loopasam

Reasons are mainly: No incentive to develop antibiotics from a legal perspective (FDA), as insurance companies prefer to reimburse the cheap and generic, still working mostly "well enough" for now.

Insurers pay for in-patient antibiotics as part of a lump sum to hospitals known as a Diagnosis Related Group (DRG). Using a cheap antibiotic increases hospital profit margins, while using an expensive new drug could mean that a hospital might lose money by treating a given patient. As a result, hospitals are incentivized to use cheaper antibiotics whenever possible. This puts significant pricing pressure on new antibiotics, which are one of the only type of medicines paid for like this.

The arts saw a $20 billion trade surplus, leading with movies and TV programs and jewelry.

In a pharma setting, the 3D structure of a protein is mostly used to perform drug design (https://en.wikipedia.org/wiki/Drug_design#Computer-aided_dru...), i.e. trying to understand how a chemical will physically interact with a protein and thereby modify it's physiological function, in order to treat a disease.

The biggest problem comes from the fact that proteins are (1) non-static and very flexible and (2) don't exist in vacuum, they interact with a myriad of other entities in a living system. In other words, it's not because you know the structure of a protein and how to theoretically perturb it with a small molecule, that you have a drug. The large majority of structures predicted to be active against a protein target are not, when tested in a biological assay. The process helps, but ultimately it's a very empirical endeavor (test a ton of different chemicals in actual experiments, try to abstract some logic and move on from that). As a result, simply knowing the structure of a protein will not get you far down the line into finding a new drug.

On the resource topic: Even in a very large pharma setting, you will find only a dozen of scientists or so dedicated to the topic (out of tens of thousands employees), supporting many projects and with very little time to perform their own research. As a result, any team fully dedicated to the problem (like AlphaFold) can easily over-compete pharma. Most of the cost in drug discovery comes from dealing with patients and clinical trial. It's only at this stage that you'll know how your drug really works, and how it fits in the existing market and society (think of neuroscience for instance).

I don't want to undermine the protein structure field and AlphaFold results (it's fascinating), but pharma business model de facto relies very little on knowing a protein structure or not. It's also mostly useful to design small molecules, a class a bit out of fashion (biologics are the top-sellers in 2018, and new modalities are coming-up, like RNAs and gene editing for instance).