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French biotech raises €12m for osteoarthritis trial

A French biotech has raised €12m to test whether GLP-1 drugs can modify osteoarthritis progression.
The funding will advance 4Moving Biotech’s lead programme, 4P004, toward a phase 2a proof-of-concept readout in knee osteoarthritis, a joint disease that causes pain and stiffness.
Despite affecting more than 600 million people worldwide, no therapy approved in Europe or the US has yet been shown to slow or modify disease progression in osteoarthritis.
4Moving Biotech is testing whether GLP-1 receptor agonists, drugs best known for diabetes and obesity, can succeed where others have fallen short.
“With this closing in place, we are well equipped to reach the next value-creation milestone by delivering robust phase 2a data and reaching a proof-of-concept inflection point,” said Luc Boblet, chief executive of 4Moving Biotech.
Rather than systemic administration, the company is testing whether GLP-1 biology can be made relevant to osteoarthritis by acting directly in the joint, targeting local inflammation and tissue responses that systemic approaches have repeatedly failed to address.
“By acting directly in the joint, 4P004 tackles pain, inflammation and tissue damage through GLP-1-mediated pathways,” said professor Francis Berenbaum, the company’s chief medical officer.
The study is designed to assess “dual efficacy: symptom relief and synovial health improvement via contrast-enhanced MRI,” which images the joint lining, with topline results expected in the second half of 2026.
The round was secured from private investors and family offices investing directly into 4Moving Biotech, a subsidiary of 4P-Pharma, and combines equity with loans, a structure the company says is aligned with long-term value creation.
It follows a €7.6m France 2030 i-Démo grant awarded last year and coincides with the transatlantic expansion of the INFLAM-MOTION phase 2a study to the US.
Founded in 2020 as a spin-off from 4P-Pharma, 4Moving Biotech has now raised around €30m in total, combining private capital with non-dilutive public funding.
The broader landscape for disease-modifying osteoarthritis drugs offers little room for overconfidence.
A 2025 review of phase two and three osteoarthritis trials found that while “many DMOADs have progressed to clinical trials, very few have made a significant impact and none have been approved for clinical use.
Reviewing eleven candidates tested between 2010 and 2024, including small molecules, biologics and cell or gene-based therapies, authors conclude that failure has been driven less by any single mechanism than by the difficulty of demonstrating truly disease-modifying benefit.
Several programmes reported statistically significant effects on either pain or joint structure, but rarely both.
The review notes that “the clinical relevance of a marginal increase in one without the other remains unclear,” warning that structural effects without symptom relief may be clinically meaningless, while pain relief without structural protection could even accelerate disease progression.
Over the past decade, major programmes at Pfizer, Eli Lilly, AbbVie, GlaxoSmithKline and Sanofi have been discontinued or deprioritised after failing to deliver regulator-acceptable evidence of disease modification.
In 2020, Unity Biotechnology reported phase two data showing that its senolytic candidate UBX0101, developed as a disease-modifying therapy for knee osteoarthritis, failed to deliver clinically meaningful improvements in pain or joint structure.
Unity subsequently discontinued its osteoarthritis programme, exited the field entirely and ceased operations in 2025.
The phase 2a readout will be the point at which the GLP-1 approach in osteoarthritis either earns its next chapter or joins a long list of programmes that fell short.
Research
Mole rat gene extends mouse lifespan
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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