Can artificial intelligence reduce side effects of medicine

Must be in the Water

What if we could calculate every potential variable of a pharmaceutical with machine learning and artificial intelligence. The results would be fewer if any side effects, let’s explore the concept briefly. Many pharmaceuticals advertise not to consume with grapefruit juice because the acidity causes the drug to metabolize too rapidly resulting in an acute overdose. The same can be said for your drinking water, depending only on the alkalinity (pH) of your water of choice you may be changing the metabolic rate of your pharmaceuticals.

This is only one variable of drinking water, now consider iron concentration, fluoride content, calcium, and arsenic. All are ingredients in your water, you probably simply throw the notice away, but maybe you shouldn’t. Even if you don’t drink your tap water, you probably bath in it, and many of the ingredients we absorb through our skin; so you see just how complex this problem is.

What’s holding us back

To fully understand the situation, data would need to be collected not just on the water, but on the exposure to the water:

Do you drink the water?

What about cooking with it?

How many times a day do you bathe?

How frequently do you wash your dishes?

Do you have sprinkler systems for your lawn/garden?

Which home filtration methods do you employ?

Now let’s consider other variables that are also known to have an impact on pharmaceuticals:

  • Exposure to sunlight or UV radiation
  • Genetic Predisposition
  • How much sleep do you get
  • Are you in close proximity to farms that use pesticides or weed abatement
  • Do you consume red meat or fish
  • Do you use e-cigarets or tobacco

With every variable, there are dozens of additional data points. Every individual would need access to a personal quantum computer to determine the best treatment options and pharmaceuticals. In addition to the personal quantum computer, everyone would need a personal actuary monitoring every environmental interaction.

Conclusion

A multi-faceted problem requires a multi-faceted solution. New technology is blooming like wildflowers around us with little guidance and disjointed objectives. Until there is a unifying force that connects each of these devices to address more than simply lighting a room with voice commands or playing your favorite song, it will be necessary to develop single-use solutions for each problem. The use of artificial intelligence and machine learning alone will not reduce pharmaceutical side effects, they are simply cogs that need to be tuned in the beautifully crafted timepiece. Like a clock without hands, the software is useless without the data; its acquisition, transmission, and translation are a few of the overlooked cogs we are expertly honing.

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2018-05-31T11:27:43+00:00