Cambridge Cognition

Adding speech to a CANTAB battery in Alzheimer’s disease/MCI research

Francesca Hazel — Thu, 29 Oct 2026 12:15:50 +0000

Adding speech to a CANTAB battery in Alzheimer's disease/MCI research

After the blood test

In August 2026, the US Food and Drug Administration cleared Roche’s Elecsys pTau217 blood test to aid the assessment of amyloid pathology in adults aged 55 and over with signs, symptoms or complaints of cognitive decline.1 Roche describes it as the first single-biomarker blood test cleared to support both ruling in and ruling out amyloid pathology, using the same cut-offs in primary and specialty care.1 For a field long dependent on PET imaging and lumbar puncture, the clearance considerably widens who can be assessed, and in what setting.

The label is equally explicit about the test’s limits. Its safety and effectiveness have not been established for predicting the development of dementia or for monitoring the effect of treatment.1 Plasma markers are increasingly able to establish who carries Alzheimer’s pathology; they say nothing about how memory, attention or language are changing in that person, which is what most MCI and early-AD studies are designed to measure.

Cognitive assessment therefore remains central, and groups designing a test battery face a practical question about its scope. Episodic memory and language abilities are often impacted early in AD and are therefore a typical focus of cognitive assessment. The case for combining measures of both rests on what each captures that the other does not.

Two windows on the same disease

The pairing of memory and language measures has a long precedent. Blackwell and colleagues followed 43 memory-clinic patients with questionable dementia for 32 months, during which 11 received a diagnosis of probable AD.2 At baseline, those who later converted had made substantially more errors at the six-pattern stage of CANTAB® Paired Associates Learning (PAL) than those who did not (mean 31.0 vs 6.6).2 The best-fitting model in that sample combined PAL with the Graded Naming Test, a pen-and-paper word-finding test. The authors attributed this to anatomy, with PAL dependent on the transentorhinal and hippocampal regions in which Alzheimer’s pathology first appears, and naming on the temporal neocortex.2

Connected speech engages that second set of processes directly. Describing a picture or recounting the previous week draws on lexical retrieval, semantic knowledge, syntactic planning and memory for recent events. From a few minutes of such speech, the Winterlight pipeline derives several hundred acoustic, lexical, semantic and syntactic measures, ranging from pausing and speech rate to word frequency and the semantic relevance of a description to its stimulus.3,4 A meta-analysis of pause and rate measures found that people with AD and, to a lesser degree, MCI showed longer pauses than controls; speech rate also differentiated the groups.5 These pausing and rate differences may reflect the lexical retrieval difficulties, reduced verbal fluency, and executive planning deficits that characterise MCI and AD, consistent with the progressive temporal and frontal lobe changes that underlie these conditions.

Memory as an early marker

Much of the CANTAB evidence in early AD derives from PAL, a measure of visual memory and associative learning. A 2023 study from Perugia examined how CANTAB performance relates to CSF biomarkers in people at the threshold of impairment. Chipi and colleagues assessed 74 consecutive memory-clinic patients with subjective cognitive decline and available CSF results for amyloid (A+) and tau (T+) positivity, using both a traditional pen-and-paper battery and three CANTAB tasks: Pattern Recognition Memory (PRM), PAL and Spatial Working Memory (SWM).6

None of the seven participants who performed normally on both assessments had an AD-like CSF profile (A+/T+), compared with 14 of the 35 (40%) who showed subtle deficits on both (p = 0.03).6 The authors’ principal conclusion was methodological. At this stage, they argue, reliance on a single test risks over- or underestimating decline, and complementary measures should be combined.6 The argument applies equally to the addition of speech assessment.

What speech adds

A potential advantage of speech is sensitivity to change over short intervals. In a six-month study of 50 older adults assessed on a tablet, global coherence (the semantic relevance of a picture description to the picture’s key content) declined significantly faster in participants with MCI or early AD than in those scoring within the normal range on the MoCA.3 Over the same period, neither the MoCA nor the ADAS-Cog changed significantly, nor did any of the standard neuropsychological tests completed by the MCI/AD group.3

In clinical trials, speech can be obtained without a dedicated task. Recordings of Clinical Dementia Rating (CDR) interviews from the Tauriel phase 2 trial allowed Winterlight to analyse the responses of 130 participants with amyloid-confirmed prodromal-to-mild AD to questions about recent experiences from the memory section of the interview.4 A composite of nine acoustic and linguistic features changed over 18 months at a rate comparable to the CDR Sum of Boxes (standardized β 0.29 vs 0.30) and numerically faster than the ADAS-Cog (0.22) and MMSE (−0.23), with similar behaviour in a held-out test set (β 0.26).4 In a subsequent conference poster, the same composite, applied without modification to the placebo arm of a second trial (Lauriet, mild-to-moderate AD), showed a comparable rate of change (β 0.26).7

Speech measures also relate to AD biology. In a further conference poster based on baseline recordings from 429 people with mild-to-moderate AD in a phase 2/3 trial, adding selected speech features to models comprising age, sex and MMSE significantly improved estimates of CSF Aβ42/40, CSF total tau and cortical thickness in AD-related regions.8 The cortical thickness model performed best, with adjusted R2 rising from 0.21 for the base model to 0.35 with speech features added, which the authors suggest may indicate a closer link between speech and current neurodegeneration than between speech and CSF levels of AD pathology.8

CANTAB and speech in one session

Bio-Hermes-002, an ongoing multicentre observational study of adults aged 60–90 with or without memory concerns, examined the two modalities together. In an analysis presented as a poster at AAIC 2026, 353 participants (173 cognitively normal, 180 with MCI) completed CANTAB PAL, the Digit Symbol Substitution Task (DSST) and SWM, together with the Winterlight picture description task (PDT), all administered within the CANTAB app.9

Model (all include age, sex and education)	AUC	Sensitivity	Specificity
Demographics only	0.63	–	–
+ CANTAB (PAL, DSST, SWM)	0.72	0.73	0.63
+ speech features	0.71	0.54	0.78
+ CANTAB and speech	0.75	0.63	0.77
+ MMSE (clinical reference)	0.75	0.60	0.79

Adding speech features to the CANTAB model significantly improved model fit (p = 0.002), though the gain in AUC was modest.9 PAL and DSST were the strongest cognitive predictors, and lexical diversity the strongest speech feature.9 The two modalities differed in their operating characteristics: CANTAB tasks were more useful for ruling in (higher sensitivity) and speech for ruling out (higher specificity), while the combined model achieved a more even balance between the two.9 Its AUC matched that of the MMSE reference model (0.75 each); the authors note that MMSE scores contributed to the assignment of MCI status, introducing a degree of circularity into the classification.9

Designing a speech protocol for MCI and AD

Speech is measured at three levels: the acoustic properties of the voice, the timing of its delivery, and the linguistic structure and content of what is said. In the AD studies discussed here, much of the signal sits at the linguistic level, in global coherence,3 lexical diversity9 and measures of word type, information content and vocabulary,8 and the speech composite score combined six linguistic features with three acoustic ones.7 Linguistic features depend on an accurate transcript, so recording and transcript quality matter as much as the choice of features.

PDT is the task common to most of the AD evidence above.3,8,9,10 Because the scene is fixed, a description can be scored against the information it contains, the basis of information-content measures such as content units and object units. At the same time, the open-ended nature of the task elicits a rich sample of expressive speech and language, capturing variation in syntax, vocabulary and discourse organisation.9

Speech can also be collected remotely and without supervision. In an Amsterdam study of 50 cognitively unimpaired adults using the Winterlight app at home over five days, adherence was 91.6% and only 2.7% of baseline recordings could not be processed.10

Several design lessons follow from the AD evidence:

Decide whether the question is detection or change. Features selected to separate MCI from normal cognition9 are not the composite built to track 18-month change,4 and each calls for its own validation.

Prespecify, then test out of sample. The speech composite score was derived in a training set from the Tauriel trial, confirmed in a held-out set and applied without modification to a second trial.4,7

Average across sessions, and vary the stimulus. Most acoustic features showed relatively low reliability from a single recording, but all reached good test–retest reliability (ICC 0.75 or above) with sufficient averaging, and describing a different picture each session reached that threshold in fewer sessions. For cross-sectional studies in particular, including several task trials and averaging across them is advisable.

Standardize the recording, including the environment and the distance between speaker and device.10

Where new studies could contribute

The questions these studies leave open translate directly into work that academic groups, with established cohorts and biomarker access, are well placed to run. The Bio-Hermes-002 analysis used each participant’s first assessment,9 so whether a combined CANTAB and speech battery tracks within-person change more sensitively than either alone is a natural next test. The authors of the Tauriel trial speech analysis identify comparison with healthy ageing as a priority,4 which repeated assessment in cognitively healthy older adults would address. The authors of the cortical-thickness and CSF modelling study name blood-based biomarkers as the next step,8 now practical with a plasma pTau217 test cleared in the US.1 Longitudinal work in cognitively unimpaired adults has also been proposed,10 for which prevention cohorts are well suited. The number, spacing and type of speech tasks are open methodological questions in their own right.

