DeSci.Berlin

DeSci Conference | 18 + 19 June 2026 | Alexandrinenstraße 118-121, 10969 Berlin

[DeSci.Berlin @DeSciBerlin]

Two days of talks on the future of DeSci, AI-driven biotech, agentic science, autonomous drug discovery and more!

A huge thank you to our speakers, partners, and everyone who showed up.

Couldn't make it this year? Watch the full talks ↓

[Bio Protocol @BioProtocol]

It took @rakymnft two years just to get tested for a rare genetic condition that runs in her family.

The result finally came through, and then it took another year to share it with her own parents.

To this day, she has no idea who else has a copy of her DNA 🧵

[Bio Protocol @BioProtocol]

"Yes, you should lose weight and exercise but let's cut to the chase...you should be on GLP."

We sat down with Dr. Mohsen Soofian, a board-certified physician who has used peptides in clinical practice for nearly a decade.

Here is what actually holds up. 🧵

[Bio Protocol @BioProtocol]

He sold his last cancer company to Eli Lilly for $300M.

His next one isn't going the traditional route.

Here's the case for DeSci from someone who already won the old game 🧵

[DeSci.Berlin @DeSciBerlin]

Full talk: https://t.co/4R8k7yRvDE

[DeSci.Berlin @DeSciBerlin]

.@aubreydegrey on Taking Rejuvenation to Longevity Escape Velocity

Aging and the diseases of aging run on the same underlying process, accumulated molecular and cellular damage.

Treating the disease without touching the damage rarely works for long.

Targeted damage repair removes that damage directly, before it ever crosses the threshold that causes disease in the first place.

For 50 years, calorie restriction was the best documented way to extend a mouse's life, worth about 4 extra months starting from middle age.
Stacking four separate damage repair interventions in middle aged mice matched that same result, and proved, for the first time, that the effects compound.

Mice given more interventions consistently outlived mice given fewer.

The next study targets 8 or more stacked interventions and a full 12 month extension, tracked through 24/7 AI monitored smart cages.

Longevity research doesn't need one perfect drug. It needs more of what already works, run together.

[Bio Protocol @BioProtocol]

Launching a DeSci project is the easy part.

What breaks teams is everything after: milestones, community, governance, keeping flippers out, all while trying to do the science.

We spent six months building the fix. It involves agents but it starts with a story by @elliossios 🧵

[DeSci.Berlin @DeSciBerlin]

Full talk: https://t.co/vxvccTN7yX

[DeSci.Berlin @DeSciBerlin]

Communities have raised real capital for science again and again over the past few years.

The same problem shows up every time.

Funders never get research progress reported back, and the underlying data stays siloed inside the project instead of reaching the people who funded it.

Molecule Labs ( @molecule_sci) fixes this directly.

Researchers spin up a project page in minutes, drop in decks, data sets, and milestones as they happen.

Every action gets versioned, timestamped, and made either public or encrypted depending on what the contributor chooses.

MIRA, an AI agent built on top of this same data, reads a project's public lab activity and scores its readiness level automatically.

Funders finally get a real signal before they have to dig through a data room themselves.

[Bio Protocol @BioProtocol]

Most great science dies in the same place: the gap between a good idea and the money to test it.

Ryan from Bio opened with that problem at DeSci Berlin, then showed what's being built to close it.

It is called OpenLabs 🧵

[Molecule @Molecule_sci]

Missed @desciberlin?

Our recap blog is the fastest way to get updated on where autonomous research, wet lab robotics, and compliant IP funding actually stand right now

🔗 below!

[Bio Protocol @BioProtocol]

A guy designed a cancer vaccine for his dying dog using AI.

And it worked.

It is a preview of how we cure diseases next.

Here is the future of science @paulkhls laid out at DeSci Berlin 🧵

[DeSci.Berlin @DeSciBerlin]

Full talks:

- Day 1: https://t.co/k3elYo4iXz
- Day 2: https://t.co/EgUof0FlCh

[DeSci.Berlin @DeSciBerlin]

The 5th edition of DeSci Berlin brought together the people building what science becomes next.

