Big Data search for effective medications

My proposal was to search for medications in the reverse sense, by looking for drugs missing from patients medical histories, suggesting the drug might be protective against the disease. But that article above shows big-data can find effective medications in the direct sense, by reviewing large data sets of patients medical histories looking for drugs that patients with positive outcomes had in common.

The article explains the doctors in China noticed rural patients with severe disease surviving better than city patients with severe disease. They hypothesized it was due to rural patients using the cheaper Pepcid to deal with heartburn.

The doctors then confirmed there was a statistical association between Pepcid and more positive survival rates. The point I’m making though is by reviewing such a large data set of 6,000 patient histories the computer could have identified that association even when the doctors had no inkling there was a link.

This method then can be used to find other medications that had a positive influence on patient outcomes, even when doctors are not aware of it.

That report I discussed earlier on New York COVID-19 cases had a data set of 4,000 cases, 2,000 hospitalized and 2,000 non-hospitalized, “Factors associated with hospitalization and critical illness among 4,103 patients with COVID-19 disease in New York City”. The hospitalized cases would have the medical histories already in the data set. For the non-hospitalized cases, they could be called in to collect their medical histories. Then this method would also work with this data set to find effective medications. It’s common to look at collected medical histories and find certain risk factors for bad outcomes of a disease, especially for COVID-19 as that New York report did. Why not look at those medical histories to search for medications with a link to positive outcomes for a disease?

In fact this method likely would work for any of the studies that had cases numbering in the thousands in their data set. But note that I’m also suggesting going beyond just this. With approaching one million COVID-19 cases in the U.S., this would provide an unprecedented degree of data that could be used to search for drug associations to positive patient outcomes.

If this works, then it becomes obvious to take this to the next level to find effective drugs for any disease.

Robert Clark