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Big-data analysis points toward new drug discovery method

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Big data has already impacted healthcare business in the recent times and it is no secret that new fields are discovering its relevance. However, in fields of medical research too, big data is showing immense possibilities. As long as there is data, big data concepts can be applied and developed further to provide valuable insights. Such has been the case with UC San Francisco where a research team has developed a method so that humongous amount of data available through open access data can be processed and new usages of drug can be churned out. Previously, scientists used to perform series of experiments of specimens and that too left a lot of room for error. However, things are going to change very soon.

Computation instead of experimentation

The days of experimentation are not gone, but they may well face a revolution when biology labs will be infiltrated by big data experts instead of researchers of life sciences. Researching on specimens leave plenty of risk leading to completely different reaction on humans, but with big data, there is no such risk. It takes FDA-approved drugs and other compounds to molecular fingerprints for situations like cancer. Then, the link between the diseases and the drugs can easily be mapped according to metrics like impact, side effects etc. So, particular drugs may then be targeted and more experiments will be conducted so that such side effects can be minimized and their resistance to counter-drugs can also be curbed. Thus, diseases will then be easy to work upon by targeting them with particular drugs and avoiding prescribing some more.Big-data analysis points toward new drug discovery method

Doctors become more knowledgeable

Doctors, while prescribing drugs, have stuck to particular dosages and specific names for decades. However, things are going to change very soon as they individually tailor the drugs according that particular patient. Drugs that were used for curing simple, innocuous diseases are now being used to fend off powerful forms of liver carcinoma, such is the power of big. This kind of cancer is the most frequent and fatal across the world and no effective treatment has not come out even after so much progression in the field of medicine and genetic research. Of course, genetics came into rescue, but big data mediated in the process.

Collecting cancer data

For the research, two petabytes worth data that accounted for three dozen cancer variations and 14 different caner typologies were compared with control samples of tissues, especially adjacent to tumors. After going through this database, they used another humongous open access database from the LINCS dataset, belonging to Library of Integrated Network-based Cellular Signatures. They are locating the source of harmful proteins through the data analytics of gene expressions. They have already tried out these genes in the various concentrations of drug as particular durations of the treatment. Hence, all kinds of variations are recorded in the database ranging from normal, adjacent, and affected cells and then compared through data analytics to bring revolution in the world of drugs and medical sciences.