Data mining tools for personalized cancer treatment

10.2.2017
Helsinki Challenge semifinalist team iCombine aims to create data mining tools to find the best cure for individual cancer patients.

In the laboratories of Institute of Molecular Medicine Finland (FIMM), drug testing is done ex vivo. That is, various leukemia drugs are tested with patient samples instead of the patients themselves. This enables the researchers to test different drug combinations efficiently and without burdening the patient.

FIMM is also the home for Helsinki Challenge team leader Jing Tang. With his cross-disciplinary team of researchers in medicine, biology and informatics from University of Helsinki and University of Turku, Tang wants to integrate biomedical data in order to find personalized treatment options for leukemia, and later on possibly for other cancer types and diseases as well.

Integrating vast amounts of drug screening and genomic profiling data can be used to make suggestions about drug combinations.

"Then, based on the patient’s genetic background, we would know what might be the best drug combination," Tang clarifies.

Currently, the research platform is experimental, and the researchers need more data. In practice this works in three steps: the patient gives the sample, the clinician gets the results from drug screening, and the researchers get the patient data.

The future of personalized medicine

After several years of experiments the bottleneck in the project is data integration. Therefore it is integral to include informatics.

"We will develope a series of computational methods for drug combination prediction, modeling and data analysis. These methods will offer an improved efficiency to identify more effective combinatorial treatments for personalized medicine," Tang says.

"For this we need people from various fields with the same aim – we want to give the patient the right drug the right time. That will also save costs."

Currently, the sampling of the patients is done in research institutes, such as FIMM.

 "We are still in the beginning of brainstorming how to make it affordable for the hospitals," Tang says.

In order to make personalized medicine more accessible and applicable he intends to take Helsinki Challenge as an opportunity to build a larger community around the topic.

"Of course our aim is to win, but we also benefit from participating Helsinki Challenge by building a research network so that more people will be involved. We need various stakeholders including patient organizations, clinicians, researchers, biobankers, decision-makers, pharmaceutical companies and so on," Tang says.

Find out more about the iCombine team: Team iCombine: Our model could make cancer treatment more effective.

Read also: Revolutionizing drug discovery with computational approaches.