title: An algorithm for evaluating potential tissue drug distribution in toxicology studies from readily available pharmacokinetic parameters.
abstract: Having an understanding of drug tissue accumulation can be informative in the assessment of target organ toxicities; however, obtaining tissue drug levels from toxicology studies by bioanalytical methods is labor-intensive and infrequently performed. Additionally, there are no described methods for predicting tissue drug distribution for the experimental conditions in toxicology studies, which typically include non-steady-state conditions and very high exposures that may saturate several processes. The aim was the development of an algorithm to provide semiquantitative and quantitative estimates of tissue-to-plasma concentration ratios (Kp ) for several tissues from readily available parameters of pharmacokinetics (PK) such as volume of distribution (Vd ) and clearance of each drug, without performing tissue measurement in vivo. The computational approach is specific for the oral route of administration and non-steady-state conditions and was applied for a dataset of 29 Genentech small molecules such as neutral compounds as well as weak and strong organic bases. The maximum success rate in predicting Kp values within 2.5-fold error of observed Kp values was 82% at low doses (<100 mg/kg) in preclinical species. Prediction accuracy was relatively lower with saturation at high doses (≥100 mg/kg); however, an approach to perform low-to-high dose extrapolations of Kp values was presented and applied successfully in most cases. An approach for the interspecies scaling was also applied successfully. Finally, the proposed algorithm was used in a case study and successfully predicted differential tissue distribution of two small-molecule MET kinase inhibitors, which had different toxicity profiles in mice. This newly developed algorithm can be used to predict the partition coefficients Kp for small molecules in toxicology studies, which can be leveraged to optimize the PK drivers of tissue distribution in an attempt to decrease drug tissue level, and improve safety margins.
authors.affiliation: Consultant, Québec city, Québec, Canada.
authors.forename: Patrick
authors.initials: P
authors.lastname: Poulin
authors.forename: Donna M
authors.initials: DM
authors.lastname: Dambach
authors.forename: Dylan H
authors.initials: DH
authors.lastname: Hartley
authors.forename: Kevin
authors.initials: K
authors.lastname: Ford
authors.forename: Frank-Peter
authors.initials: FP
authors.lastname: Theil
authors.forename: Eric
authors.initials: E
authors.lastname: Harstad
authors.forename: Jason
authors.initials: J
authors.lastname: Halladay
authors.forename: Edna
authors.initials: E
authors.lastname: Choo
authors.forename: Jason
authors.initials: J
authors.lastname: Boggs
authors.forename: Bianca M
authors.initials: BM
authors.lastname: Liederer
authors.forename: Brian
authors.initials: B
authors.lastname: Dean
authors.forename: Dolores
authors.initials: D
authors.lastname: Diaz
mesh_terms: D000465:Algorithms; D000818:Animals; D004285:Dogs; D051379:Mice; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism*; D051381:Rats; D054852:Small Molecule Libraries / Q000493:pharmacokinetics*; D014018:Tissue Distribution
chemical_list: D004364:Pharmaceutical Preparations; D054852:Small Molecule Libraries
keywords: ADME; DMPK; disposition; distribution; partition coefficients; pharmacokinetics; safety assessment; tissue distribution; toxicology; volume of distribution