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Transporter Knockdowns for In Vitro Drug Interaction Monitoring

$214,696R43FY2008FDFDA

Pharmaron (Exton) Lab Services Llc, Exton PA

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Abstract

[unreadable] DESCRIPTION (provided by applicant): In vitro assays that reliably correlate with observed clinical DDI outcomes would facilitate drug development and reduce reliance on extensive animal testing. Immortal human in- testinal Caco-2 cells are widely used by pharmaceutical companies to study drug trans- port, but interpretation is hampered by the presence of multiple drug efflux transporters. Chemical inhibitors of drug transporters are available and are used to partially dissect transport mechanisms. Unfortunately, currently available inhibitors are only partially specific, creating ambiguities in interpretation. Knockdown of gene expression by interfering RNA is much more specific; therefore, transport assays employing Caco-2 cells in which a given transporter has been knocked down by continuous presence of RNAi targeted to that message have the potential of yielding specific and unambiguous transport results. We propose to use lentiviral-mediated short hairpin RNAi constructs targeted at drug efflux transporter sequences to construct Caco-2 knockdown cell lines and appropriate controls and to characterize the differentiation state and drug transport properties of the constructs with the goal of creating improved cell lines for in vitro drug transport assays. We anticipate providing assays employing these human knockdowns that will be compliant with the types of guidelines being discussed in a recent FDA guidance. PUBLIC HEALTH RELEVANCE: The intent of this project is to develop a new standard of in vitro research tools that provide superior prediction of drug-drug interactions (DDIs) in humans. In 1988, it was estimated that roughly 2.8% of all hospitalizations were a result of DDIs. If successful, the results of this research program will lead to a rapid and predictable test system for DDIs that will benefit the drug research community and provide better DDI prediction in man. [unreadable] [unreadable] [unreadable]

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