Here's what it looked like from the inside.

[DeSci.Berlin @DeSciBerlin]

https://t.co/SJL3SCmuAb

[DeSci.Berlin @DeSciBerlin]

Highlights and key takeaways from Day 2 of DeSci Berlin 2026👇

→ @vitarnabio targets a mutation tied to both cancer risk and accelerated aging, one drug, two disease mechanisms. Early mouse data already shows a 4x increase in tissue uptake across the heart, brain, and liver.

→ Most AI in drug discovery still needs a human to check the data, submit the order, and read the result. @peptai_ removes all three, designing candidates, paying a wet lab directly through x402, and reading results back with no human in the loop. Every candidate gets minted onchain as IP through @Molecule_sci, so the trail survives even if the experiment fails.

→ Open Labs lets a researcher post a single hypothesis and get real feedback from a focused community before any token or funding exists. Stake tokens behind a project, and the yield flows directly to fund the research while the principal stays untouched.

→ On the panel about closing the loop between AI design and the wet lab, one constraint kept coming up. Biology lacks perturbation data, real records of what happens when a specific sequence actually gets changed. Agents can propose endless candidates, but proving any of them still runs on lab time.

→ @adaptyvbio turned wet lab validation into an API call, send a protein sequence, get real binding data back in days. To test it, they pitted AI agents against human protein designers on the same target at a hackathon. The agents matched the best humans in the room, and the top two performers ran on GPT and Grok, no specialized biology model required.

Full talks here ↓

[DeSci.Berlin @DeSciBerlin]

https://t.co/1KGkbCwsm6

[DeSci.Berlin @DeSciBerlin]

Highlights and key takeaways from Day 1 of DeSci Berlin 2026👇

→ @paulkhls: Drug discovery costs $2.5B and takes 10–15 years per approval. Most of that is bureaucracy, not biology. 90–96% of trials fail and half never get published.

→ AI-designed peptide binders cost as little as $7 per design run, generating dozens of candidates at once. What used to take months and tens of thousands of dollars now takes hours. The economics of early drug discovery just collapsed by orders of magnitude.

→ Science is sitting on $21T of untapped real-world asset value, but DeSci's entire ecosystem AUM is only ~$40M. Crypto-native fundraising has already deployed $6.1M across 125 projects with 30,000+ community members and shows that the model works. What's missing is capital.

→ @vitadao funded @Mykalt45's early research through an IP-NFT-anchored grant. It spun into Aeon Bio , which filed one of the first end-to-end DeSci patents. His other company, CrossBridgeBio, sold to @EliLillyandCo for $300M.

→ @dermadao sells two real products today, Moon Drops and Sun Drops. Dongsinne Sohn built the project from her personal experience with severe eczema. Chronic skin conditions are too small for pharma and too niche for big beauty, the exact constraint DeSci is positioned to fill.

→ @foresightinst's warning: Fable 5 access got pulled by export order with 24 hours' notice. If you don't host the model, you don't control your access to it, a hard lesson for anyone building on rented intelligence. Less than 5% of Africa's AI researchers have frontier model access. The gap is growing wider.

→ For 50 years, the best documented way to extend a mouse's life was calorie restriction, worth about 4 extra months. @aubreydegrey's team matched that by stacking several damage-repair therapies instead, and proved for the first time that the effects compound.
Next target: 12 months.

Full talks ↓

[DeSci.Berlin @DeSciBerlin]

> Day 1: https://t.co/dRzMhyapXX

> Day 2: https://t.co/yau6QaScTZ

[DeSci.Berlin @DeSciBerlin]

Two days of talks on the future of DeSci, AI-driven biotech, agentic science, autonomous drug discovery and more!

A huge thank you to our speakers, partners, and everyone who showed up.

Couldn't make it this year? Watch the full talks ↓

[DeSci.Berlin @DeSciBerlin]

Closing out DeSci Berlin, Alex Miloski on what AI agents and on-chain rails change about funding the science.