A second view

Blood tests will identify Alzheimer’s pathology in more people, and earlier. Whether memory is holding up, or language is beginning to change, remains a question for cognitive assessment, and the current evidence suggests that two complementary modalities answer it more completely than one. For studies already using CANTAB, a few minutes of recorded speech is a modest addition to the protocol.

Speech analysis for academic research

The speech studies above used Winterlight speech analysis, which will soon be available to academic research groups. Picture description, journaling, and paragraph reading and recall are administered through the Connect platform, transcribed by automatic speech recognition and returned as approximately 300 named acoustic, timing and linguistic features, with a feature dictionary defining each one. Because the features are named and interpretable, a study can prespecify a small set, as the Tauriel composite did, rather than reporting the best of several hundred.

If you are considering adding speech to an MCI or AD cohort that already uses CANTAB, or deciding which features to name in a protocol, we are glad to talk it through. Get in touch.

References

Roche. Roche receives FDA clearance for Elecsys® pTau217, advancing Alzheimer’s disease assessment across primary and specialty care. Press release. August 24, 2026. Accessed October 14, 2026. https://www.roche.com/investors/updates/inv-update-2026-08-24
Blackwell AD, Sahakian BJ, Vesey R et al. Dement Geriatr Cogn Disord. 2004;17:42–48.
Robin J, Xu M, Kaufman LD, Simpson W. Front Digit Health. 2021;3:749758.
Robin J, Xu M, Balagopalan A et al. Alzheimers Dement (Amst). 2023;15:e12445.
Cohen AS, Divers R, Calamia M et al. J Int Neuropsychol Soc. 2026 Jan;32:24–31.
Chipi E, Bellomo G, Salvadori N et al. J Prev Alzheimers Dis. 2023;10:523–529.
Spilka MJ, Xu M, Toth B et al. Robustness and generalizability of a speech-based digital biomarker derived from recordings of the Clinical Dementia Rating (CDR) interview. Poster presented at: Alzheimer’s Association International Conference; 2024; Philadelphia, PA. Abstract: doi:10.1002/alz.094733
Robin J, Xu M, Spilka M, Cormack F. Speech measures enhance the prediction of Alzheimer’s disease biomarkers. Poster presented at: Clinical Trials on Alzheimer’s Disease; December 1–4, 2025; San Diego, CA.
De Lillo M, Robin J, Xu M et al. Early identification of mild cognitive impairment using multi-modal digital assessments. Poster presented at: Alzheimer’s Association International Conference; July 12–15, 2026; London, UK.
van den Berg RL, de Boer C, Zwan MD et al. Alzheimers Res Ther. 2024;16:176.

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The post Adding speech to a CANTAB battery in Alzheimer’s disease/MCI research appeared first on Cambridge Cognition.

Advancing Alzheimer’s prevention: Are clinical trials ready for earlier interventions?

Owen Moulding — Mon, 26 Oct 2026 13:53:57 +0000

Advancing Alzheimer's prevention: Are clinical trials ready for earlier interventions?

Last week, the FDA announced the launch of the Neuroscience Advancement and Innovation Nexus (NAIN), a new cross-centre programme designed to advance the science, tools and regulatory approaches supporting medical product development for conditions affecting the brain and nervous system. Its first initiative, the Alzheimer’s Prevention Accelerator, will focus on treatments intended to prevent or delay Alzheimer’s-related cognitive decline.

This initiative addresses some of the most persistent challenges in Alzheimer’s drug development, with particular emphasis on identifying appropriate trial populations, developing stage-appropriate endpoints and establishing the evidence needed to demonstrate that treatments prevent or delay cognitive decline.

Advances in blood biomarkers are making it possible to identify Alzheimer’s pathology years before noticeable changes in memory or thinking. Earlier intervention could delay the onset of symptoms, but it poses a difficult question for clinical research: how can we demonstrate that treatment has prevented cognitive decline in someone who has yet to develop measurable impairment?

Addressing this challenge requires a better understanding of who is likely to progress, how cognition changes in the earliest disease stages and how those changes relate to meaningful treatment benefits.

Digital cognitive measurement plays an important role in this, particularly the potential for sensitive, longitudinal digital assessments to complement biomarkers in generating more detailed and nuanced evidence of disease progression and treatment efficacy.

Rethinking endpoints for prevention trials

Traditional Alzheimer’s trials have largely evaluated whether treatment slows deterioration in patients already experiencing cognitive impairment. In prevention trials, participants may perform within normal ranges for years, making it difficult to detect meaningful differences between treatment groups using conventional pen and paper cognitive scales.

Developing suitable endpoints therefore requires a more targeted approach to measuring cognitive change, tailored to the disease stage and intended treatment effect.

In very early symptomatic disease, sensitive measures of memory and learning may detect subtle changes that broader clinical scales miss. In cognitively unimpaired populations, researchers may need to evaluate the emergence of impairment or consider alternative endpoints.

Digital cognitive assessments could help by capturing more precise performance measures repeatedly over time, providing greater insight into individual cognitive domains and trajectories.

For example, CANTAB Paired Associates Learning (PAL) — a visual learning and recall task — tracked amyloid status in older adults without dementia where standard memory measures did not [1] and related to biomarkers measured a decade earlier. [2]

Integrating biomarkers and cognition

Biomarkers provide evidence of Alzheimer’s pathology and whether treatments are affecting their intended biological targets. Cognitive assessments provide insight into how these biological changes relate to memory, thinking and other cognitive functions, and can separate them by domain. For example, in patients with mild cognitive impairment, different CANTAB® subtests were associated with different pathological markers, with some tracking hippocampal volume and others tracking cerebrospinal fluid amyloid and tau.[3]

Combining these measures could help address two important challenges in prevention trials.

First, identifying appropriate participants. Individuals with similar biomarker profiles may experience very different rates of cognitive decline. Integrating cognitive performance with biological data could improve predictions of disease progression and help researchers select populations more likely to demonstrate measurable treatment effects.

Second, evaluating treatment efficacy. Longitudinal digital cognitive assessment alongside biomarkers could provide complementary evidence of whether changes in underlying pathology translate into preserved cognitive function.

The priority is to establish where combining these measurements improves clinical development decisions and strengthens the evidence of treatment benefit.

Building the scientific evidence

Cambridge Cognition is contributing to this research through studies examining the relationship between biomarkers and cognitive performance.

The AI-Mind study has investigated associations between CANTAB® cognitive measures and plasma p-tau217 in individuals with mild cognitive impairment, helping identify measures with promising sensitivity to Alzheimer’s pathology and longitudinal reliability.[4]

Meanwhile, the INTUITION Brain Health Study, conducted in collaboration with Biogen and Apple, demonstrated CANTAB®’s sensitivity to clinical status as well as the feasibility of remote cognitive monitoring at scale, enrolling more than 23,000 US participants.

These studies contribute to the scientific foundation for more sensitive, scalable cognitive measurement, while further research is needed to establish the suitability of specific measures as efficacy endpoints in prevention trials.

Advancing Alzheimer’s prevention

The FDA’s new initiative presents an important opportunity to advance the methods used to evaluate preventative treatments.

As Alzheimer’s research moves towards earlier intervention, developing sensitive, clinically meaningful endpoints and understanding how cognitive and biological measurements can be used together will be increasingly important.

The ability to detect Alzheimer’s pathology earlier has opened new possibilities for treatment. Now we need the scientific tools and evidence to demonstrate that earlier intervention can meaningfully change the course of cognitive decline.

References:

Pettigrew C, Soldan A, Brichko R, et al; BIOCARD Research Team. Computerized paired associate learning performance and imaging biomarkers in older adults without dementia. Brain Imaging Behav. 2022;16(2):921–929.
Soldan A, Pettigrew C, Moghekar A, Albert M; BIOCARD Research Team. Computerized cognitive tests are associated with biomarkers of Alzheimer’s disease in cognitively normal individuals 10 years prior. J Int Neuropsychol Soc. 2016;22(10):968–977.
Nathan PJ, Lim YY, Abbott R, et al; PharmaCog Consortium. Association between CSF biomarkers, hippocampal volume and cognitive function in patients with amnestic mild cognitive impairment (MCI). Neurobiol Aging. 2017;53:1–10.
Study – AI-Mind
Butler PM, Yang J, Brown R, Hobbs M, Becker A, Penalver-Andres J, Syz P, Muller S, Cosne G, Juraver A, Song HH, Saha-Chaudhuri P, Roggen D, Scotland A, Silveira N, Demircioglu G, Gabelle A, Hughes R, Erkkinen MG, Langbaum JB, Lingler JH, Price P, Quiroz YT, Sha SJ, Sliwinski M, Porsteinsson AP, Au R, Bianchi MT, Lenyoun H, Pham H, Patel M, Belachew S. Smartwatch- and smartphone-based remote assessment of brain health and detection of mild cognitive impairment. Nat Med. 2025 Mar;31(3):829-839. doi: 10.1038/s41591-024-03475-9. Epub 2025 Mar 4. PMID: 40038507; PMCID: PMC11922773.

