This is a list of projects hosted by the Cambridge Mathematics Placements site. Projects should be aimed at students working in the Faculty of Mathematics. To remove a listing, please contact Jacob Rasmussen
- Enhanced Decision Making in Drug Discovery
- New methods for genetic analysis
- Statistical analysis of biotherapeutic datasets to facilitate early ‘Critical Quality Attribute’ characterization.
- Deblurring with imperfectly known blurring kernels and applications in microscopy
Enhanced Decision Making in Drug Discovery
| Contact Name | Stephen Ashman |
| Contact Email | stephen.ashman@gsk.com |
| Company Name | GlaxoSmithKline |
| Address | GlaxoSmithKline Medicines Research Centre, Gunnels Wood Road, Stevenage, SG1 2NY |
| Period of the Project | 8 weeks |
| Project Open to | Part III (master's) students, PhD Students |
| Deadline to Register Interest | |
| Brief Description of the Project | This project will explore the way that scientists make decisions at key points during the Antibody drug discovery process. Program teams generate many different types of data during the drug discovery process: structure/amino acid sequence of the molecule, affinity for target, functional potency, mode of binding and numerous parameters describing the stability and manufacturability of the molecule. Each team needs to make choices about which molecules to progress on the basis of their experience of which attributes predict clinical success. Whilst experienced scientists make these decisions they are likely to be subject to a range of cognitive biases and challenged by the need to weight parameters appropriately and take account of the characteristic variance of each data type. The goal of the project would be to combine best practise in human decision-making heuristics with any notable new findings in an accessible tool that applies this standard consistently whilst providing teams with powerful visualisations describing the data supporting these decisions and recording the criteria and evidence for them. |
| Skills Required | An interest in the application of data science to drug discovery and strong data visualisation skills. |
| Skills Desired | Interest in decision theory and ability to code in R or Python. |
New methods for genetic analysis
| Contact Name | Simon Thornber |
| Contact Email | Simon.j.thornber@gsk.com |
| Company Name | GlaxoSmithKline - R&D Tech |
| Address | Gunnels Wood Road, Stevenage, Hertfordshire, SG1 2NY, UK |
| Period of the Project | Same as the other GSK proposals (over summer) |
| Project Open to | Part III (master's) students |
| Deadline to Register Interest | |
| Brief Description of the Project | The cost of DNA sequencing has now reached a level where it is economically viable for large scale sequencing programmes of thousands of volunteers to be undertaken. These data sets typically consist of patients genetic data, and a list of characteristics known as a ‘phenotype’. These data sets are then analysed using a technique known as a Genome wide association study (GWAS), to identify phenotypic characteristics that associate with genetics. With the richness of data available today, we would like to investigate alternative analysis approaches for these data sets. These approaches can take advantage the fact that multiple phenotypes may be linked (e.g. Body Mass Index, and resting heart rate), and that the data is on a scale rather than bucketed into “has phenotype” or “does not have phenotype”. This project would require investigation into other methods that have already been published, before proposing and designing new analysis approaches. |
| Skills Required | Data skills |
| Skills Desired | knowledge of Genetics |
Statistical analysis of biotherapeutic datasets to facilitate early ‘Critical Quality Attribute’ characterization.
| Contact Name | David Hilton |
| Contact Email | david.w.hilton@gsk.com |
| Company Name | Biopharm Process Research Group, GSK |
| Address | Biopharm Process Research Building 5 Ground Floor GSK Gunnels Wood Road Stevenage SG1 2NY |
| Period of the Project | 8 - 12 weeks |
| Project Open to | Undergraduates, Part III (master's) students, PhD Students |
| Deadline to Register Interest | |
| Brief Description of the Project | The Biopharm Process Research group is the first step on the route from newly discovered biotherapeutic drugs to a commercial product which can be administered to a patient. It is the group’s responsibility to screen candidate molecules for their developability, process fit and identify a suitable commercial cell line for their production. A key output from the group is the identification of Critical Quality Attributes (CQAs). These are chemical, physical or biological attributes of a molecule, or the system that produces it, which can be defined and monitored to ensure a product is within acceptable quality limits. This is an open-ended project in which the student is free to use novel strategies to analyse numerical and spectral datasets characterizing our molecules predicted attributes, and their intrinsic and in-process stability derived from techniques such as high performance chromatography, bio-layer interferometry and mass spectrometry. Using this analysis we plan to rapidly screen for CQAs and streamline our approach to CQA experimental characterization, whilst also uncovering uses for our datasets which hitherto remain unknown. |
| Skills Required | • Good knowledge of statistics and statistical computing techniques • Creativity and capability to initiate and deliver research project • Adaptability to interpret large and diverse datasets • Ability to work independently and take ownership of project • Communicate with scientists and engineers from a wide range of academic backgrounds |
| Skills Desired | • Familiarity with statistical computing software for instance JMP, Matlab, R, etc. • Familiarity with scripting languages for example Python, Perl, etc. |
Deblurring with imperfectly known blurring kernels and applications in microscopy
| Contact Name | Carola Schonleib |
| Contact Email | cbs21@cam.ac.uk |
| Company Name | |
| Address | |
| Period of the Project | 8-10 Weeks |
| Project Open to | |
| Deadline to Register Interest | |
| Brief Description of the Project | Available here. |
| Skills Required | Experience with MATLAB or Python |
| Skills Desired | Knowledge of inverse problems or numerical optimization |
