3D image analysis tool development for high-content screening

Objective

Recently both academic institutions and the pharmaceutical industry have identified 3 dimensional (3D) cellular model systems as one of the most important areas of future development in drug discovery programs and cell-based screening. High-content screening (HCS) platforms with large-scale automation and data analysis are extensively used in such programs. Automated image processing is a critical and rate-limiting step in HCS workflows that can be resolved by computational approaches. However, this has currently only been approached in a 2D manner and would benefit hugely from the ability to extend into 3D analyses.

I plan to develop a 3D image processing-statistical framework with emphasis on 3D segmentation that can be highly useful for numerous researchers working in biomedical and molecular biological fields. This project is based on my previous expertise in developing a high-content analysis pipeline around 2D image segmentation. Any current areas of research that use traditional microscopic high-throughput analyses have the potential to benefit from this tool. These include microscopic model organisms and mammalian cell research. This software will not be limited to fluorescence microscopy, but can also be applied to other platforms such as electron microscopy and in vivo imaging of animals. I will expand and characterize the means by which 3D image segmentation enables the analysis of these models in large-scale.

Continuing my previous research, one interesting application is the study of autophagy in MCF-10A mammary epithelial cells that is an easy and tractable 3D model system used in drug screening for the pathogenesis of epithelial tumours.

In summary, the development of 3D imaging tools will move the field of high-content analysis forward and open a new dimension to HCS methodologies that I hope will find its way into standard protocols. The successful completion of this project will enable me to become a leading expert in this field within Europe.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

• medical and health sciences basic medicine pharmacology and pharmacy drug discovery
• natural sciences computer and information sciences data science
• natural sciences computer and information sciences software
• social sciences sociology industrial relations automation
• natural sciences physical sciences optics microscopy electron microscopy

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

• FP7-PEOPLE-2009-RG - Marie Curie Action: "Reintegration Grants"

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-PEOPLE-2010-RG
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MC-IRG - International Re-integration Grants (IRG)

Coordinator