protein or Surfactant in Receiver Wells)
A7.2.3.3 Simulation Examples
A7.2.3.4 Gradient-pH Summary
APPENDIX 7.3 PAMPA PARAMEMBRANE WATER CHANNELS
A7.3.1 PAMPA Permeability Equation Taking into Account Paramembrane Contribution
A7.3.2 PAMPA Determinations
A7.3.3 Water Pores in PAMPA Membrane Barrier
REFERENCES
8: PERMEABILITY: Caco-2/MDCK
8.1 PERMEABILITY IN THE GASTROINTESTINAL TRACT
8.1.1 Human Jejunal Permeability
8.1.2 Environment of the GIT Site of Absorption
8.1.2.1 Intestinal Surface Accessibility and the "Smooth Tube" Approximation
8.1.2.2 Aqueous Boundary Layer (ABL)
8.1.2.3 Paracellular Aqueous Channels
8.1.2.4 pH Gradients
8.1.2.5 Normalizing In Vitro-In Vivo Conditions
8.1.3 Carrier-Mediated Transporters and PAMPA
8.2 CELL-BASED IN VITRO PERMEABILITY MODEL
8.2.1 Limitations of a Single-pH Measurement and Ways to Overcome Them
8.2.1.1 ABL-Limited Transport May Not Correlate with In Vivo Permeability
8.2.1.2 Paracellular Transport May Be Important for Low-Permeable Molecules
8.2.1.3 How to Extract PC from Papp in a Single-pH Permeability Measurement
8.2.1.4 How to Extract PC from Papp from Multiple-pH Permeability Measurement
8.2.2 Characteristic Paracellular Parameters in a Standardized Cell Culture
8.2.2.1 Model Equation to Determine Cell-Based In Vitro Paracellular Parameters
8.2.2.2 Refinement of the In Vitro Paracellular Permeability Parameters
8.3 IN SITU HUMAN JEJUNUM PERMEABILITY (HJP) MODEL
8.3.1 Model Equation to Determine HJP Paracellular Parameters
8.3.2 Refinement of the HJP Parameters
8.4 PASSIVE INTRINSIC PERMEABILITY COEFFICIENTS OF Caco-2 AND MDCK COMPARED
8.5 THEORY (STAGE 1): PARACELLULAR LEAKINESS AND SIZE EXCLUSION IN Caco-2, MDCK, AND 2/4/A1 CELL LINES
8.5.1 Selection of Paracellular Markers
8.5.2 Paracellular Model Nonlinear Regression Analysis
8.5.3 Iso-Paracellular Profiles
8.5.4 Ranking by Size Exclusion
8.5.5 Confirming the Filter Porosity Experimentally
8.5.5.1 Filter Permeability, Pf, in Caco-2 Assays
8.5.5.2 Determination of Filter Porosity
8.6 THEORY (STAGE 2): REGRESSION METHOD FOR IN VITRO CELLULAR PERMEABILITY
8.6.1 Two Stages of Analysis and the Dynamic Range Window (DRW)
8.6.2 Refinement of the In Vitro Cellular Permeability Parameters
8.7 CASE STUDIES OF CELL-BASED PERMEABILITY AS A FUNCTION OF PH
8.7.1 In Vitro Permeability Measurements Are Insufficiently Standardized
8.7.2 Pretreatment of In Vitro Permeability Measurements to Improve IVIVC
8.7.2.1 Treatment of the Two-pH Caco-2 Data to Determine "True" Cell Permeability
8.7.2.2 Treatment of the Multiple-pH Caco-2 Data to Determine "True" Cell Permeability
8.8 HUMAN JEJUNAL PERMEABILITY PREDICTED DIRECTLY FROM Caco-2/MDCK
8.8.1 Effective Human Jejunal Permeability Data Sources
8.8.2 Biophysical Model Regression Analysis of Human Jejunal Permeability
8.8.3 Refined Effective Surface Area Expansion Factor
8.8.4 Transport Analysis for Drugs in the Human Jejunum
8.8.4.1 Paracellular Route
8.8.4.2 ABL-Limited Transcellular Route
8.8.4.3 Transcellular Route
8.8.5 Polyethylene Glycol Permeability
8.8.6 The "Leakiness" of the Human Jejunum Compared with That of In Vitro Models
