Automated Solution for the characterization of transporter-based hepatic interactions of drug candidates and metabolites in B-CLEAR® (sandwich-cultured hepatocytes) using the Hamilton MICROLAB® STAR

Abstract:


Hepatic uptake, first-pass metabolism, and biliary excretion are critical parameters in determining the success or failure of a drug candidate. In vitro methods evaluating the hepatic metabolism and induction potential of drug candidates have been extensively utilized.  More recently, the roles of hepatic uptake, biliary excretion, biliary clearance and intracellular concentration of drug candidates are being evaluated. Because the number of hepatic transporters may equal or exceed the number of metabolic enzymes, an in vitro technology expressing the full complement of hepatic uptake and efflux transporters, localized and functioning similar to in vivo, is critical for evaluation of drug candidates. B-CLEAR®, Qualyst’s patented technology, is used to answer questions on hepatic uptake, biliary excretion, and intracellular concentration determination.   Automation improves the cost, labor, and time efficiencies in B-CLEAR® experiments, and automation can enable researchers to conduct secondary or small-scale screens in drug discovery and development. This application note describes a protocol for the automation of studies to evaluate the hepatobiliary disposition (uptake, efflux, and biliary clearance) of a drug candidate using B-CLEAR® technology from Qualyst on a MicroLab® Sequential Transfer and Aliquoting Robot (ML STAR) (Figure 1) from Hamilton Robotics.

Introduction:


Predictions of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of compounds in pharmaceutical development are essential aspects of the drug discovery and drug development processes. Sandwich-cultured hepatocytes (SCH) (Figure 2) form extensive, functional bile canalicular networks and maintain the expression, localization, and function of uptake and efflux transporters relative to hepatocytes in vivo.1 These canalicular networks, or bile pockets, are isolated from the media by tight junctions between cells. In the presence of buffer containing calcium, [Plus (+) Buffer], the integrity of the tight junctions is maintained.
However, in the presence of buffer not containing calcium, [Minus (-) Buffer], the tight junctions

 

Figure 2: Phase contrast image of 24-well B-CLEAR® sandwich-cultured rat hepatocytes (SCRH). Bile canalicular networks are the light areas surrounding the peripheries of the cell (left panel). Fluorescent image of 5,(6)-carboxy-2’,7’dichlorofluorescein (CDF) accumulation in bile canalicular networks of 24-well B-CLEAR® SCRH (right panel).
open and release the content of the bile pockets into the media. B-CLEAR® technology (US Patent Nos. 6,780,580; 7,604,934; 7,682,781) uses the modulation of tight junctions in SCH to predict the in vivo hepatobiliary disposition (hepatic uptake, biliary excretion, and biliary clearance), transporter-based hepatic drug-drug interactions, and potential drug-induced hepatotoxicity.2,3,4  The combination of in vivo – in vitro correlation in biliary clearance (Clbiliary) (Figure 3) and accurate prediction of intracellular concentration, makes B-CLEAR® an excellent methodology for predicting hepatic transporter-based drug-drug interactions.5,6,7                 


Until recently, B-CLEAR® experiments were exclusively performed manually in 6- and 24-well formats. B-CLEAR® experiments are complex in nature, involving parallel timed incubations in Plus (+) and Minus (-) Buffers, and may include multiple substrates at varying concentrations in the presence or absence of potential inhibitors. Hamilton Company provides world class automation solutions for a variety of applications with increased robustness, flexibility, precision, and accuracy using its unique Compressed O-Ring Expansion (CO-RE) technology. This application note demonstrates the automation capabilities of the Hamilton ML STAR and how automation can be used to execute B-CLEAR® experiments with a more reproducible and less labor intensive approach, reducing potential operator error and fatigue in complex studies and facilitating technology transfer.

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