Streamlined solutions for clinical trials

Linus Health’s digital cognitive assessment tools have been used in more than 60 clinical trials worldwide, supporting research across therapeutic areas like Alzheimer’s disease, Parkinson’s disease, and ALS. Linus’ validated, process-based assessments and platform support Phase I-IV studies, enabling sponsors to build custom digital assessment batteries aligned with each protocol, population, and operational need. With remote-capable assessments and questionnaires, Linus Health is helping research teams accelerate participant recruitment, strengthen cognitive outcome measures, and collect standardized data for secondary, safety, exploratory, and post-market evidence endpoints.

For sponsors planning multinational studies, Linus Health’s portfolio includes Class I and Class II medical devices that are FDA-listed in the United States, CE-marked and classified in the European Union under EU Medical Device Regulation (MDR), UKCA-marked for Great Britain, and registered under Health Canada’s Medical Device Establishment License (MDEL). Linus Health supports 18 languages and has worked in dozens of countries for pharmaceutical and clinical trial research studies, enabling global programs while allowing sponsors to address country-specific regulatory, ethics, and site-activation requirements applicable to each study. Read more about Linus Health’s regulatory information.

Digital cognitive assessments and blood biomarkers offer complementary views of Alzheimer’s disease. Blood biomarkers provide evidence of underlying Alzheimer’s pathology, while digital cognitive assessments measure the functional cognitive change that matters to participants, clinicians, and research teams. Together, these data points can help researchers identify and characterize potential participants, enrich study populations, and track cognitive performance alongside biological signals. Linus Health’s digital assessments can add a repeatable measure of cognition to research teams and their work, supporting more informed recruitment and study design. Learn how digital screening complements blood biomarkers.

Linus Health’s Digital Clock and Recall (DCR) is a 3-minute, iPad-based assessment that pairs the DCTclock, a digital clock drawing test, with 3-word immediate and delayed recall (Gomes-Osman et al., 2024; Jannati et al., 2024). It uses the same tasks as the Mini-Cog. The difference is that DCR doesn’t just score the final answer. It also records how each task is done, including drawing movements, pauses and latencies, and speech features during recall. This process-based approach gives research teams more information per minute of testing than tools that solely produce a score.

In comparison studies, DCR has shown higher accuracy than widely used screening tools. In 828 participants from the Bio-Hermes study, experienced raters scored the same clock drawings and recall responses with standard Mini-Cog rules. DCR’s process-based scoring correctly classified 44 cognitively impaired individuals that Mini-Cog scoring missed, while the reverse happened in only four cases (Gomes-Osman et al., 2024). In 706 Bio-Hermes participants, the DCR 0–5 score detected MCI and mild dementia more accurately than the MMSE (AUC 0.70 vs. 0.63), and took fewer than 3 minutes (Jannati et al., 2024). Of 104 participants who scored normal on the MMSE, but had verbal memory impairment on the Rey Auditory Verbal Learning Test (RAVLT), DCR flagged 81% as impaired; and DCR scores were less affected by ethnicity than MMSE scores (Jannati et al., 2024). In a real-world neurology clinic sample of 49 patients, DCR detected MCI with an AUC of 0.90 vs. 0.71 for the MoCA, and raised specificity from 41% to 88% (Castillo Dutor et al., 2026). The DCTclock has also shown agreement with established neuropsychological measures, including the RBANS, MoCA, MMSE, Trails A and B, and the Hooper Visual Organization Test (correlations of 0.51 to 0.66) (Souillard-Mandar et al., 2021).

Evidence also links DCR to Alzheimer’s disease pathology, which matters for trial screening and enrichment. In cognitively normal older adults, poorer DCTclock performance was associated with greater amyloid and tau burden on PET. It separated amyloid-positive from amyloid-negative participants with a larger effect size than the Preclinical Alzheimer Cognitive Composite (PACC) (Cohen’s d 0.76 vs. 0.30). In the same study, the DCTclock also distinguished cognitively normal adults from those with MCI or early Alzheimer’s dementia with an AUC of 0.86 (Rentz et al., 2021). In 930 Bio-Hermes participants, separate DCR-based machine learning models classified both cognitive impairment (AUC 0.83) and amyloid PET status (AUC 0.81), while the MMSE, RAVLT, and Cognivue were less accurate for amyloid status (AUCs 0.70 to 0.73) (Jannati et al., 2025a). Combined, these models identified potential candidates for anti-amyloid treatment, defined as MCI or mild dementia with a positive amyloid PET, with an AUC of 0.84 and a negative predictive value of 0.93 (Jannati et al., 2025b). For life sciences teams, this means a brief, objective cognitive measure that could help reduce costly screen failures and add more information to biomarker data when finding, enriching, and characterizing study participants.

References:
Castillo Dutor N, Hsueh Lema LE, Tormos Muñoz JM, et al. The Digital Clock and Recall outperforms the MoCA in detecting mild cognitive impairment in a real-world clinical setting. Poster presented at: Alzheimer’s Association International Conference (AAIC); 2026. 

Gomes-Osman J, Borson S, Toro-Serey C, et al. Digital Clock and Recall: a digital, process-driven evolution of Fthe Mini-Cog. Front Hum Neurosci. 2024;18:1337851. doi:10.3389/fnhum.2024.1337851

Jannati A, Toro-Serey C, Gomes-Osman J, et al. Digital Clock and Recall is superior to the Mini-Mental State Examination for the detection of mild cognitive impairment and mild dementia. Alzheimers Res Ther. 2024;16:2. doi:10.1186/s13195-023-01367-7

Jannati A, Thompson K, Toro-Serey C, et al. Concurrent detection of cognitive impairment and amyloid positivity with a multimodal machine learning-enabled digital cognitive assessment. Alzheimers Res Ther. 2025a;17:261. doi:10.1186/s13195-025-01913-5

Jannati A, Thompson K, Toro-Serey C, et al. The Digital Clock and Recall identifies eligible candidates for Alzheimer’s disease-modifying treatment. Poster presented at: Clinical Trials on Alzheimer’s Disease (CTAD) Conference; 2025b.

Rentz DM, Papp KV, Mayblyum DV, et al. Association of digital clock drawing with PET amyloid and tau pathology in normal older adults. Neurology. 2021;96(14):e1844-e1854. PMID: 33589537

Souillard-Mandar W, Penney D, Schaible B, Pascual-Leone A, Au R, Davis R. DCTclock: clinically-interpretable and automated artificial intelligence analysis of drawing behavior for capturing cognition. Front Digit Health. 2021;3:750661. doi:10.3389/fdgth.2021.750661

Linus Health applies a process-based approach across complementary digital modalities to help sponsors build a full view of treatment benefits. Configurable study batteries can capture cognitive performance and how participants complete tasks across drawing/praxis, speech/language, gait/balance, and mobile eye-tracking. This generates an objective measure of cognition, motor function, mobility, attention, and visuospatial behavior. Linus Health’s DCTclock captures and quantifies more than 100 features of the drawing process, extending measurement beyond the final clock image to include timing, movement, and strategy.

Linus Health’s electronic Person-Specific Outcomes Measure (ePSOM™) complemented these objective measures by capturing each participant’s brain health priorities and their confidence in managing them over time. Together, digital process measures and participant-reported outcomes can support cognitive, functional, safety, exploratory, and treatment benefit endpoints. This helps sponsors assess if treatment changes measurable function, and whether those changes matter in participants’ lives.