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Mice that have been genetically humanized for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging and promising in vivo models for an improved prediction of the pharmacokinetic, drug–drug interaction and safety characteristics of compounds in humans. The specific advantages and disadvantages of these models should be carefully considered when using them for studies in drug discovery and development. Here, an overview on the corresponding genetically humanized and chimeric liver humanized mouse models described to date is provided and illustrated with examples of their utility in drug metabolism and toxicity studies. We compare the strength and weaknesses of the two different approaches, give guidance for the selection of the appropriate model for various applications and discuss future trends and perspectives.
Breast cancer resistance protein (BCRP) is expressed in various tissues, such as the gut, liver, kidney and blood brain barrier (BBB), where it mediates the unidirectional transport of substrates to the apical/luminal side of polarized cells. Thereby BCRP acts as an efflux pump, mediating the elimination or restricting the entry of endogenous compounds or xenobiotics into tissues and it plays important roles in drug disposition, efficacy and safety. Bcrp knockout mice (Bcrp−/−) have been used widely to study the role of this transporter in limiting intestinal absorption and brain penetration of substrate compounds. Here we describe the first generation and characterization of a mouse line humanized for BCRP (hBCRP), in which the mouse coding sequence from the start to stop codon was replaced with the corresponding human genomic region, such that the human transporter is expressed under control of the murine Bcrp promoter. We demonstrate robust human and loss of mouse BCRP/Bcrp mRNA and protein expression in the hBCRP mice and the absence of major compensatory changes in the expression of other genes involved in drug metabolism and disposition. Pharmacokinetic and brain distribution studies with several BCRP probe substrates confirmed the functional activity of the human transporter in these mice. Furthermore, we provide practical examples for the use of hBCRP mice to study drug-drug interactions (DDIs). The hBCRP mouse is a promising model to study the in vivo role of human BCRP in limiting absorption and BBB penetration of substrate compounds and to investigate clinically relevant DDIs involving BCRP.
NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (ƒₘCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate ƒₘCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human ƒₘCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.
Divided government is often thought of as causing legislative deadlock. I investigate the link between divided government and economic reforms using a novel data set on welfare reforms in US states between 1978 and 2010. Panel data regressions show that, under divided government, a US state is around 25% more likely to adopt a welfare reform than under unified government. Several robustness checks confirm this counter-intuitive finding. Case study evidence suggests an explanation based on policy competition between governor, senate, and house.
Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.