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Cambridge Cognition joins Imperial College-led NHS study bringing earlier Alzheimer’s diagnosis into primary care

Owen Moulding — Tue, 06 Oct 2026 07:52:41 +0000

Cambridge Cognition joins Imperial College-led NHS study bringing earlier Alzheimer’s diagnosis into primary care

BEAD-PC study will now evaluate combining CANTAB® digital cognitive assessments with blood-based biomarkers in the diagnosis of Alzheimer’s disease in primary care

Cambridge, UK — Cambridge Cognition Holdings plc, (AIM: COG) the neuroscience technology company, announces its participation in BEAD-PC (Blood Biomarkers for Early and Accurate Diagnosis of Alzheimer’s Disease in Primary Care), a major UK study led by Imperial College London. The study now includes CANTAB® digital cognitive assessments alongside blood-based biomarkers.

Initiated in June 2026 and running for 15 months, BEAD-PC aims to recruit 500 participants across North West London with subjective memory complaints or symptoms of early cognitive decline. Participating GPs refer eligible patients to dedicated Primary Care Assessment Centres for digital cognitive assessment and blood sampling.

By combining objective cognitive assessment with biological markers of Alzheimer’s disease, the study aims to demonstrate how this approach can support earlier, more accurate diagnosis and be integrated into routine care at scale.

Building a pathway for earlier diagnosis

Timely and accurate diagnosis remains a major challenge in dementia care. Nearly one million people in the UK live with dementia, yet around one third of people with the condition in England remain undiagnosed, and people live with symptoms for an average of 3.5 years before receiving a diagnosis.¹

Confirming Alzheimer’s disease pathology has traditionally relied on specialist investigations such as PET imaging or cerebrospinal fluid analysis. Advances in blood-based biomarkers are making this information more accessible, while digital cognitive assessment provides an objective measure of changes in memory and thinking to reflect meaningful aspects of health and functioning for the patient.

BEAD-PC will generate real-world evidence, in the NHS, as to how blood-based biomarkers, digital cognitive assessments and specialist services can be incorporated into future diagnostic pathways.

The study forms part of the Davos Alzheimer’s Collaborative (DAC) Healthcare System Preparedness Accurate Diagnosis programme, a global initiative examining how emerging Alzheimer’s diagnostic technologies can be integrated into real-world healthcare systems. Imperial College London and Imperial College Healthcare NHS Trust, together with the North West London Primary Care Federations, are conducting the programme’s activities in the UK, while other programmes are being conducted in the United States, Germany, the Netherlands and Japan.

BEAD-PC is supported by the NIHR Imperial Biomedical Research Centre.

Rob Baker, CEO at Cambridge Cognition, said:

“While blood-based biomarkers give clinicians new ways to identify the biological signs of Alzheimer’s disease – digital cognitive assessments show changes to cognitive function that matter to patients, their families and their carers in everyday life.

BEAD-PC brings these complementary measures together in primary care, enabling earlier and more accurate diagnosis. This has the potential to shorten the route to appropriate treatment, support improved clinical decision-making, and enable healthcare systems respond more effectively.”

Professor Lefkos Middleton, Professor of Neurology at Imperial College London, said:

“New diagnostic tools will only make a meaningful difference if they can be integrated into a care pathway in a way that works for patients, clinicians and the wider health system. BEAD-PC is focused on the practical challenge of understanding how blood biomarkers and cognitive assessment can be implemented, at scale, and potentially transform the early diagnostic pathway of age-related cognitive disorders.

By evaluating this model in routine NHS primary care, we can build the real-world evidence needed to inform future diagnostic pathways, reduce unnecessary delays and help ensure that advances in Alzheimer’s detection translate into better access to the right care at the right time.”

About Cambridge Cognition

Cambridge Cognition is the neuroscience technology company making brain health measurable at scale.

Its digital cognitive and voice-based assessments along with clinical trial technologies support scientific discovery, accelerate drug development and improve patient care. Built on more than 40 years of cognitive science, CANTAB provides sensitive, objective assessment of cognitive function and has been used extensively in clinical trials and academic research worldwide.

Cambridge Cognition provides technology and scientific expertise across clinical studies, academic research, healthcare and consumer health and wellness.

For further information, visit: www.cambridgecognition.com

About Imperial College London

Imperial College London is a world-leading university for science, technology, engineering, medicine and business (STEMB), where scientific imagination leads to world-changing impact.

We were founded in 1907 with a mission ‘To be useful’, but we know that before anyone can usefully change something, they first need to understand it. That’s what we do.

We use science to try to understand more of the universe and improve the lives of more people in it. Across our London campuses, and throughout our international network, we ask bigger questions and so we shape the future. www.imperial.ac.uk

About the Davos Alzheimer’s Collaborative (DAC)

The Davos Alzheimer’s Collaborative (DAC) is a global partnership of organisations mobilising the world against Alzheimer’s disease. Advised by leaders in science, finance and healthcare, DAC works with international organisations, governments and the private sector to accelerate innovation and deliver solutions to patients around the globe.

DAC’s Healthcare System Preparedness programme (DAC-SP) aims to transform how healthcare systems worldwide detect, diagnose, treat and care for people with, or at risk of, Alzheimer’s disease, implementing and evaluating programmes that increase rates of cognitive screening, early detection and accurate diagnosis. www.davosalzheimerscollaborative.org

References:

¹ Alzheimer’s Society. Unlocking the Door to Diagnosis. 2026.

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The post Cambridge Cognition joins Imperial College-led NHS study bringing earlier Alzheimer’s diagnosis into primary care appeared first on Cambridge Cognition.

Measuring speech in schizophrenia spectrum disorders

Francesca Hazel — Thu, 01 Oct 2026 11:39:37 +0000

Measuring speech in schizophrenia spectrum disorders

A practical guide to speech features, elicitation tasks and study design

Speech is an unusual clinical signal. It is produced naturally, requires no instrumentation beyond a microphone, can be collected in a clinic or a participant’s home, and carries information at three levels at once: the acoustic properties of the voice, the timing of its delivery, and the linguistic structure and meaning of what is said. A few minutes of recorded speech yields hundreds of quantifiable variables across those three levels, none of which requires the participant to do anything unfamiliar.

For research in schizophrenia spectrum disorders (SSDs), that is particularly relevant for the assessment of negative symptoms. Alogia and blunted affect are already inferred from how much a patient says, at what rate, and with what prosodic variation; the rating scales in routine use formalize those judgements rather than replacing the observations underneath them. But those scales require extensive rater training, are ordinarily administered in clinic, are susceptible to rater and expectancy bias, and may not register change falling between severity anchors. Negative symptoms predict functional outcome and quality of life, and no current treatment produces sustained improvement in them — so a measure that is objective, repeatable and collectable remotely has obvious value alongside clinician ratings.

What gets measured

Automated pipelines extract features at three levels, each with implications for study design.

Acoustic features describe the voice signal: mean fundamental frequency and its variance, characterizing pitch and prosodic range; intensity, or perceived loudness; measures of voice quality like jitter and shimmer, which quantify cycle-to-cycle perturbation in frequency and amplitude, and harmonic-to-noise ratio.

Timing features describe the rhythm of delivery: speech rate in words per minute, articulation rate in syllables per second, mean pause duration, counts of silent and filled pauses, and the proportion of a recording containing speech rather than silence.

Linguistic features describe what was said: lexical diversity and word frequency, the distribution of parts of speech, syntactic complexity from parse-tree depth, semantic coherence between successive utterances calculated from word embeddings, sentiment scored against published affective norms, and speech-graph properties representing how ideas connect across a narrative.

A pipeline of this kind returns several hundred variables. Which of them belong in a protocol?

How speech is elicited

Speech is collected through short structured tasks rather than recorded conversation, which keeps measurement comparable across participants, sites and visits.

