High-Dimensional Pharmacology

The text below is a private opinion not linked in any form to my current employee.   So, all hands on deck… the AI revolution everyone was talking about for a long time arrived. I played a bit with ChatGPT for some of the general R&D and chemoinformatics tasks… and saying that impressed is nothing, I am shocked by the quality of the generated text and code, and the future possibilities of those products. Some people claim that ChatGPT will not replace search engines. With a bit of time, it will likely be a merge between personal assistance and worldwide web search engines. ChatGPT and its successors will revolutionize how software is built, increasing productivity while reducing costs. That, in turn, gives programmers more flexibility and time for more complex tasks. Furthermore, these tools can help bridge gaps between different programming languages, making it easier for coders to operate in heterogeneous environments. ChatGPT-like models will overtake enterprise text mining from

  It's been a while, but I found a very interesting paper that I want to comment. Proteomics is an invaluable tool for unlocking the secrets of compound polypharmacology: by quantifying the protein expression changes caused by different compounds, researchers can gain valuable insight into compound interactions at the cellular level. Proteomics in application to the understanding of compound polypharmacology is relatively well established : there are tons and tons of publications on this topic about single compounds or some SAR exploration with 10s of compounds max… and now this goldmine was published – “ A proteome-wide atlas of drug mechanism of action ”. 875 compounds, 875 proteomics profile after 24h treatment (in duplicate) on ~9000 proteins in HCT116 cell line . To be honest, nothing radically new was done in this paper, but the robustness, richness, and accessibility of data that were generated in this paper are, in my opinion, unprecedented. Articles like this have a globa