Investigación aplicada

iACE-SS

A new study led by Ace Alzheimer Center aims to determine whether, in addition to improving certain symptoms, the standard treatments for Alzheimer’s disease (donepezil, galantamine, and rivastigmine) can also influence spontaneous speech, and whether technology can measure these changes in a more sensitive, objective, and accessible way.

The main objective of the iACE-SS study is to evaluate the effect of cholinesterase inhibitors (donepezil, galantamine, and rivastigmine) on spontaneous language in patients with mild dementia associated with Alzheimer’s disease, over a 52-week prospective follow-up. The study is based on the hypothesis that changes in spontaneous language may constitute a sensitive digital biomarker for detecting and monitoring response to symptomatic treatment in the early stages of the disease, complementing traditional cognitive assessments.

Specific objectives and methodology

Specifically, the study aims to analyze the relationship between changes in cognitive performance and modifications observed in spontaneous language, comparing measures obtained through classical paper-based neuropsychological tests with those derived from digitalized and automated tools, such as the Linus Health (CCE) system and the PUNTO (iACE-SS) platform. This approach seeks to determine whether computational speech analysis enables earlier and more precise detection of clinical evolution associated with treatment with ChEIs.

Language analysis and algorithm development

Another central objective is to develop and validate algorithms capable of longitudinally quantifying the evolution of spontaneous language in patients with mild Alzheimer’s disease treated with cholinesterase inhibitors. To this end, acoustic, linguistic, and semantic variables extracted from structured, semi-structured, and unstructured tasks are analyzed, with the aim of identifying speech parameters sensitive to changes induced by pharmacological treatment.

Neurophysiological markers

The study also incorporates longitudinal electroencephalography (EEG) to evaluate whether specific markers of brain activity—both quantitative EEG measures and event-related potentials—are useful for identifying and characterizing patients who respond to symptomatic treatment. The correlation between changes in these neurophysiological markers, cognitive evolution, and modifications in spontaneous language is analyzed, exploring their potential value as functional biomarkers of therapeutic response.

Integration of biomarkers and personalized approach

Finally, the study integrates changes in speech, digitalized cognition, EEG markers, and other clinical and plasma biomarkers, exploring potential differential effects according to variables such as sex, ApoE genotype, vascular burden, or biomarker profile. The ultimate goal is to move toward personalized models for monitoring treatment response using non-invasive, low-cost, and easily scalable tools suitable for routine clinical practice.