Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Two exciting revolutions in science and technology — in AI and in omics — now enable the construction of cell models learned directly from data, providing an unprecedented opportunity for an ambitious vision of an AI virtual cell (AIVC), a multi-scale, multi-modal, large-neural-network-based model that can represent and simulate the behavior of molecules, cells and tissues across diverse states.
This AIVCs design will transform biological research by allowing high-fidelity simulations, accelerating discoveries, and guiding experimental studies, offering new opportunities for understanding cellular functions and fostering interdisciplinary collaborations in open science.
On February 28th, the European Commission adopted its proposal for a Council Recommendation on the European Research Area Policy Agenda 2025 – 2027.
The following ERA actions are proposed for the next three years : accelerating R&I investments for Europe’s industrial transformation and competitive sustainability;accelerating new approach methodologies (NAMs) to advance biomedical research and testing of medicinal products and medical devices ; a harmonised and coordinated framework for a European approach to integrity and ethics in R&I in the face of emerging challenges.
The Humans of the Wyss (HOW) series features members of the Wyss Institute community discussing their work, the influences that shape them as professionals, and their collaborations at the Wyss Institute and beyond.
Read the interview of Yunhao Zhai who joined the Wyss four years ago, after studying biochemistry, molecular biology, and immunology in China and France. Now, he is using human Lymph-Node-On-Chip to screen potential therapeutics and eventually increase the success rate of clinical trials.
The Innovation Santé 2030 plan launched a call for projects in 2023 for “Chairs of excellence in biology/health” aimed to strengthen the excellence of French biomedical research, and provide funding for research teams for five years. The first 22 winners were rewarded in 2024, and FC3R met one of them.
Dr Mohamed-Ali Hakimi is Inserm Research Director and heads a team specializing in parasitology at the Institut pour l’Avancée des Biosciences (IAB) in Grenoble (Inserm, CNRS). The project led by Dr. Hakimi proposes to study the Toxoplasma gondii parasite using in vitro cell cultures, thus replacing cats, usually used in research to better understand infection by this parasite.
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A new two-phase call for projects, with a total budget of 13.5 million euros, was launched on March 3, 2025 to encourage multidisciplinary research initiatives aimed at transforming the field of biotherapies. The aim ? To design new therapeutic solutions, optimize biomanufacturing processes and enhance their social acceptability.
This call for projects offers a unique opportunity to innovate in the field of biotherapies by bringing together diverse expertise to tackle scientific, technological and societal challenges. If you are a French academic team ready to collaborate and push back the frontiers of knowledge, this call is for you. Call deadline : April 17, 2025
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Owkin, a pioneer in Agentic AI for decoding the complexities of biology, has launched a comprehensive multimodal patient data discovery program to accelerate multimodal data access and advance medical research.
Initiated in September 2024, the program will map 11 therapeutic areas across Owkin’s extensive transatlantic network, with completion expected by May 2025. The data discovered in this program will power Owkin K, Owkin’s software, driving faster discoveries and improving patient outcomes worldwide.
Illumina announced a collaboration with the Broad Institute on a Spatial Flagship Project aimed at advancing spatial transcriptomics research using Illumina’s newly developed spatial technology platform designed to enable whole-transcriptome profiling with cellular-level resolution across large tissue samples with four times greater resolution.
“Spatial transcriptomics opens entirely new pathways to gain crucial insight into the cellular function of organisms,” says Steve Barnard, PhD, chief technology officer of Illumina.
A team of scientists from the University of Toulouse, Toulouse University Hospital and Inserm have achieved a double breakthrough that could have implications for the optimization of medically assisted reproduction (MAP) techniques. Not only have they succeeded in manufacturing functional human fallopian tube organoids, but they have also demonstrated that their use enables sperm mobility to be maintained at levels higher than those obtained in the culture media currently used for MAP.
These results are published in the January issue of the journal Human Reproduction.
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The developing human brain displays unique features that are difficult to study in animal models. A research team in the Netherlands established culture conditions to derive organoid cultures directly from human fetal brain tissue by preserving tissue integrity, which can be long-term expanded and display cellular heterogeneity and complex organization.
The team published a protocol which describes detailed procedures to establish human fetal brain organoids (FeBOs) that broadly retain regional characteristics, along with procedures for their passaging and characterization. In addition, they describe genome engineering approaches applied to FeBOs to generate mutant FeBO lines that serve as versatile bottom-up brain cancer models.
Read the publication in Nature Protocols
A new work evaluated a non-animal toolbox to be used within a next-generation risk assessment (NGRA) framework to assess chemical-induced lung effects using human upper and lower respiratory tract models, namely MucilAir™-HF and EpiAlveolar™ systems, respectively.
The findings suggest that combining computational and in vitro new approach methodologies (NAMs) informed by adverse outcome pathways (AOPs) associated with pulmonary toxicity can provide relevant biological coverage for chemical lung safety assessment.
MLinvitroTox is a machine learning (ML) framework developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS).
A research group just released a Python MLinvitroTox v2 package, which, in addition to automation, expands functionality to include predicting toxicity from structures, cleaning up and generating chemical fingerprints, customizing models, and retraining on custom data. Furthermore, as a result of improvements in bioactivity data processing, the current release introduces enhancements in model accuracy, coverage of biological mechanistic targets, and overall interpretability.