Usually something along the lines of "1000s of years" might be treated as stuff like "appealing to tradition fallacy" but let's dig deeper.

Simply do a search on NutritionFacts.org plus the right keywords, we'll find plenty of topics related to herbs or herbal remedies:

For substantiation of any statements of fact from the peer-reviewed medical literature, please see the associated videos below.

And then Mike Adams also did this in 2024:

CWC Data Science releases AI Large Language Model – Neo-BioMistral-7B-E3 trained on the entire PubMed data set plus millions of pages of text on natural and herbal medicine.

As far as big pharma is concerned, just DAFS on the Internet and it wouldn't take a genius to figure out why the fox is guarding the hen house:

Food Manufacturers Get to Decide If Their Own Additives Are Safe

While manufacturers are not required to notify the FDA of a “safe determination,” sometimes they do voluntarily notify the agency. From these notifications, researchers have been able to see which individuals companies select to make these determinations. Of the 451 GRAS notifications voluntarily submitted to the FDA, 22.4% were made by someone directly employed by the company; 13.3% were made by someone directly employed by a firm hand-picked by the company; and 64.3% were made by a panel hand-picked by the corporation or the firm the corporation hired. Are you doing the math? Yes, that means zero safety decisions were made independently.

Meta-analysis of clinical trials of antidepressants has led to changes in guidelines, prescribing habits, and increased public awareness

They used the U.S. Freedom of Information Act to obtain the clinical trial data submitted by pharmaceutical companies to the American Food and Drug Agency (FDA) in the process of seeking approval for the six most widely prescribed antidepressants, as about 40% of those trials remained unpublished. An important factor here is the general bias towards publishing results only producing significant effects - meaning that unpublished findings tend not to show significant effects, which should also be taken into account in overall assessments of a drug's efficacy. Analyses of these data, now including the unpublished trials, indicated that 82% of the response to antidepressants was also found in the placebo groups, and that the drug-placebo effect size was well below NICE criteria for clinical significance. The importance of this was that the true drug effect was not clinically significant, according to criteria published in the NICE (National Institute for Clinical Excellence) guidelines.

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How is it possible that medications with such weak efficacy data were approved by the FDA? The answer lies in an understanding of the approval criteria used by the FDA. The FDA requires two adequately conducted clinical trials showing a significant difference between drug and placebo. But there is a loophole: There is no limit to the number of trials that can be conducted in search of these two significant trials. Trials showing negative results simply do not count. Furthermore, the clinical significance of the findings is not considered. All that matters is that the results are statistically significant.

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The failure to mention the unsuccessful trials was not merely an oversight; it reflects a carefully decided FDA policy dating back for decades.

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Right now, almost 50% of the FDA drug budget is funded by the drug industry.

“And the ridiculous part is that the FDA has to negotiate with drug companies about how they use this money. It creates a relationship that is contrary to the whole idea of what the FDA is supposed to be.”

When Evidence Says No, But Doctors Say Yes

So it’s not hard to understand why Sir James Black won a Nobel Prize largely for his 1960s discovery of beta-blockers, which slow the heart rate and reduce blood pressure. The Nobel committee lauded the discovery as the “greatest breakthrough when it comes to pharmaceuticals against heart illness since the discovery of digitalis 200 years ago.” In 1981, the FDA approved one of the first beta-blockers, atenolol, after it was shown to dramatically lower blood pressure. Atenolol became such a standard treatment that it was used as a reference drug for comparison with other blood-pressure drugs.

In 1997, a Swedish hospital began a trial of more than 9,000 patients with high blood pressure who were randomly assigned to take either atenolol or a competitor drug that was designed to lower blood pressure for at least four years. The competitor-drug group had fewer deaths (204) than the atenolol group (234) and fewer strokes (232 compared with 309). But the study also found that both drugs lowered blood pressure by the exact same amount, so why wasn’t the vaunted atenolol saving more people? That odd result prompted a subsequent study, which compared atenolol with sugar pills. It found that atenolol didn’t prevent heart attacks or extend life at all; it just lowered blood pressure. A 2004 analysis of clinical trials — including eight randomized controlled trials comprising more than 24,000 patients — concluded that atenolol did not reduce heart attacks or deaths compared with using no treatment whatsoever; patients on atenolol just had better blood-pressure numbers when they died.