Several types of tasks have commonly been used in research studies. Picture description asks the participant to describe a scene presented to them, with a follow-up prompt for additional detail. It takes approximately two minutes and returns measures of fluency, lexical richness, syntactic structure and semantic coherence, together with task-performance scoring against the content units present in the image. Open-ended journaling uses a narrative prompt, takes approximately one minute, adds prosodic and sentiment measures to the same linguistic set, and allows for psychologically relevant prompts that can elicit more affective content. Paragraph reading and recall has the participant read a standardized passage aloud and recall it after a delay, roughly a minute each; because the words are supplied, reading isolates motor speech and fluency from language production, while recall adds a measure of episodic memory.

Recordings are transcribed by automatic speech recognition (ASR), and acoustic, timing and linguistic features are generated from the audio and transcript together.

Lessons from the literature

The evidence base is now substantial enough to draw practical guidance from. A systematic review published in June pooled diagnostic classification accuracy across 20 schizophrenia studies (n = 2,033) at 84.0% (95% CI 81.1–86.6), with moderate heterogeneity (I² = 54.7%).1 The question is no longer whether speech carries signal, but how to design a study that measures it well. A few lessons:

Choose the right features for the research question. Some features separate patients from controls, some vary with severity within a diagnosis. Decide which question you are asking at the start.

Match the number of features to your sample size. For smaller study populations, reporting the best of several hundred can be a weaker position than naming a handful in advance and reporting them whatever they show. Simpler models tended to outperform deep learning at smaller population scales, and more data is not automatically better data: single-modality models often outperformed multimodal ones. Larger participant samples can support more features, and it may be advantageous to include an unfiltered large set of features for a data-driven analysis or analysis using data-reduction approaches.

Consider establishing reliability before validity. Reliability constrains the magnitude of association a study can detect, but says nothing about whether an association exists. Both need separate evidence, ideally in that order.

The use case of interest will shape the required properties of speech measures — match the standard to your purpose. Acoustic features are consistently the most stable across repeated administration, timing features less so, linguistic features the most variable — a pattern now shown in independent samples using different pipelines.2,3 Diagnostic separation, trait-like characterization or stratification, and within-person longitudinal monitoring set different psychometric bars.

Consider aggregating rather than testing individually. Composite indices and latent factors built across correlated semantic features can be more stable than their constituent features.3,4

Use more than one stimulus per visit where you can. Averaging across trials gives a better estimate, and eliciting more speech tends to improve reliability. For longitudinal designs, if stimuli are not well equated, presenting one repeating and one novel stimulus can balance practice effects against stimulus effects. Other approaches include cycling through multiple novel stimuli at each visit.

Two studies, two answers

On the topic of feature selection, two papers published this summer that pose different questions illustrate the point directly.

Spilka and colleagues asked which voice features track negative symptom severity within schizophrenia spectrum disorders.2 Sixty-two inpatients completed journaling and picture description tasks at hospital admission and again at discharge. Thirty-eight features were specified in advance based on prior research, and criteria applied in sequence: adequate test-retest reliability, significant correlation with Scale for the Assessment of Negative Symptoms (SANS) total score, and replication of both at the second visit.

Four picture-description features (mean pause duration, speech proportion, speech rate and unfilled pauses) met every criterion and three replicated from the journaling task. None correlated with positive or overall symptom severity, supporting their specificity, and none was associated with antipsychotic dose or parkinsonian symptoms. Speech rate was the strongest candidate, also showing convergent validity with an independent negative symptom measure across both tasks and visits. No acoustic feature correlated with negative symptom severity.

Tang and colleagues asked whether a brief speech sample can identify individuals needing further psychiatric assessment.5 Their ACES study analysed 266 participants from inpatient and outpatient services. The design is transdiagnostic rather than SSD-specific, so the results describe psychiatric caseness broadly in a heterogenous clinical population. Separating healthy volunteers from participants with any psychiatric disorder reached an F1 of 0.865, with 88% sensitivity and 68% specificity; speech from picture description alone reached F1 of 0.830. A more nuanced second split, between serious mental illness (defined as bipolar disorder or any psychotic disorder, including SSD and major depressive disorder with psychosis) and other psychiatric disorders, reached 0.626 — falling short, the authors say, of the accuracy required for clinical implementation but potentially useful for triage purposes. The most influential features for the first split were acoustic: instability (shimmer) and reduced pitch variance. Split 2 was influenced by articulation rate and filled pauses.

The same Winterlight extraction pipeline, overlapping investigators and comparable tasks produced largely non-overlapping feature sets. Acoustic measures allowed for the evaluation of psychiatric case-control differences but weren’t as helpful in resolving the severity of mental illness; timing measures were sensitive to the negative symptoms of schizophrenia. This divergence is not anomalous — it demonstrates the richness of speech as a clinical signal, with the ability to convey information about various aspects of psychopathology in a variety of contexts of use.

What this makes practical

The four markers identified by Spilka and colleagues need little infrastructure. Speech proportion and mean pause duration are computed from the audio waveform alone and need no transcript; speech rate and unfilled pauses depend on whether a word was spoken rather than which word it was. None requires analysis of language content, which lowers transcription burden and reduces the privacy exposure of storing patient language.

The authors identify three potential applications, pending further validation: screening or enrichment in trials targeting negative symptoms, remote monitoring between scheduled visits and a quantitative endpoint potentially more sensitive to small changes than a scale with coarse severity anchors. Longitudinal work in the same programme has shown a speech and language component tracking change in thought disorder and negative symptoms across repeated timepoints.6

The future directions that emerge from these studies are mostly suited to academic groups: independent cross-site replication, cohorts with healthy comparison groups and normative data, designs long enough to test sensitivity to change rather than stability over days and fairness auditing reported as an outcome.

Speech analysis for academic research

The studies above used Winterlight speech analysis, which will soon be available to academic research groups. Picture description, journaling, and paragraph reading and recall are administered through the Connect platform, recorded, transcribed by ASR, and returned as named acoustic, timing and linguistic features with a feature dictionary defining each one. The features are interpretable rather than opaque model outputs, which is what allows a study to examine the face validity of its predictors and prespecify a small set rather than reporting the best of several hundred. Multiple stimuli are available for each task, supporting the longitudinal with repeat testing study designs described above.

If you are considering adding speech assessment to a psychosis cohort, or working out which features to name in a protocol, we are glad to talk it through — just get in touch.

References

Parsapoor M, et al. Supervised machine learning classifiers for schizophrenia and bipolar disorder using speech and language: a systematic review, meta-analysis, and novel quality assessment framework. Artif Intell Rev. 2026. doi:10.1007/s10462-026-11587-6
Spilka MJ, et al. Identification of robust speech-based markers of negative symptom severity in schizophrenia spectrum disorders. Schizophrenia. 2026 (in press). doi:10.1038/s41537-026-00788-1
Çokal D, et al. What is the retest reliability of computationally extractable speech and language markers? Comput Speech Lang. 2026;100:101981.
Palominos C, et al. A single composite index of semantic behavior tracks symptoms of psychosis over time. Schizophr Res. 2025;279:116–127.
Tang SX, et al. ACES: ascertaining diagnosis classification with elicited speech in individuals with heterogeneous, comorbid psychiatric disorders. Psychiatry Res. 2026;365:117389. Tang SX, et al. Automated speech and language markers of longitudinal changes in psychosis symptoms. NPP—Digit Psychiatry Neurosci. 2025;3:13.

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First new CANTAB® product features developed & launched from the landmark INTUITION project

Francesca Hazel — Tue, 22 Sep 2026 15:15:32 +0000

First new CANTAB® product features developed & launched from the landmark INTUITION project

Cambridge Cognition (AIM: COG), the neuroscience technology company, announces two new product features for its CANTAB digital cognitive assessments derived from analysis of data from the INTUITION project.

Application of Expanded Normative Dataset – Increased Sensitivity and Accuracy of CANTAB®

The first development is an expanded normative dataset derived from Project INTUITION to support improved sensitivity and accuracy over earlier releases. Normative data provides the reference information against which an individual’s cognitive performance is measured. The comparison matches an individual to their appropriate comparator group within the dataset taking into account that person’s age, biological sex and level of education. These updates are being deployed across the digital touchscreen cognitive assessments which are core to CANTAB Pathway and used in both clinical studies and academic research.

Automatic detection of inattention

The unique scale and structure of the Intuition dataset has enabled Cambridge Cognition to develop a proprietary machine learning algorithm to distinguish when a user has been distracted while taking a task. This functionality has been deployed into the Company’s CANTAB One solution. When the algorithm detects that an individual has been distracted, the assessment will be flagged and can prompt the individual to retake the task. This feature is intended to reduce false positive detection of cognitive impairment by automatically screening out inattention scores, improving accuracy. It is expected that this feature will be rolled out into live field trials in the coming weeks. Following these trials, the Company intends to deploy this improvement across all uses of CANTAB One.

