At the Helsinki Chemicals Forum 2026, experts explored the challenges of implementing the European Commission’s roadmap, from bridging the gap between research and regulatory adoption to building confidence in new approach methodologies (NAMs).
Dr Gilberto Dias de Alkimin, a Regulatory Ecotoxicologist with the Regulatory Affairs department at Charles River Laboratories, provided some updates from this event. In his article, he highlighted that some panelists stressed the need for dedicated funding to support research and validation of non-animal methods, ensuring that future policy decisions are grounded in robust science. He also mentioned that NAMs must be scientifically strong, accepted by regulatory authorities, standardised to support industry compliance and mutually accepted at EU and international levels.
17 days after the official release of the European Commission’s roadmap, the high impact scientific journal Nature published an editorial entitled: “The EU needs to back its ambition to end animal testing with cash.”
The conclusion is clear: “The EU’s roadmap is an important statement of intent, and underscores its commitment to animals as sentient beings. But EU leaders must reconsider the level of their funding commitment if they want to achieve their ambition, and the milestones must have timelines attached. That will enable them to be held to account, including by those whose advocacy set them on the current path.”
Read-across is one of the most widely used in silico approaches for filling data gaps in safety assessments without generating new animal data. However, read-across is not always applied or documented consistently. Regulators increasingly expect a clear scientific hypothesis, systematic analogue selection, transparent uncertainty evaluation, and robust documentation of decision-making.
The International Collaboration on Cosmetic Safety (ICCS) just published the Read-Across Best Practice Guidance which was developed to help address that gap. The guidance provides a structured, transparent, and practical framework for conducting read-across assessments that support both human health and environmental safety evaluations.
Traditionally, the movements of molecules have been simulated using what is known as molecular dynamics, in which researchers calculate the forces between all the atoms step by step and move them a tiny bit at a time. The use of AI now enables researchers to detect molecular changes without having to perform numerical calculations.
A group of researchers from Chalmers University of Technology and the University of Gothenburg, Sweden, has now taken another step forward by developing a new AI model that could, in the long term, make drug development testing even more efficient. The new model is more than 10,000 times faster than conventional simulations. The findings are being presented in a new study published in Science Advances.
On June 10, 2026, the American Chamber of Commerce in Germany (AmCham Germany) presented its 7th Female Founders Award in Munich. This year’s award recognizes entrepreneurs whose innovations have the potential to create impact far beyond their home markets.
One of the two winners is Ghazaleh Madani, Founder & CEO of CanChip: “Less than three years ago, CanChip was just an idea driven by a simple belief: drug development can be better. Faster. More predictive. More human. Today, CanChip is developing advanced tumor-on-chip and organ-on-chip systems that help researchers and pharmaceutical companies better understand diseases and evaluate therapies before they reach patients.” she says.
Bridging the gap between the development and broad application of non-animal innovations is vital. To accelerate this transition, ZonMw launched the NAM Collaboration Grant, made possible by a financial contribution of The Dutch Society for the Replacement of Animal Testing (Proefdiervrij).
This call specifically targets intensive, hands-on knowledge transfer for culturing and analyzing human primary or iPSC-derived cells within complex 3D contexts, such as organ-on-chip systems or organoids. Applications are assessed on a first-come, first-served basis. The call is open and will run until March 30 2027 (14:00 CET) – unless the total available budget is exhausted before that time.
The NIH Office of Research on Women’s Health (ORWH) just announced two newly launched ORISE (Oak Ridge Institute for Sciences and Education) postdoctoral fellowship opportunities, which offer an outstanding avenue for early‑career scientists to gain high‑impact scientific training while advancing NIH-wide efforts in women’s health, data science, and innovative NAMs.
Key date for applicants: July 1, 2026 – Initial application deadline. Thereafter, applications will be reviewed on a rolling-basis throughout the 2026 calendar year, and selections made as projects for participation become available.

To see more calls: Check out our calls interface
An estimated 5 to 8 % of people in Germany suffer from an autoimmune disease such as asthma, rheumatoid arthritis, or inflammatory bowel disease. To significantly accelerate research to treat these conditions, Markus Rehberg, research engineer at the Translational Medicine Unit (TMU) of the Sanofi BioCampus in Frankfurt, is working at the intersection of engineering, mathematics, and biology.
