title: Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.
abstract: The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.
authors: Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States.
authors: Chelsea M
authors: CM
authors: Hosey
authors: Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States.
authors: Leslie Z
authors: LZ
authors: Benet
mesh_terms: D000818:Animals; D018938:Caco-2 Cells; D003198:Computer Simulation; D004285:Dogs; D006801:Humans; D007668:Kidney / Q000378:metabolism; D007741:Labetalol / Q000493:pharmacokinetics; D061985:Madin Darby Canine Kidney Cells; D008962:Models, Theoretical; D010539:Permeability; D015215:Zidovudine / Q000493:pharmacokinetics
chemical_list: D015215:Zidovudine; D007741:Labetalol
keywords: BDDCS; biliary; drug elimination; metabolism; permeability; renal