INTUITION Brain Health Study

The INTUITION Brain Health Study commenced in September 2021, and after 18-months on 13 March 2023, achieved its overall planned enrolment goal of 23,000 adults across the United States.

In total the study collected cognitive assessment data from these 23,000 participants completing 2-4 tasks at each timepoint, generating more than 3.2 million sessions. Consequently, the analysis is powered by over 7 million total completed tasks. The study used iPhone and Apple Watch technology to remotely collect cognitive and behavioural data over time. Cambridge Cognition’s CANTAB® assessments provided all cognitive data assessments and were central to the study. The tasks measured memory, attention and executive function across all subjects without clinical supervision.

The initial findings from project INTUITION were published on 4 March 2025 in Nature Medicine: (https://pmc.ncbi.nlm.nih.gov/articles/PMC11922773). The study is recorded at Clinicaltrials.gov at: https://clinicaltrials.gov/study/NCT05058950. Owing to its size, the Company believes this to be one of the world’s leading datasets in the field.

Application of improvements and future developments

Both new developments announced can be applied to CANTAB generally for use in all four segments: academic research, clinical studies, healthcare and consumer health and wellness.

Cambridge Cognition has identified important applications, using outputs from the INTUITION project, in clinical trial recruitment to assist sponsors seeking to identify candidates remotely who have a cognitive function profile matching the selection criteria for their clinical trials.

The analysis of the dataset continues, and Cambridge Cognition expects to release multiple further product features and capabilities. The dataset’s applications extend well beyond its observational study origins, providing a foundation for expansion into new therapeutic areas across all market segments.

Advances which are currently in development include:

new scoring methods that increase the statistical power of existing tests while remaining fully backward compatible with previous studies

shorter adaptive test versions that reduce completion time

richer metrics for tracking how cognition changes over time

Further findings from this work were presented at ISCTM Conference (isctm.org) on 16th September 2026 in Philadelphia, PA, USA.

Rob Baker, Chief Executive Officer of Cambridge Cognition, said:

“What we’ve built from the INTUITION study is a significant proprietary dataset that no competitor can easily replicate, and which gets more valuable with every analysis we run.

We are using the data to make our tests more powerful, faster to complete, and better at tracking how cognition changes over time — all while ensuring existing clients benefit immediately without changing their protocols. None of this would be possible without data at this scale.

Today’s announcements are the first new product releases from this programme. We expect more to follow as we continue to unlock new capabilities from this unique asset. These new developments demonstrate the significant value that can be unlocked through the major multi-year collaborations which we engage in.”

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C2N Diagnostics Expands Global Partnerships in United Kingdom on World Alzheimer’s Day, Joins Cambridge Cognition and The Alzheimer’s Trust to Improve Alzheimer’s Disease Diagnosis

Francesca Hazel — Mon, 21 Sep 2026 09:32:36 +0000

C2N Diagnostics Expands Global Partnerships in United Kingdom on World Alzheimer’s Day, Joins Cambridge Cognition and The Alzheimer's Trust to Improve Alzheimer's Disease Diagnosis

Collaboration integrates cognitive assessment, proprietary blood test, national phlebotomy and MRI infrastructure to accelerate patient diagnosis and care pathways throughout the UK.

World Alzheimer's Day - September 21st 2026

C2N Diagnostics, LLC (“C2N”), a pioneer in advanced diagnostic testing for brain health, and Cambridge Cognition Holdings plc, (AIM: COG) the neuroscience technology company, announce on World Alzheimer’s Day a partnership with The Alzheimer’s Trust, a newly formed subsidiary of The Cancer Screening Trust, to address the urgent and growing burden of Alzheimer’s disease and related dementias in the United Kingdom (UK).

The collaboration creates an integrated, scalable pathway for earlier and more accurate diagnosis of Alzheimer’s disease and related dementias in the UK and includes:

C2N’s UK Medicines and Healthcare products Regulatory Agency-registered PrecivityAD2® test, which helps health care professionals identify patients with amyloid pathology associated with Alzheimer’s disease;
CANTAB Pathway, Cambridge Cognition’s validated digital touchscreen cognitive assessment platform; and
The Alzheimer’s Trust’s national phlebotomy and MRI imaging infrastructure.

UK-based health care professionals can now order the PrecivityAD2® test and the CANTAB Pathwaythrough The Alzheimer’s Trust. This combined effort aims to aid in the assessment of individuals presenting with cognitive impairment who are being evaluated for Alzheimer’s disease (AD) and other causes of cognitive decline.

Health care professionals can contact hello@thealzheimerstrust.co.uk or call UK +44 (0)1935 712430 for ordering information.

How PrecivityAD2® Blood Test and CANTAB Pathway Can Increase Diagnostic Accuracy

The PrecivityAD2® test uses state-of-the-art high resolution mass spectrometry and measures the ratio of amyloid beta protein isoforms Aβ42 and Aβ40, the Aβ42/Aβ40 ratio and the percentage of tau protein that is phosphorylated at amino acid 217 and not phosphorylated at amino acid 217 or %p-tau217. The Aβ42/Aβ40 ratio and %p-tau217 are combined into a proprietary statistical algorithm to calculate the Amyloid Probability Score 2 (APS2), which provides the likelihood of amyloid plaques in the brain, a hallmark of Alzheimer’s disease.

CANTAB Pathway is Cambridge Cognition’s digital cognitive assessment platform, designed for use in a clinical setting, offering escalating tiers of tasks to provide increasingly greater insight about a patient’s cognition.

Data¹showed that cognitive performance assessed using CANTAB Pathway is sensitive to a blood biomarker associated with brain amyloid pathology. Other analyses² showed that CANTAB Pathway discriminated cognitive impairment by baseline biomarker status and tracked cognitive trajectory over two years in those patients above the upper thresholds of circulating blood biomarkers known to be associated with brain amyloid pathology.

This evidence demonstrated that CANTAB® digital cognitive assessments and amyloid blood biomarker testing capture complementary but related disease processes and, according to company executives, together offer a more complete picture for earlier, more confident diagnoses.

Similarly, a study³ published in Nature Medicine assessed the combination of a self-administered digital cognitive test plus C2N’s PrecivityAD2® algorithm across 19 general practitioner (GP) clinics in Sweden. The study found that integrating a digital cognitive test plus the blood biomarker test could detect clinical, biomarker-verified Alzheimer’s disease with an accuracy of 90% — significantly better than standard-of-care GP accuracy of 70%.

Health care professionals state that early and accurate diagnosis is clinically meaningful. Studies^4,5,6show that lifestyle interventions improved memory, thinking and overall cognitive function in older adults at risk of dementia.

UK Dementia Crisis: A Strained System

Dementia is the United Kingdom’s leading cause of death7, claiming more than 76,000 lives each year and affecting an estimated 982,000 people across the UK — a number projected to exceed 1 million and continue rising with an ageing population⁸.

Despite its scale, officials believe the dementia diagnostic pathway remains a key challenge within the National Health Service (NHS), with clinically meaningful potential consequences.

Recent findings published by Alzheimer’s Society revealed that people in the UK wait on average 3.5 years from first symptoms to diagnosis, with almost six months spent after a GP referral to a memory clinic, and nearly 75% of GPs acknowledge long waits for diagnosis⁹.

These delays to diagnosis have potential clinical consequences, noting amyloid-targeting treatments for Alzheimer’s disease, approved by UK’s MHRA, appear to be most effective when treatment begins in the earliest stages of disease^10,11.

C2N Achieves Global Regulatory Milestones for PrecivityAD2®

In 2025, C2N obtained medical device registration from the UK’s MHRA for the PrecivityAD2®

test — the first regulatory approval of the test as an in vitro diagnostic anywhere in the world. More recently, PrecivityAD2® received FDA clearance in the United States as an aid to diagnosis of Alzheimer’s disease.

These milestones build on a landmark prospective study published in the Journal of the American Medical Association (JAMA)¹² that enrolled over 1,200 patients in both the primary care and specialty care settings and showed 92% Negative Predictive Value (NPV) and 91% Positive Predictive Value (PPV) for the PrecivityAD2® clinically validated algorithm using a pre-defined, single cutoff, while a two-cutoff approach yielded 95% NPV & PPV, respectively. This performance exceeds expert consensus recommendations for an Alzheimer’s disease blood biomarker test to serve as a substitute for CSF testing or PET imaging alternatives¹³.

Dr. Joel Braunstein, CEO, C2N Diagnostics, says, “C2N is excited to play an important role in this partnership by helping to address the dementia diagnosis crisis in the UK and believes this collaboration could be a model in other parts of the world. We especially appreciate and admire what The Cancer Screening Trust has accomplished in the field of oncology and look forward to similar success with Alzheimer’s disease. We have found Cambridge Cognition to be a highly collaborative and trusted partner in helping to educate stakeholders about novel diagnostic tools available to physicians and patients in the field of Alzheimer’s disease.

