
The pharmaceutical industry is in a drug-discovery slump. How much can AI help? - vo2maxer
https://www.nature.com/articles/d41586-019-03846-0
======
aaavl2821
The oft cited $2.6B cost to develop a drug is derived from data from big
pharma drug development programs. There is some evidence that startups are 5x
more efficient at developing drugs [0]

The last several years have seen large increases in the number of new FDA
approved drugs. The number of FDA approved drugs developed by big pharma is
roughly constant, while the number being developed by startups is increasing

AI can certainly help improve R&D productivity, but it is far from the only
lever. Better risk management, clinical trial design, advances in protein
engineering, larger genomic datasets analyzed with "traditional" statistical
methods, better disease models, new therapeutic modalities, etc have all
contributed to more efficient R&D productivity over the last decade and will
continue to do so. But these don't get much attention outside of the pharma
industry

[0]
[https://www.baybridgebio.com/blog/rd_bigpharma_startup.html](https://www.baybridgebio.com/blog/rd_bigpharma_startup.html)

~~~
denzil_correa
> The oft cited $2.6B cost to develop a drug is derived from data from big
> pharma drug development programs.

This number can not be validated as most of the information is not public.
It's a self-reported number and should be treated as such.

[https://www.reuters.com/article/pharmaceuticals-
tufts/correc...](https://www.reuters.com/article/pharmaceuticals-
tufts/corrected-tufts-says-average-new-drug-costs-2-6-bln-to-develop-critics-
wary-idUSL2N0T82C620141118)

~~~
aaavl2821
I don't think that number is too crazy. I did my own back of the envelope
analysis and got $1.5B in early stage r&d spend per approved drug discovered
by big pharma. If you add a few hundred million for late stage r&d (big pharma
spends about the same on late and early stage r&d) and then include cost of
capital its in the ballpark of that number

------
denzil_correa
> “In some cases, we might be allowed to pass over animal models and go
> straight to human testing once we show these drugs can hit their targets
> with no toxicity.” But those changes are probably many years away, he
> admits. He adds that it is wrong to imply that AI replaces scientists and
> conventional research—whereas AI supports and amplifies human efforts, it
> still depends on humans to generate novel biological insights, set research
> directions and priorities, guide and validate results, and produce needed
> data.

This paragraph succinctly summarizes the current situation, future hope and
effort required.

------
cde-v
I wasn't aware the pharmaceutical industry was still trying to discover new
drugs. Seems like they are more focused on marketing and keeping their drugs
(or their drugs, but with slight modifications) under patent.

~~~
mft_
Interesting; can I ask what your opinion was based on?

A quick Google gives a couple of sources; admittedly, the devil's usually in
the details, but they should be enough to convince that there is significant
amount being spent on research:

[https://www.bbc.com/news/business-28212223](https://www.bbc.com/news/business-28212223)

[https://www.raps.org/news-and-articles/news-
articles/2019/7/...](https://www.raps.org/news-and-articles/news-
articles/2019/7/do-biopharma-companies-really-spend-more-on-market)

------
Der_Einzige
Better dimensionality reduction techniques are high up there. How do we get
better than UMAP?

