Cerebrospinal fluid can be used as a surrogate to assess brain exposures of breast cancer resistance protein and P-glycoprotein substrates.

The objectives of the study were to characterize the selectivity of dantrolene to breast cancer resistance protein (Bcrp) and to evaluate whether cerebrospinal fluid (CSF) can be used as a surrogate to assess brain exposures of BCRP and P-glycoprotein (Pgp) substrates. The impact of Bcrp and Pgp on dantrolene exposures in brain and CSF was examined in Bcrp and Mdr1a/1b knockout mice and was further investigated in wild-type mice in the presence of the Bcrp inhibitor (3S,6S,12aS)-1,2,3,4,6,7,12,12a-octahydro-9-methoxy-6-(2-methylpropyl)-1,4-dioxopyrazino[1',2':1,6]pyrido[3,4-b]indole-3-propanoic acid 1,1-dimethylethyl ester (Ko143), the Pgp inhibitor 6-[(2S,4R,6E)-4-methyl-2-(methylamino)-3-oxo-6-octenoic acid]-7-l-valine-cyclosporine A (PSC833), and the dual inhibitor N-(4-[2-(1,2,3,4-tetrahydro-6,7-dimethoxy-2-isoquinolinyl)ethyl]-phenyl)-9,10-dihydro-5-methoxy-9-oxo-4-acridine carboxamide (GF120918). The effect of Bcrp and Pgp on digoxin exposures in brain and CSF was investigated in wild-type mice in the presence of the inhibitors. In vivo studies showed dantrolene exposures in brain and CSF, but not the blood, increased in Bcrp(-/-) and Mdr1a/1b(-/-)/Bcrp(-/-) mice, or in the presence of the Bcrp inhibitors Ko143 or GF120918. Inhibition of Pgp by GF120918 and PSC833 significantly increased digoxin exposures in brain, CSF, and blood to a lesser extent. Results from the present study demonstrated that inhibition of Bcrp and Pgp increased not only the exposures of dantrolene and digoxin in brain, but also the exposures in CSF. In addition, the change of exposures in CSF reflected the changes in brain. The present study strongly suggests that the dantrolene and digoxin exposures in CSF are primarily determined by the rapid transport from brain to CSF, and inhibition of Bcrp and Pgp exhibits little impact on using CSF as surrogates to assess brain exposures of Bcrp and Pgp substrates.

Monoclonal antibody exposure in rat and cynomolgus monkey cerebrospinal fluid following systemic administration.

BACKGROUND: Many studies have focused on the challenges of small molecule uptake across the blood-brain barrier, whereas few in-depth studies have assessed the challenges with the uptake of antibodies into the central nervous system (CNS). In drug development, cerebrospinal fluid (CSF) sampling is routinely used as a surrogate for assessing CNS drug exposure and biomarker levels. In this report, we have studied the kinetic correlation between CSF and serum drug concentration-time profiles for five humanized monoclonal antibodies in rats and cynomolgus monkeys and analyzed factors that affect their CSF exposure. RESULTS: Upon intravenous (IV) bolus injection, antibodies entered the CNS slowly and reached maximum CSF concentration ( CSF T max ) in one to several days in both rats and monkeys. Antibody serum and CSF concentration-time curves converged until they became parallel after CSF T max was reached. Antibody half-lives in CSF ( CSF t ½ ) approximated their serum half-lives ( serum t ½ ). Although the intended targets of these antibodies were different, the steady-state CSF to serum concentration ratios were similar at 0.1-0.2% in both species. Independent of antibody target and serum concentration, CSF-to-serum concentration ratios for individual monkeys ranged by up to tenfold from 0.03 to 0.3%. CONCLUSION: Upon systemic administration, average antibodies CSF-to-serum concentration ratios in rats and monkeys were 0.1-0.2%. The CSF t ½ of the antibodies was largely determined by their long systemic t ½ ( systemic t ½ ).

MARS: bringing the automation of small-molecule bioanalytical sample preparations to a new frontier.

BACKGROUND: In recent years, there has been a growing interest in automating small-molecule bioanalytical sample preparations specifically using the Hamilton MicroLab(®) STAR liquid-handling platform. In the most extensive work reported thus far, multiple small-molecule sample preparation assay types (protein precipitation extraction, SPE and liquid-liquid extraction) have been integrated into a suite that is composed of graphical user interfaces and Hamilton scripts. Using that suite, bioanalytical scientists have been able to automate various sample preparation methods to a great extent. However, there are still areas that could benefit from further automation, specifically, the full integration of analytical standard and QC sample preparation with study sample extraction in one continuous run, real-time 2D barcode scanning on the Hamilton deck and direct Laboratory Information Management System database connectivity. RESULTS: We developed a new small-molecule sample-preparation automation system that improves in all of the aforementioned areas. CONCLUSION: The improved system presented herein further streamlines the bioanalytical workflow, simplifies batch run design, reduces analyst intervention and eliminates sample-handling error.