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In honor of Alzheimer's Awareness Month, we’re exploring the science and stories surrounding Alzheimer’s disease.
Updates every hour. Last Updated: 26-Oct-2026 00:16 ET (26-Oct-2026 04:16 GMT/UTC)
HONG KONG, August 28, 2026 — Insilico Medicine ("Insilico"), a clinical-stage biotechnology company powered by generative artificial intelligence (AI), today announced the publication of a landmark study in Alzheimer's & Dementia: The Journal of the Alzheimer's Association. In close collaboration with researchers from the University of Oslo (UiO) and Akershus University Hospital (Ahus) led by Dr. Sofie Lautrup and Prof. Evandro Fei Fang, the team utilized Insilico's proprietary AI biology platform, PandaOmics, alongside extensive experimental validation to uncover new molecular targets for Alzheimer’s disease (AD) and other neurodegenerative conditions.
The research provides compelling evidence that the impairment of the NAD⁺-mitophagy axis plays a central role in both healthy brain aging and neurodegeneration. By examining large-scale human data, the team demonstrated that interventions modulating mitochondrial metabolism hold profound potential for diagnosing and treating age-related cognitive decline.
Regular aerobic exercise – the kind that gets your heart pumping – can improve important thinking skills called executive functions, and the benefits appear especially strong for women after menopause, according to Rutgers researchers.
Phosvitin, a rich phosphoprotein found in egg yolks, is the starting material for phosvitin phosphopeptides (PPPs), a powerful and potentially impactful dietary delivery agent to relieve oxidative stress that can lead to neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. Results show promise with PPPs, including increasing cell viability, free-radical reduction and inhibitory activities that promote cell protection.
In a new study, researchers describe the development and validation of a multi-ancestry polygenic risk score (PRS) for AD that performs much better than previously constructed ones, especially for genetically diverse groups. This expanded representation of population groups is crucial for developing more robust and universally applicable PRS models, which can improve risk prediction among an ancestrally diverse group of patients.