Healthcare and life sciences

Published in Science: New research into cancer immunotherapies

Cancer immunotherapies, treatment approaches which harness a person’s own immune system to target and kill cancer cells, are currently a major driver in the development of new cancer treatments. In research recently published in Science, scientists at IBM, Columbia University and the Memorial Sloan Kettering Cancer Center (MSKCC) have solved an important piece of the immunotherapy puzzle. MSKCC researchers discovered that genes associated with how killer T cells recognize cancer cells are essential for immunotherapies’ success.

Supercomputers identify rare gene that may increase risk of Type 2 Diabetes

Laxmi Parida, IBM research scientist and manager of the Computational Genomics Group, who is based in Yorktown Heights, New York, says using supercomputers to help analyze medical data will help doctors understand genetic links to diseases in more complicated cases. She says algorithms can untangle the web of genetic data that can hide important diagnostic clues.

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First-of-a-kind microbiome dataset published in Nature

It’s becoming increasingly clear that our health is influenced by our personal complement of microbes – our microbiome. Awareness of the microbiome has grown in leaps and bounds thanks to the massive capacity of scientific instruments that read the DNA of microbes. But many fundamental questions about microbes remain unanswered, even questions that seem like they should be easy. “Has anyone seen this microbe before?” “Where? “When?” After today, answering these questions will be a lot easier. The problem was not lack of data, but that each microbiome dataset was an island onto itself and not easily compared to the others. Working as a team of microbial ecologists, computational scientists, bioinformaticians, and statisticians, we analyzed the largest collection of microbiome data (by 100 times). In the current issue of Nature, we report the first-of-a-kind microbiome database that lets researchers track microbes across the planet, even if the microbes don’t have a name (as is usually the case).

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New research in AI pushes frontiers in epileptic seizure prediction

Recently, the Lancet’s EBioMedicine journal published a study led by scientists from IBM Research-Australia and the University of Melbourne marking important progress in personalized seizure forecasting. The findings, described in a paper titled ‘Epileptic Seizure Prediction using Big Data and Deep Learning: Toward a Mobile System,’ present new results in epileptic seizure prediction using deep learning algorithms deployed on a brain-inspired, mobile processor. Investigators found that the algorithm successfully predicted an average of 69 percent of seizures across patients, including patients who previously had no prediction indicators.

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