HealthNewsReview

"The bigger picture is that almost all hard R&D takes place under the umbrella of some sort of protection from copying."

There is a huge difference between protection from copying, and protection from building similar things that achieve the same goal. Patents are not simply "protection from copying".

Drug patents often cover things like "using the same body mechanism to achieve a desired result".

(Now, you can argue this is necessary to protect them, but let's be clear - it's not straight copying if i make a pill with a completely different chemical composition that ends up triggering the same mechanisms. However, it likely runs afoul of their carefully drafted patents.

I'm also aware there are chemical compound patents that would not cover me doing this, but usually, when the drug companies can, they get both)

"Intel spends billions a year on semiconductor R&D, and protects it with trade secrets"

and design mask protection (see https://en.wikipedia.org/wiki/Integrated_circuit_layout_design_protection)

"Pharma companies spend billions on drug R&D and protect them with patents. "

They are also heavily subsidized, unlike your intel example. Tax payers, for example, pay about 50% of pharma's R&D costs (and pharma includes a lot more than actual R&D in R&D cost).
http://www.healthnewsreview.org/2012/02/the-costly-myths-about-pharmaceutical-rd/

and
http://www.thefiscaltimes.com/Columns/2012/02/16/What-Those-New-Super-Drugs-Really-Cost#page1

"Hard R&D that isn't…

> "Healthcare providers will be using our platform to gain access to next-gen diagnostic algorithms"

And what is the nature of these "next-gen diagnostic algorithms"? Are they the research results of medical experts published to medical journals using limited data sets on limited populations that promise to magically cure each and every malady of any patient population, or rather, is a more realistic example of a "next-gen diagnostic algorithm" something not useless, but less grandiose, such as algorithm that tries to address the likelihood of a narrow problem like sepsis occurring in the ICU?

When there are competing algorithms/research papers around the same topic, how do you decide which algorithm is best? And how "actionable" is the algorithm's prediction?

All this reminds me a little of IBM Watson marketing and MD Anderson Cancer Center, where the hype machine generated high expectations, and the results did not match the hype.

"IBM pitched its Watson supercomputer as a revolution in cancer care. It’s nowhere close": https://www.statnews.com/2017/09/05/watson-ibm-cancer/

"MD Anderson Cancer Center’s IBM Watson project fails, and so did the journalism related to it": https://www.healthnewsreview.org/2017/02/md-anderson-cancer-centers-ibm-watson-project-fails-journalism-related/

Google's DeepMind Health also seems worth mentioning in this context:…

Most evidence does not suggest this.

2015: "[...] the NIH made the bold announcement that intensive intervention with a combo of three drugs to reach a new target systolic blood pressure of under 120 mm Hg reduced the rate of heart attacks, heart failure and stroke by 30% and cardiovascular deaths by 25%, "

http://www.healthnewsreview.org/2015/09/nih-sprint-study-sparks-questions-about-overtreatment-of-mild-hypertension/

http://www.cochrane.org/CD000028/HTN_blood-pressure-lowering-drugs-reduce-stroke-and-heart-attack-in-elderly-people-with-hypertension

http://eurheartj.oxfordjournals.org/content/early/2012/04/16/eurheartj.ehs075

http://www.escardio.org/The-ESC/Press-Office/Press-releases/Last-5-years/Antihypertensive-therapy-reduces-CV-events-strokes-and-mortality-in-older-adult

There's more evidence available.

Radicava was approved in Japan in 2015 and by the FDA in 2017 to treat ALS though presumably most of the research for it occurred long before then.

It costs $145000 per year in the US and $35000 per year in Japan. It slows down the progression of the disease in a specific subset of patients (early stages of the disease with rapid progression of symptoms) which comprises approximately 7% of people with ALS. Trials among a general ALS population failed to show any efficacy.

https://www.healthnewsreview.org/2017/09/facts-about-the-new-als-drug-radicava-that-youre-unlikely-to-see-in-news-stories/

I chose one at random, it didn't explain an underlying mechanism why vitamin D might have such a large range of health benefits like you claim.

It is quite easy for an organisation to p-hack. It's also quite easy for an organisation to ignore correlation vs causation.

So I was wanting to know in summary (a blog is fine) what the underlying mechanism is to which vitamin D could solve so many problems.

[edit] I'll add an article critical of your way of researching - https://www.healthnewsreview.org/2017/03/vitamin-d-cancer-how-can-2-news-releases-from-the-same-study-be-polar-opposites/

You way underestimate IBM sales staff.

The real problem is that Watson doesn't work, and health care providers spent millions on it which could have gone to real, actual research.

https://www.forbes.com/sites/matthewherper/2017/02/19/md-anderson-benches-ibm-watson-in-setback-for-artificial-intelligence-in-medicine/#55d873273774

https://www.forbes.com/sites/jasonbloomberg/2017/07/02/is-ibm-watson-a-joke/#51d87341da20

https://www.healthnewsreview.org/2017/02/md-anderson-cancer-centers-ibm-watson-project-fails-journalism-related/