Imagine a machine learning paper that released no code, and no data, and was funded by public money, and the IP was owned by a startup that was also funded by p

Imagine a machine learning paper that released no code, and no data, and was funded by public money, and the IP was owned by a startup that was also funded by public money, and the PI was on the payroll. Laughable, right? Generally there is more trust when the theory, the data collection, the data analysis, the model development, the product, and the application, are all completely separate and open. It also advances the science much faster. However, it definitely kills a lot of those monopoly profits. I propose that there’s really no reason that pharmaceuticals research can’t progress in this manner, with great public benefit. And it would be so simple to enforce: all public grants require everything to be developed in the open, not just data release at the time of publication, or pre-registration, but full release at each stage, no patents, and a preference for funding independent dataset production rather than results. As it is, we pay for the research, then we pay monopoly prices for the drug. It’s like these companies don’t really do anything but collect money. Also, If anybody knows of a way to donate money to cancer research in a way that doesn’t feed directly into somebody’s profits, please let me know. I have recently become loosely connected to a foundation that has been dumping a lot of money into Dana Farber, and this is highlighting a lot of my concerns as I learn more about the industry.