Cancer is a disease that is as old as the human civilization itself. At present, it is the second leading cause of death after cardiovascular disease. Looking at the advancements in modern medicine, one may wonder, why haven’t we found a cure for cancer yet? Cancer is a complex disease and can affect various parts of the body. A single tumor can have billions and billions of cells with each cell capable of acquiring mutations individually. To find a cure, it is almost impossible to study each variation individually. Additionally, the disease is always changing, evolving, and adapting. The best chance of studying the disease is to understand the genetic makeup of the tumor, which has billions of genomic codes. Such studies are far beyond human comprehension and require a technology that can process such vast amount of information. Big data can make such calculations possible and aid in the cancer treatment.
Cancer is a genetic disease, and is caused by certain mutations in the genes that control our cell’s functioning, especially how they grow and divide. Variation or a fault in some genes can cause the cells to grow in an uncontrolled manner. Such errors can occur due to exposure to carcinogens, radiation, and surrounding biophysical environment.
Why is it so challenging to study cancer?
Its now clear that to study cancer, physicians must understand the make-up of a particular gene. However, for an extended period of time, it has been an almost impossible task. Consider this; the human gene is composed of four different types of chromosomes. The DNA in the largest chromosome, chromosome number 1, consists of approximately 220 million base pairs. Cancer can result from mutation or alteration in any one of such base pairs. Similarly, mutations can occur in any combination of such base pairs. As a result, it is impossible for humans to devise an effective cancer treatment plan by studying all such mutations.
How can big data help in finding cancer treatment?
Big data has the capability to analyze such a broad array of information not only across a single gene but also across genetic makeup across large samples of a cancer patient. It can find out the correlation between certain factors that cause a particular type of cancer. So how can big data aid the healthcare industry to find a cure for cancer?
Targeted treatment can be used to target cancer’s specific genes and proteins that fuel the growth of cancer cells. By testing a sample of the tumor, patients can be given new drugs and targeted therapy to figure out whether the tumor has a specific target. By analyzing samples across a large population, physicians will be able to improve the efficiency of such targeted treatments.
One of the pioneers in the field of cancer treatment using AI is the supercomputer, IBM Watson. Since each cancer is different, and each person has different genes, Watson can recommend a cancer drug that will most likely treat a particular patient’s cancer. It is because the supercomputer is programmed with specific details on how thousands of medicines interact with the human body. From there, Watson can make recommendations on which medication interacts beneficially with the cell affected by the cancer-causing mutation.
It is evident that genomic data is enormous. It takes around 200GB of storage to capture the raw code output by a genome sequencer. The cure for cancer lies in such databases. Using comparative analysis, researchers can isolate the factors that lead to cancer. However, it is not as simple as it looks, it requires huge storage and immense computing power to perform such analysis. Big data can assist healthcare professionals to compute, harvest, and decode such significant amount of data and consequently contribute towards cancer treatment.
For now, radiotherapy is the major treatment mode for cancer along with surgery and chemotherapy. A large majority of cancer patients receive radiotherapy as a part of their treatment. However, there’s a problem with such treatment mode. Physicians need to know the exact amount of radiation required, too little and it won’t work, and too much can cause side-effects and damage healthy cells as well. Analyzing historical radiation data could be used to guide radiotherapy safety thereby improving treatment efficacy.
To know more about how big data analytics can help find treatment for cancer, predictive analytics, and machine learning