Recently, an AI agent called peptAI became popular, designing ADHD candidate peptides within 24 hours at a cost of only a few thousand dollars, directly causing the BIO Protocol token to surge. Half of Crypto Twitter’s bios now include "DeSci," just like six months ago when everyone was frantically adding "AI."

But after reviewing some in-depth analyses, including opinions from well-known industry research institutions, I found that the story behind this is far from simple.

First, let’s talk data: AI-discovered drugs have an 80-90% success rate in Phase I clinical trials, far higher than the traditional 47%. Sounds impressive, but the problem is that Phase I only tests whether the drug is safe, not whether it can cure the disease. In other words, passing Phase I only means your compound won’t kill patients outright; it still needs to go through Phase II and III screening. Currently, fewer than 40 AI-discovered compounds have reported Phase II data, and none have completed Phase III.

Insilico Medicine’s Rentosertib is the most advanced AI-discovered compound now. It announced promising Phase II results in mid-2025, and only started Phase III enrollment in Q4 2025. If all goes well, FDA approval might not come until 2029. The probability of an AI-designed drug completing the entire process is only 60%, and so far, no drug has truly finished it.

Now, let’s look at BIO’s trend: it dropped from $0.89 to $0.018, then rebounded 105% immediately after peptAI news. The current price is around $0.05, with a 24-hour change of -8.86%. Trading volume is $720 million, and market cap is just over $100 million. The problem is, the entire logic of DeSci is built on an assumption: token holders are willing to wait 7 to 10 years for clinical cycles. But in reality? Crypto Twitter quickly shifts to chase the next narrative.

Interestingly, the things that could truly change the game are actually being overlooked. OpenFold3 has been released under the Apache 2.0 license, fully trainable and commercially usable, with performance comparable to AlphaFold3. But since there’s no tradable token, the crypto community isn’t paying attention. The ChEMBL database contains data on 2.5 million compounds, freely accessible. Wet lab validation costs have dropped below $2,000. These foundational infrastructures, which used to cost pharmaceutical companies millions to build, are now on GitHub, with five pharmaceutical companies collaborating on federated training.

Where are the real opportunities? In 2025, U.S. research funding faces issues. Over 7,800 NIH and NSF grants totaling over $5 billion have been frozen. New competitive grants have plummeted from 11,659 to 6,095, a 48% drop. the success rate for researchers’ grant applications has fallen from 21% to 13%. Harvard University lost $945 million, Fred Hutchinson Cancer Research Center lost $508 million.

This is where DeSci can truly make an impact. Projects funded by VitaDAO, like Gero and Chugai Pharmaceutical (a Roche subsidiary), signed agreements with milestone payments of up to $250 million. This is the first case where DAO-funded projects have been valued in the nine-figure range by major pharma companies, and the entire process occurred without governance chaos or跑路.

But this requires a premise: professional governance. Even if AI can cut drug development time in half, it still takes 4 to 5 years from discovery to approval. In an investment market that can shift within a quarter, that’s a long wait. So, DeSci needs more than just a few months of quick pivoting; it needs to build a financing infrastructure tightly bound to clinical milestones and led by professionals.

This year, 15 to 20 AI-discovered drugs are entering Phase III, with Rentosertib’s data not expected until 2028 at the earliest. Regardless of token price fluctuations, open-source tech stacks continue to reduce costs, and the funding vacuum is pushing researchers to find willing investors. Between these two forces, there may indeed be a viable model.