These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: In vitro-to-in vivo prediction of P-glycoprotein-based drug interactions at the human and rodent blood-brain barrier.
    Author: Hsiao P, Bui T, Ho RJ, Unadkat JD.
    Journal: Drug Metab Dispos; 2008 Mar; 36(3):481-4. PubMed ID: 18057117.
    Abstract:
    In vitro inhibition of P-glycoprotein (P-gp) expressed in cells is routinely used to predict the potential of in vivo P-gp drug interactions at the human blood-brain barrier (BBB). The accuracy of such predictions has not been confirmed because methods to quantify in vivo P-gp drug interactions at the human BBB have not been available. With the development of a noninvasive positron emission topography (PET) imaging method by our laboratory to determine P-gp-based drug interactions at the human BBB, an in vitro-in vivo comparison is now possible. Therefore, we developed a high throughput cell-based assay to determine the potential of putative P-gp inhibitors [including cyclosporine A (CsA)] to inhibit (EC(50)) the efflux of verapamil-bodipy, a model P-gp substrate. LLCPK1-MDR1 cells, expressing recombinant human P-gp, or control cells lacking P-gp (LLCPK1) were used in our assay. Using this assay, quinine, quinidine, CsA, and amprenavir were predicted to be the most potent P-gp inhibitors in vivo at their respective therapeutic maximal unbound plasma concentrations. The in vitro EC(50) of CsA (0.6 microM) for P-gp inhibition was virtually the same as our previously determined in vivo unbound EC(50) at the rat BBB (0.5 microM). Moreover, at 2.8 microM CsA (total blood concentration), our in vitro data predicted an increase of 129% in [(11)C]verapamil distribution into the human brain, a value similar to that observed by us (79%) using PET. These data suggest that our high throughput cell assay has the potential to accurately predict P-gp drug interactions at the human BBB.
    [Abstract] [Full Text] [Related] [New Search]