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When they're not potentially infectious, they have extraordinary health claims.
The maker of wide-ranging "water-based homeopathic medicines" has recalled 32 products marketed to children and infants due to microbial contamination, according to an announcement posted on the Food and Drug Administration's website this week.
The announcement does not provide any specifics about the contamination or potential risks. However, the North Carolina-based manufacturer behind the recall, King Bio, issued a similar announcement back in July. At that time, the company recalled three other products after an FDA inspection found batches contaminated with the bacteria Pseudomonas brenneri, Pseudomonas fluorescens, and Burkholderia multivorans.
Pseudomonas brenneri is a bacterium recently found in natural mineral waters, and its clinical significance is murky. However, Pseudomonas fluorescens is known to be an opportunistic pathogen, causing blood infections, and Burkholderia multivorans can cause infections in people with compromised immune systems and cystic fibrosis. It was also recently found to be a rare but emerging cause of meningitis.
[...] UPDATE 8/24/2018: King Bio updated its website to include a note about the recall. The company wrote that: "Within the past two weeks, microbial contamination was discovered in two children's products, but as an added measure of caution, we chose to recall all the children's products manufactured from August 2015 to August 2018." It added that no injuries or illnesses have been reported to date.
(Score: 2) by ikanreed on Monday August 27 2018, @06:50PM (10 children)
Ah, now I see what you're getting at. But the reality is that real world medical data is super messy, and interfered with by a billion things that no model could accurately handle. You're asking for an exact windspeed of a hurricane when it makes landfall based on the tropical depression forming off the coast of West Africa. Working on a clinical trial is more about the 90% probability arc for 6 days. And making sure people don't die. If with the multitudes of data we have on storm tracks and a very reliable understanding of the underlying mechanisms, the real world doesn't allow for that kind of precision.
And finding reliable dose-response curves are often a goal of secondary trials.
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @10:52AM (9 children)
Science is just too hard so we use pseudoscience instead! Yep
(Score: 2) by ikanreed on Tuesday August 28 2018, @02:01PM (8 children)
There's nothing unscientific about the hypothesis "we expect to see improved results in this specific area and if we don't compared to a placebo (or standard treatment)". Sorry you're enough of a pseudoscientist to reject controlled experimentation that doesn't fit your engineering-broken brain.
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @05:30PM (7 children)
This isnt even close to being an hypothesis. Im guessing there are typos in there though. A hypothesis would be something like "this drug causes nitric oxide release from endothelial cells which leads to arterial dilation which leads to lower arterial pressure if there is no concomitant increase in blood pressure".
Then you'd have to build a quantitative model of
This model can be entirely empirical if you want (eg use machine learning), but once the function is chosen and all the "best" parameters/coefficients are picked someone needs to collect new data from new people/rats/whatever and show that it still works, because you did (without a doubt) overfit to the data used to develop the model.
Go find me a clinical trial that includes something like this or cites it as supporting evidence. You wont find any... It doesnt exist.
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @05:31PM
Typo:
"this drug causes nitric oxide release from endothelial cells which leads to arterial dilation which leads to lower arterial pressure if there is no concomitant increase in blood volume"
(Score: 2) by ikanreed on Tuesday August 28 2018, @07:37PM (5 children)
Your quantitative model is so damn reductionist. No way things like "how much water I drank today" factored into your gross simplifications.
No factoring in "what food did they take with the medicine affecting release rate"
No "did they exercise raising blood circulation"
No "does their case of this illness come in a more virulent strain sometimes"
No "how do their hormone levels fluctuate"
It doesn't exist because what you want is stupid, and your stupid with them.
You're a goddamn pseudoscientist.
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @09:13PM
The stuff you dont account for is included in the uncertainties. That is why a model is always going to be consistent with a range of values. This is the entire point of statistics...
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @09:21PM (3 children)
Anyway, this why all the talent is fleeing academia. Its filled with people who find science too hard... almost all your time is wasted explaining the most basic stuff to them. Its irritating as hell.
(Score: 2) by ikanreed on Tuesday August 28 2018, @09:27PM (2 children)
You know, for all my interactions with PhDs, I don't think I've ever met one who "fled academia" because "science is too hard"
Pointless budget cuts? Oh yeah. Tenure track becoming impossible? For sure. Noxious department politics? Definetly
Having some entirely fantastical notion of rigor that wasn't being lived up to? Never.
(Score: 0) by Anonymous Coward on Tuesday August 28 2018, @10:13PM (1 child)
You misread. Those are the ones who stay in academia... The people who dont want to put up with them (and all the BS they try to substitute for doing a good job) are the ones fleeing.
(Score: 2) by ikanreed on Wednesday August 29 2018, @01:25AM
Nah, I read you right the first time, but typed wrong. I mean you'll just have to take my word on that, and the context clues of the rest of my post.