“We believe that adding PrecivityAD2® into an integrated diagnostic pathway through The Alzheimer’s Trust creates a unique opportunity for a broad, long-term solution throughout the UK.”

CANTAB Pathway Complements PrecivityAD2® Test

CANTAB Pathway is Cambridge Cognition’s digital cognitive assessment platform, designed for use in a clinical setting. The three escalating tiers of tasks are:

CANTAB One provides a rapid cognitive screening to identify if a problem exists;
CANTAB Insight delivers deeper, multi-domain profiling to assist the physician in their diagnostic pathway; and
CANTAB Plus is intended for specialists using disease-specific assessments, in this case for mild cognitive impairment, Alzheimer’s disease and the other dementias, to give a detailed and thorough picture of cognitive sub-domain specific profiling to assist in determining if disease is present and what form this might take.

CANTAB Pathway has already been deployed commercially across multiple settings, including an agreement with a major European private healthcare group. Cambridge Cognition also has a research collaboration with ŌURA, “the world’s leading smart ring.” The company says these deployments demonstrate the scalability of CANTAB Pathway and position Cambridge Cognition to capture demand across both institutional healthcare and consumer wellness markets.

Cambridge Cognition’s digital touchscreen and voice-based cognitive assessments are supported by over 3,700 peer-reviewed publications. The company says multiple papers demonstrate the sensitivity in detecting early signs of mild cognitive impairment, when deployed both in clinic and at home.

A scoping review, published in Alzheimer’s & Dementia1⁴ evaluated 79 different self-administered digital cognitive assessments for clinical use in Alzheimer’s disease from multiple providers. This study identified CANTAB® as one of only three tools fully meeting predefined framework criteria for real-world deployment.

Rob Baker, CEO, Cambridge Cognition, says, “The dementia diagnostic challenge in the UK demands bold, collaborative action. By uniting C2N’s pioneering blood biomarker technology, Cambridge Cognition’s clinically validated digital assessments and The Alzheimer’s Trust’s commitment to patient-centred care, this partnership offers a new model for how the healthcare system can meet the scale of the crisis.”

Dan Hogarty, Director, The Alzheimer’s Trust, says, “This collaboration with C2N and Cambridge Cognition enables us to offer the best tests available to those in need and to address the issue with sensitivity and integrity. All three parties are in this sector for the long term and are equipped to handle the enormous challenges.”

Frank Hogarty, CEO, The Alzheimer’s Trust and The Cancer Screening Trust, says, “The Alzheimer’s Trust can support physician or patient referrals from the whole of the UK, and through our in-house clinical team, either via video or phone calls, support patients through their diagnosis and care pathways according to test results. This personalized, patient-centric approach is a best practice that we have optimized through The Cancer Screening Trust over the last five years.”

About Cambridge Cognition

Cambridge Cognition, the neuroscience technology company, designs, develops and delivers digital cognitive assessments that drive scientific discovery, accelerate drug development and improve patient care.

The company is built on rich, curated data and deep technical expertise. We are building a strong global brand with scalable technology that will support the rising world demand for diagnosing and treating brain health. The Company creates shareholder value through organic sales growth, strategic partnerships, joint ventures, and spinouts.

The Company operates in four market sectors:

Clinical Studies for new pharmaceuticals;
Academic Research for scientists to understand CNS disorders;
Healthcare to provide physicians with cognitive assessments to allow them to diagnose and treat patients; and
Consumer Health & Wellness to provide individuals access to accurate, reliable, and meaningful data to assess their cognitive health.

Find out more.

About C2N Diagnostics

C2N is a leading specialty diagnostics company with a vision to bring Clarity Through Innovation®. C2N strives to provide exceptional clinical laboratory services and advanced diagnostic solutions in the field of brain health. C2N’s high-resolution mass spectrometry-based biomarker services and products are used for: clinical decision-making to improve patient care, including diagnosis and treatment monitoring; maximizing the quality and efficiency of clinical trials that test novel treatments for neurodegeneration; and providing innovative tools to help healthcare researchers better understand novel mechanisms of disease, identify new treatment targets, and conduct important epidemiologic studies to improve global public health. C2N assays have been used in over 200 Alzheimer’s disease and other research studies throughout the U.S. and the world. This includes landmark treatment and prevention trials involving disease-modifying therapies (DMTs) that are changing the trajectory of Alzheimer’s disease. Over 90,000 Precivity®-related biomarker measures have been reported through peer-reviewed publications, with many more manuscripts currently under review.

The company acknowledges generous support from National Institute on Aging, GHR Foundation, Alzheimer’s Drug Discovery Foundation, BrightFocus Foundation, Alzheimer’s Association and The Michael J. Fox Foundation. For more information visit http://www.c2n.com.

About The Alzheimer’s Trust

The Alzheimer’s Trust is a not-for-profit organisation set up to offer the best advice and tests to the UK market. Our mission is to combine the leading diagnostic and cognitive assessment tests with our excellent customer service to ensure that clients benefit from the latest worldwide diagnostic technologies in Alzheimer’s disease. For information and advice please email hello@thealzheimerstrust.co.uk

References:

¹Kaula, A.J., Stang, N.K., Taptiklis, N., Hatlestad-Hall, C., Haraldsen, I. and Cormack, F.K. (2025), Reliability and Sensitivity of Cognitive Outcome Measures to Plasma p -tau217 in Mild Cognitive Impairment in the AI-Mind study. Alzheimer’s Dement., 21: e108841. https://doi.org/10.1002/alz70861_108841

²Stang, Kaula, Taptiklis, Cormack et al., AAIC 2026; https://pages.cambridgecognition.com/cantab-mci-ptau217ai-mind

³Tideman, P., et al. Primary care detection of Alzheimer’s disease using a self-administered digital cognitive test and blood biomarkers. Nat Med 31, 4131–4139 (2025). https://doi.org/10.1038/s41591-025-03965-4

⁴Baker LD, Espeland MA, Whitmer RA, et al. Structured vs Self-Guided Multidomain Lifestyle Interventions for Global Cognitive Function: The US POINTER Randomized Clinical Trial. JAMA. 2025;334(8):681–691. doi:10.1001/jama.2025.12923

⁵Crivelli L, Suemoto C, Sosa A et al. Multidomain lifestyle intervention for the prevention of cognitive decline in at-risk older adults in Latin America (LatAm-FINGERS): a single-blind, multicentre, randomised controlled trial. The Lancet, 2026; 408, 417-42

⁶Ngandu T, Lehtisalo J, Solomon A et al. A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. The Lancet, 2015; 385, 2255-2263

⁷Alzheimer’s Research UK, Dementia Is Still UK’s Biggest Killer, December 2025

⁸Alzheimer’s Society, How many people have dementia in the UK?, 2024

⁹Reports expose a dementia care system failing patients at every stage | Alzheimer’s Society , May 2026

¹⁰van Dyck, C.H., Li, D., Kanekiyo, M., Dhadda, S., Hersch, S., Gee, M., Irizarry, M.C. and Kramer, L.D. (2025), The Lecanemab Clarity AD Open-Label Extension in Early Alzheimer’s Disease: Initial Findings From the 48-Month Analysis. Alzheimer’s Dement., 21: e108905. https://doi.org/10.1002/alz70861_108905

¹¹ Sajeendran et al., “Donanemab in Early Alzheimer’s Disease: Greater Benefit in Lower Tau Burden (P2-12.011).” Neurology. 2026;106(11 Supplement 1):868. https://doi.org/10.1212/WNL.0000000000213161

¹² Palmqvist S, Tideman P, Mattsson-Carlgren N, et al. Blood Biomarkers to Detect Alzheimer Disease in Primary Care and Secondary Care. JAMA. 2024;332(15):1245–1257. doi:10.1001/jama.2024.13855

¹³ Schindler, S.E., Galasko, D., Pereira, A.C. et al. Acceptable performance of blood biomarker tests of amyloid pathology — recommendations from the Global CEO Initiative on Alzheimer’s Disease. Nat Rev Neurol 20, 426–439 (2024). https://doi.org/10.1038/s41582-024-00977-5

¹⁴Hampel H, Nakamura Y, Bell J, et al. Evaluating digital cognitive tests for clinical use in Alzheimer’s disease: A novel framework and scoping review. Alzheimer’s Dement. 2026; 22:e71559. https://doi.org/10.1002/alz.71559

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Integrating Blood-Based Biomarkers & Digital Cognitive Assessments to Accelerate Brain Health Research

Francesca Hazel — Tue, 25 Nov 2025 17:25:05 +0000

The Convergence: Integrating Blood Biomarker Tests and Digital Cognition to Accelerate Alzheimer’s Research

The paradigm for diagnosing and monitoring Alzheimer’s disease (AD) is shifting from relying on clinical symptoms to incorporating definitive biological evidence of amyloid and tau proteinopathy. As discussed in our recent joint webinar with C2N Diagnostics and the AI-Mind project, combining blood biomarker (BBM) tests and digital cognitive assessments (DCAs) represents a fundamental, integrated shift in disease research that enables faster detection, more precise monitoring, and potentially more effective therapeutic interventions. This combination of cognitive and physiological assessments is crucial for advancing brain health research.

