CTAD24 | Posters & Content

Madrid, Spain | 29 October - 1 November 2024

This week, our team traveled to Madrid to attend CTAD 2024, where they presented several posters and hosted a session on Validating Speech-Based Biomarkers for Measuring Disease Progression in Alzheimer's Disease (AD). These materials are now available for you to access below.

If you would like to chat with the authors, please get in touch using the form below.

Posters

Comparability and Usability of Cambridge Neuropsychological Test Automated Battery (CANTAB®) tests delivered via a smartphone. Emily Thorp
Is there comparability between smartphone and desktop devices used at home on Bring your own device (BYOD), and can norms and other associated measures be relevant to the smartphone format?

P183 Exploring Novel RT-Based Measures Calculated from Detailed Paired Associate Learning Task Data: Preliminary Analyses. Alex Kaula Phd, presented by Nick Taptiklis

Paired Associates Learning (PAL) is typically used to assess episodic memory, but these preliminary analyses suggest reaction time (RT) data from PAL tasks can provide additional insight into cognitive function. This may enhance the sensitivity of PAL and potentially augment RT data from other tasks.

P179 Longitudinal analysis of the factor structure of a multidomain cognitive task battery in ageing and preclinical AD. Nick Taptiklis

Oral Presentation by Michael Spilka, PhD

Validating speech-based biomarkers for measuring disease progression in AD: A head-to-head comparison of three biomarker development strategies.

This session examined the development and validation of a speech-based marker of clinical progression in Alzheimer’s disease (AD). The research highlights how automated speech markers offer a new, objective way to track clinical progression, helping to simplify and complement traditional AD measures.

Key Findings:

Using Existing Patient Interviews: The study leveraged existing Clinical Dementia Rating Scale (CDR) interview recordings, demonstrating the potential to create speech-based markers without requiring additional assessments.
Comparing Three Biomarker Approaches: Researchers compared three methods for generating speech-based scores, finding that their previously validated marker stood out for its simplicity, reliability, and correlation with traditional disease progression metrics.
Broader Application and Patient-Centric Insights: By spanning the continuum from mild cognitive impairment (MCI) to moderate AD, speech-based biomarkers enable a patient-friendly, low-burden way to capture disease progression—an advancement likely to enhance clinical trials and, ultimately, patient care.

This work underscores the growing importance of speech-based biomarkers, which provide an efficient, explainable, and relevant approach to tracking Alzheimer’s progression and supporting more comprehensive insights in clinical research.

Get in touch!

If you’d like to discuss any of the content further, or would like to get more insights from the Cambridge Cognition team, complete the form below and we will be in touch.