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A Federated, AI-Curated Clinical Knowledge Archive for Diagnosis and Research

Contributed on Sept 7, 2026 by Stefano Bae

PhD student, La Sapienza University, Rome, Italy

stefano.bae@uniroma1.it

Goal

From Instruments to Reusable Data: an AI Layer for Experimental Data

Capture and Reuse

Contributed on Sept 3, 2026 by Francesco D'Amico

PhD student, La Sapienza University, Rome, Italy

francesco.damico@uniroma1.it

SEE ATTACHMENTS

AI-assisted science needs a collective verification network

Contributed on Sept 2, 2026 by Luca Maria Del Bono

PhD student, La Sapienza University, Rome, Italy

lucamaria.delbono@uniroma1.it

Artificial intelligence (AI) is already changing radically the way scientific research is carried out. Programming, numerical calculations, literature searches, data analysis, or the exploration of alternative hypotheses are increasingly being delegated to AI systems. This allows scientist to focus on more higher level and creative-based tasks. Additionally, this change has the potential to make science much more interdisciplinary. At variance with system-specific research that has been carried out in the last decades, a researcher can now use AI to explore questions that require knowledge or technical tools outside their main field of expertise. A physicist, for example, might use AI to construct a model involving biological mechanisms that they would previously have lacked the expertise or time to investigate.

However, the same development creates a…

Welcome to the First Round !

Submit here you contribution, including name, academic email address and Institution.

In this round we expect that most contributions will consist of approximately one page of text. Other formats are acceptable if you provide a reason for it.

Please provide as an attached supplementary file full details of any AI interactions, including models used, prompts and responses.

Here are the guidelines:

https://www.cellcomm.org/round-1-competition-guidelines

AlphaFold is a major advance for AI in science recognized by the 2024 Nobel Prize in Chemistry. It was made possible by the data of the Protein Data Bank (PDB) and developed by a company, DeepMind.

                  A recent initiative is a collective history called "From PDB to AlphaFold":

https://www.cellcomm.org/from-pdb-to-alphafold

                  This history points to data as key to the synergy between AI companies and academia. Appreciating the implications of this potential synergy could lead to a joint effort to encourage the rest of society to increase support for science. It could also lead to support from the AI industry (for example taking the form of open-source software) for transparent, nonprofit AI dedicated to basic science, which would not compete with commercial applications.

                  As pointed…

AI in Science: virtual cells and organisms

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             We are currently discussing the following message for Foundations about virtual cells and organisms. The most useful virtual organism is clearly a digital human model, a worthwhile task that will benefit all of us, but also a challenge that will require the effort of a large part of the biomedical scientific community.

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Message draft:

"Subject: A non-financial role for [Foundation Name] in advancing virtual cells and organisms.

Quotations from the "REMARKS ON THE DISPROOF OF THE UNIT DISTANCE CONJECTURE" paper that might help non-mathematicians to appreciate its relevance to other scientific fields.

Especially relevant for biomedical problems are the noted ability of AI to find connections among scientific facts that are part of different specialized fields, and the persistence in exploring the implications of these connections.

Noga Alon

" AI was able to do here what lots of excellent human researchers tried and failed to do. Like other mathematicians who had the opportunity to experiment, even if only briefly in my case, with ChatGPT Pro 5.5, my impression has been that AI tools are capable of changing research

in mathematics in a dramatic way. The new spectacular solution of the Erdős unit distance problem convinces me that it is hard to overestimate the full potential impact of this change."

Example of first step of brainstorming on human collective scientific intelligence, with 3 AI models.

- May 2026

PROMPT

The following is the current focus of a discussion among scientists and scholars, shown on the cellcomm.org website. Can you provide a comment about the usefulness of the plan for human health and knowledge, suggestions on how to make it more likely to succeed and an estimate of the likely number of participants after the first Round, after the second Round and after five years?

Trey Ideker has been appointed as the new Director of the University of Oxford’s Big Data Institute (BDI). He will take up the role in June. He is currently a Professor in the Department of Medicine at the University of California, San Diego (UCSD), where he also leads and co-leads several major data-driven research initiatives, including an ADAPT Center for Precision Oncology, the Cancer Cell Map Initiative, and the Bridge2AI Functional Genomics Data Generation Program.

Dear Trey,

What are your plans for the Oxford's Big Data Institute? What is your vision of data science and AI, and, more broadly, of science in this age of advancing AI?

Trey: