Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulations. Sheila Annie Peters
CONCLUSIONS REFERENCES 17 ABSORPTION‐RELATED APPLICATIONS OF PBPK MODELING 17.1 INTRODUCTION 17.2 IN VITRO – IN VIVO DISCONNECT, PARAMETER NON‐IDENTIFIABILITY AND THE IMPORTANCE OF IDENTIFYING FACTORS LIMITING ABSORPTION THROUGH A DECONVOLUTION OF THE MECHANISMS CONTRIBUTING TO GUT BIOAVAILABILITY 17.3 NON‐REGULATORY INTERNAL APPLICATIONS OF PBPK MODELING AND SIMULATIONS 17.4 REGULATORY APPLICATIONS OF PBPK MODELING AND SIMULATIONS 17.5 CONCLUSIONS REFERENCES 18 REGULATORY GUIDELINES ON THE REPORTING OF PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELING ANALYSIS 18.1 INTRODUCTION 18.2 FOOD AND DRUG ADMINISTRATION (FDA) GUIDELINES 18.3 EUROPEAN MEDICINES AGENCY (EMA) GUIDELINES 18.4 COMPARISON OF FDA AND EMA GUIDELINES 18.5 RISK‐INFORMED EVIDENTIARY FRAMEWORK TO ASSESS PBPK MODEL CREDIBILITY 18.6 DRUG MODEL VERIFICATION OF LOCALLY ACTING PRODUCTS (LAPs) REFERENCES 19 RESOLVING THE CHALLENGES TO ESTABLISHING CONFIDENCE IN PBPK MODELS 19.1 INTRODUCTION 19.2 REQUIREMENTS FOR DEVELOPING MECHANISTICALLY CREDIBLE PBPK MODELS FOR THE THREE BROAD CATEGORIES OF APPLICATIONS 19.3 CHALLENGES TO DEVELOPING MECHANISTICALLY CREDIBLE PBPK MODELS AND CONSEQUENCES 19.4 RESOLVING THE CHALLENGES TO DEVELOPING MECHANISTICALLY CREDIBLE PBPK MODELS 19.5 TOTALITY OF EVIDENCE 19.6 CONCLUSIONS REFERENCES 20 EPILOGUE 20.1 PBPK MODELING SUCCESSES 20.2 CHALLENGES 20.3 MEETING THE CHALLENGES 20.4 FUTURE DIRECTIONS FOR PBPK MODELING REFERENCES
11 SECTION III: CASE STUDIES OF PBPK APPLICATIONS IN THE PHARMACEUTICAL INDUSTRY CASE STUDY 1: HYPOTHESIS TESTING (SOLUBILITY) S1.1 IDENTIFICATION OF HIGHER IN VIVO SOLUBILITY THAN MEASURED IN VITRO REFERENCES CASE STUDY 2: HYPOTHESIS TESTING (GASTRIC EMPTYING) S2.1 IDENTIFICATION OF GASTRIC EMPTYING-LIMITED ORAL DRUG ABSORPTION REFERENCES CASE STUDY 3: HYPOTHESIS TESTING (INTESTINAL LOSS) S3.1 IDENTIFICATION OF INTESTINAL LOSS REFERENCES CASE STUDY 4: PBPK/PD S4.1 KEY QUESTION S4.2 BACKGROUND S4.3 OBJECTIVES S4.4 DATA S4.5 MODELING STRATEGY S4.6 SENSITIVITY ANALYSIS S4.7 CONCLUSION REFERENCES CASE STUDY 5: DRUG–DRUG INTERACTION (INHIBITION) S5.1 KEY QUESTION S5.2 BACKGROUND S5.3 OBJECTIVES S5.4 DATA S5.5 MODELING STRATEGY S5.6 SENSITIVITY ANALYSIS S5.7 LEARNINGS REFERENCES CASE STUDY 6: DRUG–DRUG INTERACTION (INDUCTION) S6.1 DRUG–DRUG INTERACTION RISK ASSESSMENT FOR MIDAZOLAM DUE TO CYP3A INDUCTION BY RIFAMPICIN REFERENCES CASE STUDY 7: GENETIC POLYMORPHISM S7.1 IMPACT OF GENETIC POLYMORPHISM ON THE PHARMACOKINETICS OF RISPERIDONE S7.2 Results REFERENCES CASE STUDY 8: PEDIATRIC EXTRAPOLATION S8.1 IMPACT OF UGT2B7 MATURATION ON THE PHARMACOKINETICS OF MORPHINE S8.2 CONCLUSION REFERENCES CASE STUDY 9: PREGNANCY S9.1 IMPACT OF PREGNANCY ON THE PHARMACOKINETICS OF METRONIDAZOLE S9.2 RESULTS REFERENCES CASE STUDY 10: HEPATIC IMPAIRMENT S10.1 IMPACT OF HEPATIC IMPAIRMENT ON THE PHARMACOKINETICS OF MIDAZOLAM AND LIDOCAINE S10.2 MODELING STRATEGY S10.3 RESULTS REFERENCES CASE STUDY 11: RENAL IMPAIRMENT S11.1 IMPACT OF RENAL IMPAIRMENT ON