FDA is now open to Bayesian statistical approaches. A leap forward!
Bayesian statistics can help:
✅ Clinical trial design
✅ Finding the optimal dose
✅ Extrapolation to children
✅ Leveraging phase 2 results in phase 3
we have enough ideas for peptides
the bottleneck is better systems for testing more compounds, faster, and learning which ones actually achieve desired effects
drug development is fundamentally an uncertainty reduction problem.
centralized funding forces early irreversible bets.
desci spreads risk across parallel experiments and lets capital follow what actually works.
thats why desci wins.
2026 is the beginning of the shift to a decentralized pharma industry
1. biology is too complex for single institutions to explore alone.
2. centralized trials learn too slowly for modern disease timelines.
3. innovation compounds only when experimentation isn’t permissioned.
that last one is the most important. those of us building on decentralized rails will soon be publishing discoveries too significant for trad institutions to ignore.
to my founder friends: use inexperience to your advantage
uncertainty breeds experimentation which is where true growth is born
twenty years of experience often teaches you what's "supposed" to work
sometimes not knowing the rules lets you see what everyone else misses