How Can Big Data Be A Cancer-Fighting Tool?
The silver bullet of medicine, curing cancer is still elusive, although massive resources and intensive research are now available and directed towards this problem. The term ‘cancer’ does not define just one disease, but a large family of body malfunctions whose common denominator is the uncontrolled growth of specific cells with mutated DNA. Depending on the tissue where this growth occurs and the general characteristics of the organism, no two cases are the same. For a disease estimated to hit more than one-third of the US population, the need to find answers is high.
One of the most promising solutions to this problem is ‘computational biology.’ This field links natural science to information technology by aiming to code biological data into models that can be analyzed to define relations and patterns. A helpful tool in this endeavor is Big Data analysis, a new approach to look at datasets that are measured in TB (1TB = 1024GB). For example, the data retrieved from only one patient suffering from cancer could reach 50TB, including daily changes and breaking down genomic data.
The sheer possibility of collecting these amounts of data was highly unlikely just a few years ago, but it is now growing at an exponential rate due to the expansion of different Internet of Things (IoT) devices. This helps scientists get into the mechanics of cancer and not only classify it by the organ where it occurs, but by taking into consideration how it unfolds and reacts to treatment.
These new insights can help researchers investigate at an atomic level and not only identify the vicious cells but go far in the DNA structure and identify the mutated genes that are causing the condition. This is just the first phase of a long drug discovery process that needs to recognize the substances that can make an impact on that specific gene and cause cancer remittance.
The difference from traditional cancer cure is that this approach does not only look at exterior manifestations but tries to understand the genetic triggers. This is an entirely new way of dealing with this deadly disease. The advantage of this method is that it focuses on the root cause instead of external manifestations. Scientists gather several sources of data points into one centralized data lake, and by applying unstructured data analysis algorithms, they aim to find meaningful connections. This is a world away compared to the clinical trial method which was used until now, with little success.
According to Carl Sagan, we are made of star stuff. Applying this logic, Dr. Caldas from Cancer Research UK is adapting an algorithm developed by astronomers for galaxy studies to categorize medical images. Cancer researchers are utilizing the same methods that scientists use to count the stars and classify galaxies to count malign cells and create classifications of the disease.
Stars aren’t the only inspiration for these pioneers, as they are being inspired by other areas as well.
