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Early Alzheimer’s prediction platform secures €21 million investment

The project aims to identify people at risk of dementia before symptoms appear.
More than 7 million people are living with dementia in the EU. This number is projected to double, reaching 14 million by 2050.
There is currently no cure for Alzheimer’s disease. Although the search for potential treatments is showing promise, it is anticipated that these medications will be most effective in the early stages of the disease.
The recently launched AI screening platform, PREDICTOM aims to identify individuals at risk of developing dementia, even before symptoms manifest.
The cognitive and biomarker screening platform has this week announced it will be backed by €21 million in funding, with €8 million from the EU, €9 million from industry and €4 million from UKRI.
A consortium of 30 partners from academia, business, civil society and hospitals is steering the project. The Consortium includes partners from 15 countries across Europe, Asia and America and is led by Stavanger University Hospital.
Dag Aarsland, Professor of Old Age Psychiatry at King’s College London and research lead at Stavanger University Hospital, is the leading the project.
“Detecting early signs of dementia is key to slowing its progression. Unfortunately, a majority of those at risk are not identified in time. Our platform seeks to change this by enabling early discovery, allowing timely intervention and preventative treatment,” Aarsland said.
A crucial aspect of PREDICTOM is that much of the screening can be performed by the patients themselves in the comfort of their homes.
By initiating the process at home, the project aims to reduce strain on healthcare services and associated costs. Biomarkers, including saliva, stool, digital markers and blood via prick-tests, will be collected at participants’ homes or GP offices, streamlining a process traditionally carried out in hospitals or specialised clinics.
More than 4000 participants will partake in PREDICTOM’s trial project. The samples will be based on a pool of people from previous initiatives like PROTECT UK, PROTECT Norway and Radar-AD, as well as people from the catchment area of other participating centres in Germany, France, Switzerland, Belgium and Spain.
“If our project succeeds, there will be significant savings in both cost and time,” Aarsland said
After the home collection, samples will be sent to PREDICTOM, where their platform will process the participant data, integrating blood, cerebrospinal fluid, imaging, electrophysiological and digital biomarkers.
AI algorithms will generate risk assessments, early diagnoses and prognoses, laying the foundation for early intervention and treatment.
This project is part of the Innovative Health Initiative (IHI), a public-private partnership (PPP) between the European Union and the European life science industries.
“We are very pleased to have such a robust team with top notch expertise spanning diverse fields, including IT, AI, medicine, ageing research and professionals from both small and large businesses,” Aarsland added.
The project runs from 1st November 2023 to 31st October 2027.
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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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