Skip to main content

PhD Studentship at Babraham - Systems Pharmacology Models of Druggable Targets and Disease Mechanisms



Our friendly neighbours at The Babraham Institute are looking for a PhD candidate to work on systems pharmacology models, as part of a collaboration between the Le Novère (Babraham), the Hermjakob (EMBL-EBI) and the pharmaceutical company GlaxoSmithKline. The Le Novère group uses quantitative computational models to understand cellular and molecular processes, and develop community services that facilitate research in computational systems biology (http://lenoverelab.org).

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.


  • Thiele I et al. A community-driven global reconstruction of human metabolism. Nat Biotechnol. 2013 Mar 3. Online advance publication.
  • Cucurull-Sanchez L et al. Relevance of systems pharmacology in drug discovery. Drug Discov Today. 2012 17: 665-670
  • Le Novère N et al. BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res. 2006 34: D689-D691.

For any further information or to express interest, please contact Nicolas Le Novère (n.lenovere (at) gmail.com) 

Comments

Popular posts from this blog

ChEMBL 34 is out!

We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains:         2,431,025 compounds (of which 2,409,270 have mol files)         3,106,257 compound records (non-unique compounds)         20,772,701 activities         1,644,390 assays         15,598 targets         89,892 documents Data can be downloaded from the ChEMBL FTP site:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release:  https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding vaccines). 71 out of the 882 newly added EMA drugs are only authorised by EMA, rather than from other regulatory bodies e.g.

New SureChEMBL announcement

(Generated with DALL-E 3 ∙ 30 October 2023 at 1:48 pm) We have some very exciting news to report: the new SureChEMBL is now available! Hooray! What is SureChEMBL, you may ask. Good question! In our portfolio of chemical biology services, alongside our established database of bioactivity data for drug-like molecules ChEMBL , our dictionary of annotated small molecule entities ChEBI , and our compound cross-referencing system UniChem , we also deliver a database of annotated patents! Almost 10 years ago , EMBL-EBI acquired the SureChem system of chemically annotated patents and made this freely accessible in the public domain as SureChEMBL. Since then, our team has continued to maintain and deliver SureChEMBL. However, this has become increasingly challenging due to the complexities of the underlying codebase. We were awarded a Wellcome Trust grant in 2021 to completely overhaul SureChEMBL, with a new UI, backend infrastructure, and new f

Accessing SureChEMBL data in bulk

It is the peak of the summer (at least in this hemisphere) and many of our readers/users will be on holiday, perhaps on an island enjoying the sea. Luckily, for the rest of us there is still the 'sea' of SureChEMBL data that awaits to be enjoyed and explored for hidden 'treasures' (let me know if I pushed this analogy too far). See here and  here for a reminder of SureChEMBL is and what it does.  This wealth of (big) data can be accessed via the SureChEMBL interface , where users can submit quite sophisticated and granular queries by combining: i) Lucene fields against full-text and bibliographic metadata and ii) advanced structure query features against the annotated compound corpus. Examples of such queries will be the topic of a future post. Once the search results are back, users can browse through and export the chemistry from the patent(s) of interest. In addition to this functionality, we've been receiving user requests for  local (behind the

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

New Drug Approvals - Pt. XVII - Telavancin (Vibativ)

The latest new drug approval, on 11th September 2009 was Telavancin - which was approved for the treatment of adults with complicated skin and skin structure infections (cSSSI) caused by susceptible Gram-positive bacteria , including Staphylococcus aureus , both methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) strains. Telavancin is also active against Streptococcus pyogenes , Streptococcus agalactiae , Streptococcus anginosus group (includes S. anginosus, S. intermedius and S. constellatus ) and Enterococcus faecalis (vancomycin susceptible isolates only). Telavancin is a semisynthetic derivative of Vancomycin. Vancomycin itself is a natural product drug, isolated originally from soil samples in Borneo, and is produced by controlled fermentation of Amycolatopsis orientalis - a member of the Actinobacteria . Telavancin has a dual mechanism of action, firstly it inhibits bacterial cell wall synthesis by interfering with the polymerization and cross-linking of peptid