Big Data Analytics tools to help find drugs for Cancer


Here’s to the Big Data analytics tool which would take us to a whole another level in advance precision medicine/drug in cancer and other complex diseases!!!

In this new age where everything almost runs by technology and through data- Big data which is the most popular and most sought-after techniques is a huge data set which can be analyzed computationally to give insights on patterns, trends especially related to human behaviour and human interactions. This Big data tool uses info from many types of cancer and helps the researcher to identify the correct potential treatment and make it into a fine precise cancer medicine. The tool combines the numerous data sets available, then analyses them thus turning them into real good clinical insights for the researcher’s use. The recent efforts that were put int the collection of numerous data from multiple cancer types has produced over rimming results and data from which cancer researchers could benefit from and use the tool to understand all the data in their hands too.

To understand the proper preclinical models there are three sources of data sets to combine is what expert researchers say, the three sources are- molecular data sets from both cancer cells, patients, and thirdly the drug proliferating data.

The tool that is called the TransPRECISE, uses data from 7,714 cancer patients across many types of cancer (31 types) to get valuable data for knowing about cancer and for creating a cure. The highest point advantage of this tool would be that it is dynamic in nature, i.e. we could have this whole tool set up in a computer system. And new data could be kept on adding whenever new cancer patients are brought in.

The tool TransPRECISE picks up data from cell lines as well as drug sensitivity, which will be helping researchers in finding a medicine/drug for it. With the analytical tool, we could analyze all the tumour cells and come up with important insights for the drug. Researchers around the world are looking into new ways to predict a likely drug, and results have pointed to the current treatments like ibrutinib which are used for positive breast cancer patients with brca; a gene causing breast cancer.

The tool TransPRECISE provides us with an opportunity to bridge the gap between the human and preclinical models to point correctly at the cancer pathway drug interactions to pave the way to find a drug-using big data tool.


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