He and his team create so-called virtual patients to model the effectiveness of new drugs before they are tested in clinical trials. “It’s a labor-intensive process, but it allows us to understand biological relationships and the differences between patients,” explains the engineer.
Preclinical toxicology study reports contain the expert interpretations required to distinguish test article-related effects from incidental findings, yet these conclusions often remain embedded in unstructured text form that limit systematic reuse and integration with computational safety approaches.
To address this gap, researchers developed a Large Language Model (LLM) combining automated document preprocessing, section identification, schema-constrained information extraction, and semantic harmonization, complemented by targeted human curation. They evaluated the system performance using 200 Roche toxicology study reports, encompassing clinical pathology, histopathology, exposure data, and more. Across domains, extraction performance was characterized by consistently high sensitivity (typically above 95%) and precision (frequently exceeding 97%) for most parameters. These results demonstrate that LLM-assisted extraction can reliably capture expert toxicological interpretations at scale and provide a foundation for data-centric safety assessment, strategic decisions, reverse and forward translational toxicology research.
Read the publication in Archives of Toxicology
Histology has been a cornerstone for complex in vitro model (CIVM) characterization for decades. However, it remains a low-throughput method with time-consuming workflows.
A research team led by Nikolce Gjorevski at Roche developed a holistic “histo-workflow,” utilizing 3D-printed histomolds that facilitate co-planar embedding of CIVMs at high throughput, resulting in up to 80 samples in one section, that enable spatially controlled histological sectioning and downstream analyses. Altogether, the histomolds afford opportunities for CIVM processing and analysis, while significantly reducing labor and reagent resources, thereby democratizing high-throughput handling of CIVMs in histopathology.
Read the Group Leader’s post on Linkedin
Read the publication in Cell Reports Methods
Accurate representation of brain morphology is critical, as more complex organoid structures better mimic the human brain. Deep learning (DL) and machine learning (ML) approaches have become integral to analyzing organoid morphology, yet tools for comprehensive, time-resolved assessments are scarce.
A group of researchers at Izmir Biomedicine and Genome Center (IBG) introduced BrAIn, a DL-based application for analyzing the developmental progression of brain organoids (BOs). The tool tracks BOs evolution from embryoid bodies (EBs) and quantifies physical parameters. It also classifies abnormal morphologies and detects key features of neuronal differentiation. BrAIn emerges as a robust, user-friendly tool to quantify BO development and explore how versatile growth conditions influence their morphology and maturation.
Read the publication in Bioengineering & Translational Medicine
Human embryo implantation is a complex and finely regulated process relying on dynamic cross talk between maternal and fetal tissues.Traditional endpoint analyses often miss transient or subtle cellular behaviors critical to this process.
To overcome these limitations, researchers developed a cost-effective, rapidly prototyped implantation-on-chip (IOC) device that mimics the maternal – fetal interface within an AI-integrated platform that enables continuous, in situ monitoring of early implantation events with high spatiotemporal resolution. By combining microfluidics, live-cell imaging, and artificial intelligence, they can automatically track and quantify key implantation-related behaviors, providing a powerful tool to study early pregnancy mechanisms and assess the impact of environmental factors.
Read the publication in Advanced Intelligent systems
3Rs Collaborative & IQ Consortium Revisiting Liver MPS – Webinar recording
Comparing the US, UK, and EU Roadmaps for Phasing Out Animal Testing: A Pharmaceutical Lens – by Michael Phelan, PhD
European Commission publishes first Joint Clinical Assessment on innovative medicine
AI-enabled 3D liver microtissue analysis for improved toxicity screening – an application note from Molecular Devices on Drug Discovery News website.
Pharma Boardroom interview with Nathalie Moll – Director General, EFPIA
2026 ESTIV Congress: “Ensuring Safety, Advancing Science: Bridging to the Future with NAMs” – June 29 to July 2, Maastricht (The Netherlands)
NAT-Net Vanguard Symposium: Leading the Future of Health Research – June 29, 1am — 9am CEST, Online
2026 NAMeRS Summit, A NAMolution: How the Next Generation of Scientists Is Leading the Next Generation of Science – June 29, 8:30 am — 5:30 pm EDT, Online
3d.FAB Scientific Days — 11th edition – June 30 to July 2, Lyon (France)