Listen to the Full Webinar

Cambridge Cognition · The Convergence: Integrating Blood Biomarker Tests and Digital Cognition to Accelerate Alzheimer’s Research

The Imperative for Biomarker-Driven Trials

While the reliance on clinical opinion and the high cost and invasiveness of more definitive pathophysiological evidence (via PET scans or CSF analysis from lumbar puncture) have historically defined AD diagnosis, this landscape is rapidly changing.

As Dr. Braunstein noted, dementia is a clinical phenotype, not the underlying disease. In fact, up to 39% of early dementia due to AD cases are misdiagnosed in primary care settings in the absence of biomarker data.

This diagnostic inconsistency drives a need for molecular characterization to ensure proper management, including treatment.

BBM tests as Confirmatory Tools
Blood tests, such as the PrecivityAD2 test can measure analytes like Aβ42/40 and p-tau217/np-tau217 (known as %p-tau217), which can provide high diagnostic accuracy (over 90%) in confirming presence of brain amyloid pathology. These offer a less invasive and more accessible alternatives to CSF & PET for early diagnosis and monitoring.
Targeting the Treatment Window
This is critical because effective disease-modifying therapies have been approved by various global regulatory bodies, but their success depends on identifying patients early, while they are still within the appropriate “treatment window”. If diagnosis is delayed by months, or even years (up to two years in some systems), patients can miss the opportunity for intervention.

DCAs: Scaling Precision in Functional Assessment

While BBM tests can excel at confirming presence of AD pathology, clinical trials require objective, longitudinal measures of functional change – the impact of the disease. This is where DCAs provide essential value, tackling the systematic shortage of specialists and the bottleneck in memory care.

Dr. Cormack highlighted that to address the millions of people concerned about memory, assessment needs to be deployed at scale.

Feasibility and Compliance
Data shows that remote, digital cognitive assessments are not only scalable and accessible, but maintain high compliance and engagement over prolonged periods, even in patients with mild cognitive impairment (MCI) or mild AD.
Sensitivity to Biology
Modern DCAs are designed to be sensitive not just to the clinical phenotype, but also to the underlying biology. Certain tasks are able to selectively activate the hippocampus, an area particularly impaired in MCI and AD, and are statistically sensitive to AD-related biomarkers like hippocampal volume, CSF amyloid, and tau. Furthermore, the evidence shows that DCAs are able to predict functional decline over 24 months.

A Blueprint for Integration

The AI Mind project provides a powerful, real-world example of this convergence in a longitudinal setting. As Dr. Hatlestad-Hall described, the study combines high-density EEG (neurophysiology), CANTAB® DCAs (behaviour/function), and BBMs (pathology) across multiple European cohorts.

Preliminary insights from this study, based on unpublished data, reveal the complex, but measurable, relationships essential for clinical trial design:

Plasma p-tau217 levels were already dependent on APOE ε4 status at the baseline MCI stage.
Performance on a classic verbal memory test was negatively correlated with plasma p-tau217 levels.
Higher p-tau217 load at baseline appeared related to time-dependent cognitive decline, with higher quartile groups showing an average drop in performance after their second visit on tests like Pattern Recognition Memory (PRM).

This combination of tools offers a path to investigate functional trajectories in relation to biomarker evolution, providing the objective data drug developers need to manage trial risk and confirm treatment efficacy.

Precision Medicine for AD: Unifying Pathology and Function

The unified approach of precise pathology confirmation (BBM tests) and objective, scalable functional measurement (DCAs) positions CNS drug developers to transition AD care from a reactive model to a preventive one. This precision is the key to optimizing drug development, ensuring trial cohorts are appropriately enriched, and validating efficacy endpoints, ultimately helping to accelerate the delivery of life-changing treatments.

See it in Action

Speak to us to find out how BBMs and DCAs can support your research. Complete the form below and one of our team will be in touch with you shortly!

About C2N Diagnostics
C2N is a specialty diagnostics company providing exceptional laboratory services and products in the field of brain health. C2N’s high-resolution mass spectrometry-based biomarker products are used for: clinical decision-making to improve patient care, including diagnosis and treatment monitoring; maximizing the quality and efficiency of clinical trials that test novel treatments for neurodegeneration; and providing innovative tools to help healthcare researchers better understand novel mechanisms of disease, identify new treatment targets, and conduct important epidemiological studies to improve global public health.

About the AI-Mind Project
The AI-Mind project aims to ease the burden of dementia by creating innovative, AI-driven tools that assist healthcare professionals in predicting dementia risks in patients affected by mild cognitive impairment (MCI). Most dementia treatments focus on managing symptoms once they appear, leaving little room for early prevention. AI-Mind seeks to transform this process by replacing complex and inefficient screening methods with advanced, automated tools powered by AI. These tools will address the critical need for early and precise diagnosis, allowing doctors to identify patients at high risk of developing dementia with greater confidence.

The AI-Mind project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 964220. This article reflects the views of the author, and the European Commission is not responsible for any use that may be made of the information it contains.

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Bringing Trial Activities to the Participant – Lessons from the RADIAL Proof-of-Concept Trial

Francesca Hazel — Wed, 22 Oct 2025 13:23:56 +0000

Bringing Trial Activities to the Participant

Lessons from the RADIAL Proof-of-Concept Trial

The move toward more participant-centric clinical research has taken an important step forward.

At the Clinical Pharmacology & Therapeutics journal, the first papers from the RADIAL trial, the flagship study of the Trials@Home project have now been published, offering valuable insights into how clinical research can be effectively brought to participants’ homes.

The project set out to explore the opportunities, benefits, and challenges of moving beyond traditional site-based clinical trials toward decentralised and hybrid approaches, all while maintaining scientific rigor, participant safety, and regulatory compliance.

The Challenge: Rethinking the Traditional Clinical Trial Model

For decades, clinical trials have relied on participants visiting centralised research sites for every step—from screening and consenting to assessments and follow-up.

While this model has proven robust, it presents significant barriers to accessibility, inclusivity, and efficiency. Participants often face long travel times, scheduling constraints, and logistical burdens that can limit enrolment and retention.

As digital health technologies mature, a key question has emerged:
Can clinical trials be conducted safely and effectively from the participant’s home?

Addressing this question requires balancing innovation with regulatory and operational standards—ensuring that new models of research remain reliable, compliant, and participant-friendly.

A Multi-Arm Approach: Traditional, Remote, and Hybrid Designs

To explore this question, the RADIAL trial implemented a unique three-arm design comparing:

Traditional (site-based) – all study activities conducted at research sites.
Remote (fully decentralised) – participants completed all study tasks at home.
Hybrid – a blend of site visits and remote participation.

Each arm was assessed according to key performance indicators related to safety, data quality, participant satisfaction, and operational efficiency.

Our organisation served as the core technology provider for the trial—helping enable remote assessments, data capture, and participant engagement tools across all trial configurations.

Key Findings: Proof of Feasibility and Value

Initial results from the RADIAL trial demonstrate that decentralised and hybrid models can be safe, effective, and participant-friendly, provided that technology and operational workflows are implemented thoughtfully.

Key takeaways include:

Comparable data quality and safety were achieved across all trial arms, indicating that decentralised models can maintain high standards of integrity and compliance.
Participant satisfaction was high in the remote and hybrid arms, highlighting the appeal of reduced travel and greater scheduling flexibility.
Operational efficiency improved in several domains, though logistical and regulatory complexities require continued refinement.

These findings offer concrete evidence that clinical trial activities can indeed be brought to the participant—without compromising scientific or ethical standards.

Collaboration, Curiosity, and Impact

Our involvement in the Trials@Home project was guided by three core principles:

Collaboration – Working in a consortium of leading pharmaceutical companies, technology providers, and academic partners allowed us to integrate diverse expertise spanning medical, regulatory, and ethical dimensions.
Curiosity – Challenging traditional models of research delivery was essential to driving innovation and reimagining how clinical trials can operate.
Impact – Our focus was always on where technology could add the greatest value—supporting, not replacing, the human aspects of clinical research.

