The human body is immensely complex, and there are a large number of factors that can influence how a drug works in your body.
Theories are a good starting point for approaching drugs–but ultimately understanding how a drug might work, or understanding how it should work, just isn’t enough. At the moment, it’s beyond our ability to fully predict all the ways a drug might affect your body.
For concrete examples, consider Viagra and Latisse, medications for erectile dysfunction and eyelash growth respectively. Viagra was developed for high blood pressure and Latisse was developed for glaucoma. Their uses today are both unexpected side effects that were discovered during testing.
Because we can’t trust our predictions, we instead ask for evidence in the form of experiments. Once we have experiment data, it overshadows any theoretical knowledge. If a drug theoretically shouldn’t work, or we have no reason to believe it would work, but the data shows that it does, then we side with data and conclude that our theoretical understanding is limited. However, this is true even of drugs where our theoretical understanding is very good. We still recognize that our understanding is ultimately limited by our less-than-perfect understanding of the human body and this necessitates experimenting to look for unexpected effects. We also accept that the mechanism of action we believe to understand may only be one part of a more complex chain of mechanisms.
In short, when it comes to medicine: data trumps theory. This is true regardless of whether our theoretical understanding is weak or strong.
The biggest hurdle for any medicine is the test of time. Over the years paracetamol has seen countless tests so we exactly know what kind of effects can come out of it so as to treat it promptly.
There’s precautions to be taken and a dosage identified completely known to us, while the exact cogs ticking behind the scenes may not be fully be known we have a good data of how it affects everyone and hence treated as a over the shelf drug
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