title: Predicted metabolic drug clearance with increasing adult age.
abstract: OBJECTIVE
  To determine the effect of increasing adult age on predicted metabolic drug clearance.
  
  
  METHODS
  Predicted metabolic drug clearances (CLPT ) were determined using in vitro-in vivo extrapolation coupled with physiological-based pharmacokinetic modelling and simulation (IVIVE-PBPK) in Simcyp®. Simulations were conducted using CYP-selective 'probe' drugs with subjects in 5 year age groups (20-25 to 90-95 years). CLPT values were compared with human pharmacokinetic data stratified according to age (young = 20-40 years and elderly = 65-85 years) and gender. Age-related changes in the physiological parameters used for IVIVE of CLPT were described.
  
  
  RESULTS
  Predicted metabolic drug clearances decreased with increasing adult age to approximately 65-70 years: caffeine from 1.5 to 1.0 ml min(-1)  kg(-1) (a 33% decrease), S-warfarin from 0.100 to 0.064 ml min(-1)  kg(-1) (36%), S-mephenytoin from 4.1 to 2.5 ml min(-1)  kg(-1) (39%), desipramine from 10.6 to 7.3 ml min(-1)  kg(-1) (31%) and midazolam from 5.4 to 3.9 ml min(-1)  kg(-1) (27%). Except for S-mephenytoin, predictions were within 3.5-fold of clearances from clinical studies when stratified by age and gender. A trend towards higher CLPT was observed in females, but this was only statistically significant in larger virtual trials. Physiological parameters that determine CLPT decreased with increasing adult age: mean microsomal protein g(-1) of liver, liver weight, hepatic blood flow and human serum albumin concentration.
  
  
  CONCLUSIONS
  Decreased metabolic clearance in the elderly was predicted by Simcyp® and was generally consistent with limited clinical data for four out of five drugs studied and the broader literature for drugs metabolized by CYP enzymes. IVIVE-PBPK may be increasingly useful in predicting metabolic drug clearance in the elderly.
authors.affiliation: Department of Clinical Pharmacology, Flinders University and Flinders Medical Centre, Adelaide, SA, Australia. tom.polasek@flinders.edu.au
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Polasek
authors.forename: Farhaan
authors.initials: F
authors.lastname: Patel
authors.forename: Berit P
authors.initials: BP
authors.lastname: Jensen
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Sorich
authors.forename: Michael D
authors.initials: MD
authors.lastname: Wiese
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Doogue
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000378:metabolism*; D002110:Caffeine / Q000493:pharmacokinetics*; D003198:Computer Simulation; D003891:Desipramine / Q000493:pharmacokinetics*; D005260:Female; D006801:Humans; D008297:Male; D008617:Mephenytoin / Q000493:pharmacokinetics*; D008657:Metabolic Clearance Rate; D008874:Midazolam / Q000493:pharmacokinetics*; D008875:Middle Aged; D008954:Models, Biological; D014859:Warfarin / Q000493:pharmacokinetics*
chemical_list: D002110:Caffeine; D014859:Warfarin; D008617:Mephenytoin; D008874:Midazolam; D003891:Desipramine