Why This Matters

Decentralised and hybrid clinical trial models have the potential to transform how research is conducted globally. By making participation more accessible, inclusive, and flexible, these models can reduce barriers, enhance diversity in clinical research, and speed up the generation of meaningful evidence.

Validated technologies, robust protocols, and strong partnerships are key to scaling these innovations safely and effectively.

Implications and Future Directions

The publication of the RADIAL trial papers marks an important milestone, but the work continues. Future efforts will focus on:

Optimising remote recruitment and consenting processes to ensure inclusivity and compliance.
Refining technology solutions to further streamline data capture and monitoring.
Building regulatory and operational frameworks that support widespread adoption of decentralised approaches.

By learning from the RADIAL experience, sponsors and CROs can design future studies that blend the best of both worlds—maintaining scientific rigor while putting participants at the center.

Conclusion

The RADIAL trial has demonstrated that bringing clinical research to participants’ homes is not only feasible but can enhance the quality, efficiency, and inclusivity of clinical trials.

As we continue to refine these approaches, we move closer to a future where participation in clinical research is more flexible, accessible, and human-centered—no matter where participants live.

We are proud to have contributed to this landmark initiative and look forward to helping our partners apply these learnings to shape the next generation of decentralised clinical trials.

References

Van Den Berg, R. L. et al. Digital remote assessment of speech acoustics in cognitively unimpaired adults: feasibility, reliability and associations with amyloid pathology. Alz Res Therapy 16, 176 (2024).
Robin, J. et al. Automated detection of progressive speech changes in early Alzheimer’s disease. Alz & Dem Diag Ass & Dis Mo 15, e12445 (2023).
Robin, J., Xu, M., Kaufman, L. D. & Simpson, W. Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment. Front. Digit. Health 3, 749758 (2021).

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Author

Rob Baker
Chief of Product & Operations

Francesca Hazel
Job title

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The post Bringing Trial Activities to the Participant – Lessons from the RADIAL Proof-of-Concept Trial appeared first on Cambridge Cognition.

Speech Analysis as an Objective Biomarker in MDD Trials Speech Biomarkers for Alzheimer’s Disease Show Promise Across Multiple Languages

Francesca Hazel — Tue, 21 Oct 2025 15:29:03 +0000

Speech Biomarkers for Alzheimer’s Disease Show Promise Across Multiple Languages

The search for reliable, accessible biomarkers for early detection of cognitive decline has taken an important step forward.

At AAIC 2025, our team presented data demonstrating that speech and language patterns can serve as valid digital biomarkers for Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD) across multiple languages. This is a critical advancement for global clinical research, helping ensure that early detection and monitoring tools are inclusive and effective for diverse populations.

The Challenge: Moving Beyond English-Only Research

While researchers have long recognized that neurodegenerative diseases affect speech and language, most studies have historically focused on English-speaking populations. As clinical trials expand globally, there is a pressing need for digital endpoints that work reliably across different languages.

A key question emerged: Do speech markers for MCI and AD hold true across different languages and linguistic structures? Addressing this question could significantly enhance the inclusivity and applicability of digital cognitive assessments.

A Multilingual Approach

To explore this, we analySed baseline data from 242 patients with MCI and AD across four languages: Danish, Dutch, German, and Spanish. Each participant completed a standardised picture description task in their native language, and we analysed their speech using the Winterlight speech processing pipeline.

We focused on five key speech features previously linked to MCI and AD:

Number of picture objects described
Number of nouns used
Speech rate
Pronoun-to-noun ratio
Average word length

We also created a composite score combining these measures and examined how all features related to the Mini Mental State Examination (MMSE), a widely used cognitive assessment tool.

Key Findings: Consistency Across Languages

Our results provide encouraging evidence for the cross-linguistic validity of speech biomarkers:

Consistent patterns across languages: The relationships among speech features showed generally consistent directions across all four languages, with German showing the strongest correlations.
Strong correlations with cognitive function: Both the composite score and object content unit score were significantly correlated with MMSE scores across all languages. Composite score correlations ranged from –0.26 to –0.47, while object content unit correlations ranged from 0.27 to 0.42.
Enhanced sensitivity through combined measures: The composite score and object content unit score were more sensitive to cognitive decline than individual speech features alone, suggesting that a holistic approach to speech analysis is most effective.

Why This Matters

Validated digital endpoints that work across languages can enable more inclusive and diverse clinical trials, potentially accelerating the development of new treatments for neurodegenerative diseases.

Speech-based assessments offer several advantages:

Non-invasive and accessible
Provide objective, quantifiable data
Complement clinician assessments and patient-reported outcomes

These tools could transform how cognitive health is monitored, making early detection of MCI and AD possible for people regardless of the language they speak.

Implications and Future Research

These results provide objective evidence that executive function deficits can be captured through the speech of individuals with depression. By detecting these changes through brief, low-burden, scalable assessments, speech markers offer a valuable tool for assessing both depression and cognitive dysfunction in a flexible, high-frequency manner. This helps to shine a light on aspects of cognition and behaviour that are affected but often missed by routine clinical assessments.

The next crucial steps involve a longitudinal follow-up to build on these findings with repeated testing. This research will test whether voice assessments can track changes in depressive symptoms following treatment.

Conclusion

The cross-linguistic validity of speech and language digital biomarkers represents a meaningful step toward more inclusive and accessible approaches to detecting and monitoring cognitive decline. By continuing to refine these tools and expand their use across diverse populations, we move closer to a future where early intervention for neurodegenerative diseases is available to all.

References

Van Den Berg, R. L. et al. Digital remote assessment of speech acoustics in cognitively unimpaired adults: feasibility, reliability and associations with amyloid pathology. Alz Res Therapy 16, 176 (2024).
Robin, J. et al. Automated detection of progressive speech changes in early Alzheimer’s disease. Alz & Dem Diag Ass & Dis Mo 15, e12445 (2023).
Robin, J., Xu, M., Kaufman, L. D. & Simpson, W. Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment. Front. Digit. Health 3, 749758 (2021).

Poster Download Request

Thank you for your interest in our research. Please complete the form below to access our research content.

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Author

Rob Baker
Chief of Product & Operations

Francesca Hazel
Job title

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26 October 2026

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01 October 2026

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22 September 2026

First new CANTAB® product features developed & launched from the landmark INTUITION project

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The post Speech Analysis as an Objective Biomarker in MDD Trials Speech Biomarkers for Alzheimer’s Disease Show Promise Across Multiple Languages appeared first on Cambridge Cognition.

CTAD | Posters & Presentations

Francesca Hazel — Mon, 13 Oct 2025 14:37:14 +0000

CTAD | Posters & Presentations

Hilton San Diego Bayfront, 1 Park Boulevard - San Diego, CA 92101 | 1-4th December

We're excited to announce we are attending the 18th Clinical Trials on Alzheimer's Disease (CTAD)

This year’s Clinical Trials on Alzheimer’s Disease (CTAD) conference brings together global leaders advancing research and innovation in Alzheimer’s and dementia treatment. We’re proud to be part of this important event connecting academia, industry, and regulatory experts to drive meaningful progress in clinical development.

As pioneers in digital health and cognitive assessment technologies, Cambridge Cognition is committed to supporting advancements in the measurement of cognitive function, improving trial efficiency, and enhancing the understanding of brain health in neurodegenerative diseases.

CTAD offers an exciting opportunity to share perspectives, explore emerging research, and engage with the international Alzheimer’s community. We look forward to connecting with researchers, clinicians, and partners who share our mission to accelerate innovation in neuroscience.

Join us as we celebrate progress, collaboration, and the pursuit of better outcomes for patients worldwide. See you at CTAD 2025!

Want to book a meeting to speak with us at the event?

Please note this calendar timezone is based in the same as the event times (UTC: – 07:00 Pacific Time), please ensure you change the timezone before booking a meeting slot.

Presentation download request

Thank you for your interest in our research. Please complete the form below to access our research content.

29 October 2026

Adding speech to a CANTAB battery in Alzheimer's disease/MCI research

26 October 2026

Advancing Alzheimer's prevention: Are clinical trials ready for earlier interventions?

06 October 2026

Cambridge Cognition joins Imperial College-led NHS study bringing earlier Alzheimer’s diagnosis into primary care

01 October 2026

Measuring speech in schizophrenia spectrum disorders

22 September 2026

First new CANTAB® product features developed & launched from the landmark INTUITION project

21 September 2026

C2N Diagnostics Expands Global Partnerships in United Kingdom on World Alzheimer’s Day, Joins Cambridge Cognition and The Alzheimer's Trust to Improve Alzheimer's Disease Diagnosis

The post CTAD | Posters & Presentations appeared first on Cambridge Cognition.