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  (BBSRC CASE DTP) Translational modelling of zonal distribution of hepatic transporters and glucuronidation enzymes and their interplay within physiologically-based paradigms


   Faculty of Biology, Medicine and Health

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  Dr Aleksandra Galetin, Prof A Rostami  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project

Population-based systems biology approaches using virtual populations are being used increasingly to model prospectively hepatic disposition and drug-drug interactions of co-administered drugs both in healthy individuals and in individuals with different diseases. Despite the utility of these mechanistic physiologically-based modelling approaches, the efforts are challenged by the complexity of underlying biology involving a multiplicity of transporters/enzymes and the lack of protein expression, turnover and functional activity data within different zones of the liver lobules to support such modelling.

The aim of this project is to use state-of-the-art experimental approaches (including targeted proteomics, in vitro ‘organ-on-a-chip’ systems, LC-MS/MS, immunoblotting and SiRNA) in conjunction with mechanistic modelling to address existing knowledge gaps in hepatic drug disposition involving non-P450 mediated metabolism (e.g., glucuronidation via UGTs) coupled with transport of the corresponding metabolites. The primary focus will be on characterisation of zonal distribution of UGTs and plasma membrane transporters in the human liver tissue samples and samples from different in vitro hepatocyte cellular platforms, including microfluidic devices such as ‘organ-on-a-chip’. In addition, the project will focus on characterising the turnover of hepatic UGT enzymes and drug transporters (e.g., OATP1B1) which is crucial for prospective evaluation of the risk of drug-drug interactions when changes in the level of the enzyme/transporter are an important contributing factor (e.g., induction of protein synthesis). Data obtained will be applied to refine the existing physiologically-based pharmacokinetic liver models to improve translation to in vivo. The proposed inter-disciplinary and model-driven approach has strong foundations and builds upon previous and ongoing research in our group.

Weblink to Dr Aleksandra Galetin
https://www.research.manchester.ac.uk/portal/Aleksandra.Galetin.html

Weblink to Prof. Amin Rostami
https://www.research.manchester.ac.uk/portal/amin.rostami.html

Simcyp
https://www.certara.com/software/pbpk-modeling-and-simulation/

Funding Notes

This is a CASE studentship is to be funded by BBSRC. If you are interested in this project, please make contact with the Principal Supervisor to arrange to discuss the project further asap. You MUST also submit an online application form - full details on how to apply here www.manchester.ac.uk/bbsrcdtpstudentships.
Please note this project has a closing date of 24 November, a week later than other BBSRC projects.

Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.

References

1) Galetin A. Rationalizing underprediction of drug clearance from enzyme and transporter kinetic data: from in vitro tools to mechanistic modeling. Methods Mol Biol. 2014;1113:255-88
2) Galetin A, Zhao P, Huang SM. Physiologically Based Pharmacokinetic Modeling of Drug Transporters to Facilitate Individualized Dose Prediction. J Pharm Sci. 2017 106(9):2204-2208
3) Almond LM, Mukadam S, Gardner I, Okialda K, Wong S, Hatley O, Tay S, Rowland-Yeo K, Jamei M, Rostami-Hodjegan A, Kenny JR. Prediction of Drug-Drug Interactions Arising from CYP3A induction Using a Physiologically Based Dynamic Model. Drug Metab Dispos. 2016;44 (6):821-32.
4) Harwood MD, Achour B, Russell MR, Carlson GL, Warhurst G and Rostami-Hodjegan A. Application of an LC-Ms/MS method for the simultaneous quantification of human intestinal transporter proteins abundance using a QconCAT technique. J Pharm. Biomed. Anal., 2015, 110, 27-33.