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Adipocyte Cell Imaging Challenge

AstraZeneca and AI Sweden are challenging the AI community to solve the problem of labeling cell images without requiring toxic preprocessing of cell cultures. The task is to utilize machine learning to combine the advantages of bright field and fluorescence imaging and at the same time avoid the toxic effects of cell labeling by predicting the content of the fluorescence images from the corresponding bright field images.

Background

Novel therapeutics and cell imaging

Historically, most drugs have been small molecules binding to target proteins in the body. The problem is that one drug might bind to several similar proteins, creating unwanted side effects. A more specific way is to target the RNA sequence of the proteins where nanomedicines often are used to transport RNA cargo through the body.  These nanomedicines are small engineered machines made from biomolecules that interact with cell membranes and machinery to deliver RNA into cells where it can affect their function. 

To be able to inject the nanomedicines into the skin will make treatments with nanomedicines easier for patients. One of the most important cellular targets are the fat cells (adipocytes) that we all have in our skin. To avoid using human test subjects, adipocyte cell cultures can be created from stem cells. One of the most important methods to investigate the uptake of nanomedicines in cells is cell imaging, which is the topic of this challenge.

The goal of cell imaging is to extract relevant information about the cell structures that can guide pharmaceutical development. To permit imaging of different cell structures, fluorescence microscopy is used to label specific parts of the cell.

How will it work?

AstraZeneca is sharing a data set consisting of pictures of stem-cell derived human adipocyte cell cultures  The cells have been imaged, using a robotic confocal microscope, at three different magnifications, using both brightfield and fluorescence imaging. After the competition, the data set will be accessible for non-commercial purposes to all AI Sweden partners through the Data Factory.

More about the challenge here

Facts

  • Application is open, apply before October 15
  • The challenge will be held online starting on November 2
  • Total prize sum, sponsored by AstraZeneca is $5000
  • Maximum number of team members is 5
  • Teams will have access to computational infrastructure during the competition