Data plays a major part in many of today’s innovations that impacts the society at large. This includes a lot of the great drug discoveries that’s been created to treat the worst illnesses. Even the most lethal disease of them all, cancer. It has been found that Big Data plays a major impact on affective research to treat cancer.
Big Data is extremely large data sets that can be analyzed to reveal patterns, trends, and associations. Especially relating to human behavior and interactions. A very complex and broad term, but with a lot of potential for great findings.
Like big data, cancer is also complex and broad in the sense of how many types there are.
In the United States alone, the National Cancer Institute (NCI) estimated 1,688,780 new cancer cases and 600,920 cancer-related deaths last year.
Cancer in all its types, constantly changes, evolves, and adapts. Which makes the data used for the research even more complex.
Snapshots of the tumor’s genetic makeup is what best helps understand its evolution. The measurements underlying these snapshots generate tremendous amounts of information. It’s then scientists such as Olivier Elemento who desire to identify patterns that will help prevent, diagnose, treat, and ultimately cure cancer. All being done with big data analytics and computer science.
Sequencing DNA and cancer genomes is what guides patient treatment and diagnosis by using big data. Researchers are required to break up cancer genomes into 100-base-pair long fragments and sequence hundreds of millions of these pieces. It’s then up to specific software to piece the large amounts of data back together.
Yet, sequencing alone doesn’t provide much information that can find a cure. Identifying the critical mutations in a genome is the challenge, and that’s where big data analytics fully come into play.
The researchers execute assays that measure the effect of mutations in the genome. One method is to examine changes in the transcriptome (the entire set of genes that are expressed). These assays create a lot more information, which are then combined with the DNA sequencing data.
Elemento said, “Humans have about 25,000 genes, and those genes are expressed at every different level, and expression levels are perturbed in disease. Normal cells express a pattern relatively conserved across cells in humans. We have to employ sophisticated pattern and machine learning algorithms to identify patterns that are potentially linked to disease.”
Once patterns in specific cancers are identified, the information can be leveraged to create models that diagnose and treat cancer.
On top of these models, Elemento has put together a database holding essential cancer genome mutations. These mutations are based on their own data and the cancer research community’s discoveries at large.
With this database, researchers can efficiently identify which mutations in a tumor are most essential and give that information along with an interpretation to the clinician.
The purpose of this database is for many researchers and clinicians to have the ability to update and access the data. With research happening quickly every day, the data shared within the community would make for great power and productivity.
New technologies are constantly being created and used in all industries. More importantly, the pharma industry has the potential to fully evolve for greater discoveries. By incorporating multiple data streams, from sequenced genomes to fitness tracking activity, more personalized cancer treatments can be created.
On the purpose of big data and cancer research, Elemento said, “The idea is to integrate the information to make better treatments for individual patients. Genomic information, phenotypic information, and more, to know what drugs to use and how to use the drugs.”
The Foundation Medicine is contributing to the fight against cancer with big data. They are collecting data on rare cancers, analyzing them within their huge database, and sharing it with other doctors. This connects physicians with each other, giving them more resources to treat cancer patients that weren’t available years before.
Ultimately, big data impacts the research for cures of cancer by ensuring researchers can use huge data on cancer patients (treatment plans, recovery rates, etc.) to find a pattern.
Another example of this is when researchers can examine tumor samples in biobanks that are linked up with patient treatment records. Accessing this data found, researchers can see things like how specific mutations and cancer proteins come together with different treatments. They then can find patterns that will lead to better results for the patients.
A benefit from sharing databases with hospitals, universities, and nonprofits is genetically sequencing cancer tissue samples from clinical trial patients. Then, making that data found even more wider throughout the pharma industry.
Big data can show healthcare providers how to make business more profitable but also improve operational efficiency. It can uncover the trends that can improve the quality of people’s lives.
The Centers for Disease Control and Prevention (CDC) has used big data to fight against Ebola and prevent it from being a pandemic. They had a big data program called BioMosaic. It collects data such as health statistics, population data, population migration and tracks epidemics. This has been largely helpful for testing, forecasting, and finding the diseases with potential to drastically spread.
More importantly, finding out how to prevent an epidemic. This is all done using big data in healthcare.