Big Data Predicts Pollen Levels, Keeps Allergy Medicines In Stock

Image courtesy of The enemy: pollen. (Karen Chappell)

The enemy: pollen. (Karen Chappell)

The enemy: pollen. (Karen Chappell)

Here in the Northeast, people who are allergic to pollen are having a harsh spring. They should take comfort, though, that there isn’t a corresponding shortage of allergy medicines, as there apparently was five years ago. Drug companies have learned how to take global climate data and turn it into more plentiful antihistamines when people need them.

Bayer, for example, is the maker of Claritin, a pretty standard and popular new-generation antihistimine. According to the Wall Street Journal, Bayer plans its entire supply chain for Claritin as early as nine months in advance, and uses software that models climate patterns to predict levels of popular allergens, then make sure that those areas stay supplied. Real-time and past years’ sales data are important, too, but weather is an important variable in how demand for a certain medication can change.

This spring, pollen levels are apparently up 25% on the coasts of the United States, which explains why people allergic to pollen are so unhappy, and why my car looks green. Experts say that this is because plants are spewing pollen, but there has been less rainfall than usual, which means that the pollen continues to float around, hitting humans in the face and causing allergic reactions.

Using weather models has other applications outside of allergy drugs, but those are trickier since other health conditions don’t map as precisely as pollen levels do to allergic reactions. You can try to predict demand for cough medicine along with spans of cold temperatures, for example, but that’s imprecise. If you can predict pollen levels, though, you can probably predict demand for allergy medicines.

Big Data Brings Relief to Allergy Medicine Supply Chains [Wall Street Journal]

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