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.

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:

1. Number of picture objects described

2. Number of nouns used

3. Speech rate

4. Pronoun-to-noun ratio

5. 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.

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!

This years Clinical Trial Innovation Summit brings together global leaders driving the future of clinical research and we’re proud to be part of the conversation.

We’ll be presenting on “The Importance of Cognitive Assessment in Drug Development,” exploring how innovative cognitive tools are transforming safety and efficacy evaluation across both CNS and non-CNS indications. From early-phase dose selection to long-term outcomes, sensitive computerised assessments and speech biomarkers are providing powerful new insights into drug effects.

It’s a fantastic opportunity to exchange ideas, share our perspective, and collaborate with researchers, industry leaders, and regulatory experts shaping the next generation of clinical trials.

Join us as we highlight how advances in cognitive assessment are opening new possibilities for pharmacodynamic insights, real-world data collection, and smarter trial design.

This year’s program features world-class discussions on precision psychiatry, psychedelic therapies, and lessons from global clinical trials—and we’re proud to be contributing to the conversation.

We’ll be presenting our posters during the dedicated poster session, sharing our latest research and insights with leaders from academia, industry, and regulatory bodies. It’s a fantastic opportunity to exchange ideas, get feedback, and collaborate with experts shaping the future of mental health and neuroscience innovation.

Get ready to explore how our latest findings are pushing the boundaries of what’s possible in early detection, reliable assessment, and effective trial design for neurodegenerative diseases.

Speech as a digital biomarker in clinical research

Changes in how we speak—how quickly we talk, how often we pause, and the words we choose—can be early signs of cognitive decline. People with mild cognitive impairment (MCI) or dementia due to Alzheimer’s disease (AD) often show subtle shifts in their speech patterns, such as slower speech, longer pauses, and changes in pronoun or noun use.^1,2,3

Researchers have been looking for ways to measure these changes in natural, everyday-like situations. One promising approach is the picture description task—a short, low-burden activity where participants describe what they see in an image. The task can be done remotely, captures naturalistic speech, and is well-suited for repeated testing over time.

DEFEAT-AD collaboration

Researchers at Amsterdam UMC led the DEFEAT-AD study to collect high-frequency speech assessments remotely in a sample of 50 cognitively unimpaired individuals. Participants completed a 5-day “burst” of testing using a tablet and the Winterlight Assessment app including two picture description tasks per day for five consecutive days. In the repeating condition, the same picture was shown every day. In the alternating condition, a different picture was shown each day. After a 2–3 week break, participants repeated the same 5-day burst with identical stimuli.

How reliable are speech measures?

In order for speech measures to be able to be used in higher frequency testing, we need to determine their reliability and susceptibility to practice or learning effects when these tasks are completed repeatedly over several days.

We found that most of our selected speech measures had acceptable test-retest reliability over the five days of testing, and it didn’t matter much if the same or different picture was shown. Some measures, including total words produced and number of objects described, showed some evidence of practice/learning effects, with increasing scores over the first few days.

These results show that picture description tasks can be a reliable way to track speech changes over time in a high-frequency, remote testing setup. Alternating pictures or including a practice phase before data collection may help reduce learning effects. Because picture description tasks are ecologically valid, easy to administer, and low burden, they are promising tools for long-term monitoring of cognitive health—especially in remote or decentralized clinical trials.