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  Systems Pharmacology Models of Druggable Targets and Disease Mechanisms


   Babraham Institute Graduate Programme

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Dr N Le Novère  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project

We are looking for an exceptional PhD candidate to work on systems pharmacology models, as part of a collaboration between the Babraham Institute (BI, Le Novère), the European Bioinformatics Institute (EBI, Hermjakob) and the pharmaceutical company GlaxoSmithKline (GSK, Curucull-Sanchez).

One of the major challenges of drug discovery is to demonstrate the efficacy of a potential new drug. This goes beyond the development of a potent molecule - it also implies a good understanding of the biological context, how it relates to a particular disease, and the drug's mechanism of action. The availability of relevant Systems Pharmacology models can therefore have a significant impact. The most comprehensive repository of Systems Biology models in machine readable language is BioModels Database, created by Le Novère and maintained at the EBI. In spite of its extensive collection, BioModels Database only covers a fraction of the Systems Pharmacology models described in the literature. In addition, no analysis has been performed on how they map to druggable targets and/or disease mechanisms. The candidate will: 1) Use state-of-the-art text-mining methods to extract and analyse the space of Systems Pharmacology models currently described in the literature, with particular emphasis to their relevance to druggable targets and disease mechanisms; 2) Identify the models offering the best opportunities for the discovery of new drugs, and incorporate them into BioModels Database; 3) Explore and assess the applicability of those models to real drug development cases, evaluating their quality, advantages, caveats, overlaps, gaps and impact on the demonstration of drug efficacy against specific indications.

The candidate must have an extensive knowledge of molecular biology and pharmacology, and solid basis in numerical analysis and statistics. Advanced familiarity with data representation and programming skills will also be desirable.

 About the Project