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In this project we will, together with pharmaceutical companies combine and refine three recently proposed network based concepts for development of a computational pipe-line for analysing big data for precisions medicine.

Many currently used drugs are ineffective for treating complex diseases. However, modern biology today generates enormous amounts of inexpensive, accurate, high-throughput data (‘omics), at several molecular levels.§

AI which finds patterns in complex biological data could eventually contribute to the development of individually tailored healthcare. Researchers have developed an AI-based method applicable to various medical and biological issues.

Women suffering from multiple sclerosis temporarily get much better when pregnant. Researchers have now identified the beneficial changes naturally occurring in the immune system during pregnancy. The findings can show the way to new treatments.

A combination of only 11 proteins can predict long-term disability outcomes in multiple sclerosis (MS) for different individuals. The proteins could be used to tailor treatments to the individual based on the expected severity of the disease.

Some patients experience life-threatening side effects during cancer treatment. Researchers at LiU have developed a model that can predict which patients have a high probability of side effects.

An artificial neural network can reveal patterns in huge amounts of gene expression data, and discover groups of disease-related genes. The scientists hope that the method can eventually be applied within precision medicine.