Many diseases are incredibly complex and unpredictable, and finding one-size-fits-all solutions to those diseases can be extremely difficult. Luckily, what researches do have are mountains of data. Patient history, genetic data, and diagnostic data are becoming key tools in helping fight off critical diseases. Atul Butte, the Director for the Institute of Computational Health Sciences says "hiding within those mounds of data is knowledge that can change the life of a patient, or change the world." In this blog, I'm going to go over 3 complex diseases that big data is currently helping uncover correlations, patterns, and insights to help medical professionals better understand those diseases.
Cancer has been one of the most devastating diseases of our lifetime, and is the second leading cause of death globally, killing almost 9 million people in 2015. With cancer, there isn't just one genome, and it is actually hundreds of different diseases. This makes every tumor different, and each one can grow in its own unique way. This makes treating the disease extremely complex. Comparing two cancers on a molecular level is almost impossible, and no two will ever be the same. This is what creates the biggest challenge. Researchers are currently using big data to analyze cancerous diseases on three levels. On the Cellular level, scientists are looking for patterns in data of individual cancer cells in order to find genetic biomarkers. Finding common features pointing to insights to how tumors mutate can help us better predict what treatment might be the most effective. On a patient level, doctor's look at a patients medical history and DNA data to define the best combination of treatment for them based on their tumor and genes. They how the treatments of past patients with similar disease patterns will also be effective. Doctors also look at population data to find treatment strategies for patients based on lifestyle, geography, and cancer type.
Lyme Disease is a bacterium borne illness transmitted to humans by the bite of infected ticks. Scientists are currently looking at large sets of medical data that deals with Lyme disease to investigate different aspects of the disease. Scientists are currently looking at past data to discover the natural course progression of the disease to find out when the disease gets worse. They can use this data to also discover with treatments are the most effective and which treatments produce poor outcomes. By looking at the data, the can find which patients recovered well from Lyme disease and discover with treatment made the biggest difference. They are also looking at genetic factors that affect the course of the disease and whether or not the disease can be sexually transmitted or pasted to children.
The Alzheimer's Research Foundation has recently launched a new project to collaborate with researchers to pull together big data from a range of sources for insights into Alzheimer's. Through different Alzheimer's and Dementia studies, DNA samples, brain scans, and memory tests, researchers can combine this information to help uncover insights and advance their understanding of the disease. Research Institutes from across 5 countries are pooling their data together to help doctors around the world look for trends and patterns to answer questions to better understand the disease and how to treat it. Researchers are looking for answers to questions regarding how certain patients respond to certain treatment, patterns scene in the early stages of Alzheimer's, and how they can detect the disease earlier.
Sources:
https://www.dementiablog.org/using-big-data-to-solve-a-big-problem/
https://www.canwelivebetter.bayer.com/innovation/finding-cure-cancer-big-data-solution
https://www.lymedisease.org/mylymedata-lyme-disease-research-big-data/
Cancer
Cancer has been one of the most devastating diseases of our lifetime, and is the second leading cause of death globally, killing almost 9 million people in 2015. With cancer, there isn't just one genome, and it is actually hundreds of different diseases. This makes every tumor different, and each one can grow in its own unique way. This makes treating the disease extremely complex. Comparing two cancers on a molecular level is almost impossible, and no two will ever be the same. This is what creates the biggest challenge. Researchers are currently using big data to analyze cancerous diseases on three levels. On the Cellular level, scientists are looking for patterns in data of individual cancer cells in order to find genetic biomarkers. Finding common features pointing to insights to how tumors mutate can help us better predict what treatment might be the most effective. On a patient level, doctor's look at a patients medical history and DNA data to define the best combination of treatment for them based on their tumor and genes. They how the treatments of past patients with similar disease patterns will also be effective. Doctors also look at population data to find treatment strategies for patients based on lifestyle, geography, and cancer type.Lyme Disease
Alzheimer's
The Alzheimer's Research Foundation has recently launched a new project to collaborate with researchers to pull together big data from a range of sources for insights into Alzheimer's. Through different Alzheimer's and Dementia studies, DNA samples, brain scans, and memory tests, researchers can combine this information to help uncover insights and advance their understanding of the disease. Research Institutes from across 5 countries are pooling their data together to help doctors around the world look for trends and patterns to answer questions to better understand the disease and how to treat it. Researchers are looking for answers to questions regarding how certain patients respond to certain treatment, patterns scene in the early stages of Alzheimer's, and how they can detect the disease earlier.Sources:
https://www.dementiablog.org/using-big-data-to-solve-a-big-problem/
https://www.canwelivebetter.bayer.com/innovation/finding-cure-cancer-big-data-solution
https://www.lymedisease.org/mylymedata-lyme-disease-research-big-data/
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