8.8.7 Applications of the Biophysical Model
8.8.8 Biophysical Model Summary
8.9 Caco-2/MDCK DATABASE AND ITS IN COMBO PAMPA PREDICTION
8.9.1 Caco-2/MDCK Database
8.9.2 In Combo Model Building Approach
8.9.3 Caco-2/MDCK Passive Permeability Prediction Model
REFERENCES
9: PERMEABILITY: BLOOD-BRAIN BARRIER
9.1 THE BLOOD-BRAIN BARRIER: A KEY ELEMENT FOR DRUG ACCESS TO THE CENTRAL NERVOUS SYSTEM
9.2 THE BLOOD-BRAIN BARRIER
9.2.1 The BBB Environment
9.2.2 Lipid Composition of the BBB
9.2.3 Transporters at the BBB
9.3 NONCELLULAR BBB MODELS
9.3.1 log POCT
9.3.2 ? log P
9.3.3 Air-Water Partition Coefficients and Molecular Cross-Sectional Area
9.3.4 Black Lipid Membrane (BLM) Models
9.3.5 PAMPA-BBB
9.3.6 Selectivity Coefficients (SC) and the Solubility-Diffusion Theory
9.4 IN VITRO BBB CELL-BASED MODELS
9.5 IN VIVO BBB MODELS
9.5.1 Brain/Plasma Ratio: Kp (also Known as B/P and log BB)- Extent of Penetration
9.5.2 Mouse Brain Uptake Assay (MBUA)
9.5.3 Rodent In Situ Brain Perfusion: Rate of Transport
9.5.4 Microdialysis
9.6 PARADIGM SHIFT
9.6.1 Extent of Brain Penetration (Concentration in the Brain Extracellular Fluid, ECF)
9.6.2 Equilibration Half-Time in Physiologically Based Pharmacokinetics (PBPK)
9.6.3 Unbound Fractions in Brain and Plasma
9.6.4 Brain Penetration Classification (BPC)
9.7 IN SILICO BBB MODELS
9.8 BIOPHYSICAL ANALYSIS OF IN VITRO ENDOTHELIAL CELL MODELS
9.8.1 Computational Method
9.8.2 Selection of In Vitro BMEC Permeability Data from Various Laboratories
9.8.3 Extracting Aqueous Hydrodynamic Contributions from Measured Permeability
9.8.4 In Vitro BMEC Transendothelial and Intrinsic Permeability, PC and P0
9.8.5 Dynamic Range Window (DRW)
9.8.6 Results of Paracellular and Aqueous Boundary Layer Permeability Analysis
9.8.6.1 Transporter Effects
9.8.6.2 Refined Paracellular Parameters
9.8.6.3 Ranking by Leakiness
9.8.6.4 Size Exclusion
9.8.7 Transendothelial Cell Membrane Permeability Analysis
9.8.7.1 IVIVC Analysis with Uncorrected (Pe) Data
9.8.7.2 Improved IVIVC Analysis Using P0 Data
9.9 IN SITU BRAIN PERFUSION ANALYSIS OF FLOW
9.9.1Flow-Limit Window (FLW), Where PS Cannot Be Determined from Kin
9.9.2 Approaches to Overcome the Possible Limitation of the Crone-Renkin Equation
9.9.3 Is There an ABL at the BBB?
9.9.4 The pH-CRE (Crone-Renkin Equation) Flow Correction Method
9.9.5 Paracellular Permeability at the BBB
9.9.6 Capillary versus Planar Hydrodynamic Effects in Permeability Assays
9.9.7 Effective BBB Permeability versus Lipophilicity
9.9.8 In Situ Rat Brain Perfusion Measurement as a Function of pH
9.9.9 Determined Mean Cerebrovascular Flow Velocity: Literature Comparisons
9.9.10 pH-CRE Method Recommendations: Maprotiline at pH 7.4 and 6.5
9.10 IN COMBO PAMPA-BBB MODEL FOR PASSIVE BBB PERMEABILITY
9.10.1 In Silico Model Building Software and the In Combo Strategy
9.10.2 Linear Free Energy Relations (LFER) Descriptors
9.10.3 PAMPA-BBB Selectivity Coefficients by Charge Classes
9.10.4 Abraham LFER and
9.10.5 "External" Set Comparisons
REFERENCES
10: SUMMARY AND SOME SIMPLE APPROXIMATIONS
INDEX

Systemvoraussetzungen

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