Building research infrastructure to enable clinicians to choose the right treatment for the right patient
Background
Choosing the most effective treatment for an individual with cancer is challenging. Cancers which may appear to be identical, will often respond very differently to treatment because of differences at the molecular level. The most important of these are the protein molecules. Knowing what proteins are present in cancers is essential for developing new cancer treatments and for using existing treatments as effectively as possible. A highly promising approach to increasing the accuracy of treatment choices would be to analyse all the relevant proteins in each cancer, but until now it has been impossible to do this reliably.
Professor Reddel and his colleagues have commenced a major new research program called ProCan, to analyse and measure thousands of proteins simultaneously in cancers, and use advanced computational techniques to learn how to predict the most effective treatments for individual cancers. To make this ground-breaking bank of information accessible to other researchers and clinicians, the ProCan team needs to build a highly sophisticated online database.
The research
With this funding from Cancer Council NSW, Professor Reddel and his team will now be able to create an online platform to handle the vast amounts of data produced by ProCan, and enable it to be shared for research and clinical purposes. This database will enable the transformation of raw data into a format that can be provided initially to data scientists and ultimately to clinicians for direct benefit for patients.
The expectation is that the technology will be used in the clinic within 5-7 years at which time a tumour sample will be sent to a laboratory and the results returned within 36 hours providing information about the most effective known treatments for that person.
The impact
This infrastructure will make it easier for clinicians to choose the right treatment for individual patients. For patients this will mean the best chance of successful treatment with fewer side effects.