title: From preclinical to human--prediction of oral absorption and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach in an industrial setting: a workflow by using case example.
abstract: OBJECTIVE
  A case example is presented in which the physiologically based modeling approach has been used to model the absorption of a lipophilic BCS Class II compound predominantly metabolized by CYP3A4, and to assess the interplay of absorption related parameters with the drug-drug interaction (DDI) potential.
  
  
  METHODS
  The PBPK model was built in the rat using Gastroplus® to study the absorption characteristics of the compound. Subsequently relevant model parameters were used to predict the non-linear human PK observed during first-in-human study after optimizing the absorption model for colonic absorption, bile micelle solubilization and unbound fraction in gut enterocytes (fu(gut)) using SIMCYP® simulator. The model fitted absorption parameters were then used to assess the drug-drug interaction (DDI) potential of the test compound when administered along with multiple doses of a potent CYP 3A4 inhibitor, ketoconazole. The impact of fu(gut) in the extent of DDI was assessed using parameter sensitivity analysis.
  
  
  CONCLUSIONS
  After optimizing the preclinical model and taking into consideration bile micelle solubilization and colonic absorption, the non-linear pharmacokinetics of the test compound was satisfactorily predicted in man. Sensitivity analysis performed with the absorption parameter fu(gut) indicated that it could be an important parameter in predicting oral absorption. In addition, DDI simulations using SIMCYP® suggest that C(max) and AUC ratios may also be sensitive to the fu(gut) input in the model. Since fu(gut) cannot be measured experimentally, sensitivity analysis may help in assessing the importance of fu(gut) in human PK and DDI prediction using SIMCYP®.
authors.affiliation: Clinical Pharmacology Janssen Research and Development, Beerse, Belgium. vsinha@its.jnj.com
authors.forename: Vikash Kumar
authors.initials: VK
authors.lastname: Sinha
authors.forename: Jan
authors.initials: J
authors.lastname: Snoeys
authors.forename: Nancy Van
authors.initials: NV
authors.lastname: Osselaer
authors.forename: Achiel Van
authors.initials: AV
authors.lastname: Peer
authors.forename: Claire
authors.initials: C
authors.lastname: Mackie
authors.forename: Donald
authors.initials: D
authors.lastname: Heald
mesh_terms: D000042:Absorption / Q000187:drug effects / Q000502:physiology; D000284:Administration, Oral; D000818:Animals; D004345:Drug Industry / Q000379:methods / Q000639:trends*; D004347:Drug Interactions / Q000502:physiology*; D005544:Forecasting; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000008:administration & dosage / Q000378:metabolism*; D010829:Physiological Phenomena / Q000187:drug effects / Q000502:physiology; D051381:Rats; D012984:Software / Q000639:trends*; D057188:Workflow
chemical_list: D004364:Pharmaceutical Preparations