25/05/2026
I've spent 40 years watching pharma evolve.
New molecules. New regulations. New manufacturing paradigms. I thought I'd seen it all.
Then AI started predicting protein structures in hours that used to take us years.
Here's what that really means on the ground:
โ Fewer failed trials because target validation is sharper
โ Formulation development compressed from months to weeks
โ Adverse effect signals caught earlier in silico, not in Phase III
But here's my honest take โ and maybe it's the GMP auditor in me:
The speed AI brings means nothing if the data quality feeding it is poor. Garbage in, garbage out. I've seen spotless-looking AI outputs built on shaky analytical data foundations.
The technology is extraordinary. The discipline around it still needs to catch up.
We're not replacing the scientist or the QP. We're raising the stakes for how rigorous we need to be with our underlying science.
๐ช๐ต๐ฎ๐'๐ ๐๐ผ๐๐ฟ ๐ฒ๐
๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ โ ๐ถ๐ ๐๐ ๐ด๐ฒ๐ป๐๐ถ๐ป๐ฒ๐น๐ ๐ฐ๐ต๐ฎ๐ป๐ด๐ถ๐ป๐ด ๐ต๐ผ๐ ๐๐ผ๐๐ฟ ๐๐ฒ๐ฎ๐บ ๐๐ผ๐ฟ๐ธ๐, ๐ผ๐ฟ ๐ถ๐ ๐ถ๐ ๐๐๐ถ๐น๐น ๐บ๐ผ๐๐๐น๐ ๐ต๐๐ฝ๐ฒ ๐ถ๐ป ๐ฑ๐ฎ๐-๐๐ผ-๐ฑ๐ฎ๐ ๐ฝ๐ต๐ฎ๐ฟ๐บ๐ฎ ๐ผ๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐?