With the data collected from patients, researchers are able to study different diseases and try to find better treatments and even cures. Scientists and pharmaceutical companies are able to use bioinformatics to develop new treatments and discover cures and treatments for diseases that currently do not have them. The benefit to using so much data is the ability to determine why some drugs worked for a population versus not for others.

A recent study found that the blood thinner clopidogrel, or Plavix, doesn’t work in the 75% of Pacific Islanders whose bodies don’t produce the enzyme is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques required to activate the drug. By using algorithms, researchers can determine areas that certain drugs may work and where they may not.

A new computer program developed at the University of Arizona College of Medicine is able to personalize drug treatments for patients using genetic information. The program is licensed to INTelico Theraputics, LLC, a startup in Arizona and uses genetic information from millions of patients to predict the effects of drug therapy that is personalized to each individual using their specific genetic makeup.

In another case, researchers at the University of Cambridge used an algorithm to identify four new molecules that activate a protein which is thought to be relevant to symptoms of Alzheimer's disease and schizophrenia. The machine learning program for drug discovery has shown to be twice as efficient as industry standards and could accelerate the development of treatments for these critical diseases of the brain.

Some researchers are working diligently to try and find a cure for cancer. University of Hawai'i Cancer Center researchers developed a computational algorithm to analyze data obtained from tumor samples to better understand and treat cancer.

Gordon Okimoto, co-director of Biostatistics and Informatics Shared Resource at the UH Cancer Center and collaborators developed a computational algorithm called the Joint Analysis of Many Matrices by ITeration (JAMMIT). JAMMIT uses advanced mathematics to identify different patterns across multiple molecular data types such as gene expression and genetic mutations that when taken together accurately predict what treatments would be best for a given cancer patient.

“The algorithm could accelerate the approval of powerful treatments for many cancers, improve clinical outcomes, and reduce costs for treating cancer,” said Randall Holcombe, director of the UH Cancer Center. “I believe this discovery can open a path to more precision medicine clinical trials that could be initiated and run locally in Hawaiʻi.”

As many researchers are working on different machine learning programs to help identify new treatments and cures there is no doubt that there will be many advancements in healthcare treatments and cures using these algorithms in the next 10 years. Stephen Hawking said that he believed AI will be the thing that will cure all diseases.

"Perhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one–industrialization. And surely we will aim to finally eradicate disease and poverty. Every aspect of our lives will be transformed. In short, success in creating AI, could be the biggest event in the history of our civilization," Hawking said.

There is no sure answer if AI will solve all the world's diseases, but there is no doubt that it is definitely shifting the industry and will be a tremendous help to healthcare.

The algorithm was created by Rui Chang, Associate Professor of Neurology, and Eric Shadt, Dean for Precision Medicine at the Icahn School of Medicine at Mount Sinai. It uses big data from large patient populations and a variety of sources such as DNA and RNA sequencing, proteomics, metabolomics and epigenetics. They use that data to then compare it to historic groups of those who have been diagnosed and treated for diseases and determine the course of treatments that will likely have the most effective outcome for the patient.

Source : https://www.forbes.com/sites/nicolemartin1/2019/08/30/how-healthcare-is-using-big-data-and-ai-to-cure-disease/?ss=ai-big-data#44f8b3c145cf