WHITE PAPER
Implementing Digital Endpoints in CNS Clinical Trials
Digital EndpointsAre Transforming CNS Clinical Trials
Move beyond episodic clinic visits with continuous, real-world data that improves sensitivity, efficiency, and patient insight.
Traditional CNS clinical trials rely on infrequent, subjective assessments that miss critical fluctuations in disease progression and treatment response.
This white paper reveals how digital endpoints, powered by wearable sensors, mobile apps, and advanced analytics, enable continuous, objective measurement in real-world settings, improving trial precision and reducing noise.
Backed by scientific research and real-world implementation, it outlines how sponsors can design, validate, and operationalize digital endpoints for modern CNS trials.
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Inside this White Paper
A closer look at how digital endpoints enable continuous, real-world patient measurement
Emerging approaches to detecting subtle disease progression and treatment effects
Practical perspectives on incorporating patient-centric measurement into CNS trials
Considerations for improving statistical sensitivity and reducing trial burden
Frameworks for translating raw sensor data into clinically meaningful endpoints
Evolving regulatory context shaping the use of digital endpoints
About the Authors
Robert Ellis, Ph.D.
Head of Biomarker Exploration, Co-Founder, Koneksa
Robert Ellis, PhD, leads the development of model-driven approaches to solving complex clinical measurement challenges. His work focuses on translating physiologic signals into sensitive, interpretable endpoints through the integration of algorithms, signal characterization, and data-quality optimization.
Dr. Ellis has played a central role in shaping Koneksa’s measurement science framework, including the development of integrated modeling approaches that evaluate signal behavior, quantify variability, and improve endpoint performance across clinical programs. His expertise spans digital biomarkers, sensor-based data, and performance outcomes, with extensive application in neurodegenerative and rare disease research.
He holds a PhD in geophysics and brings more than 20 years of scientific and technical leadership experience supporting clinical development. Dr. Ellis has authored numerous peer-reviewed publications in digital measurement and is a named inventor on multiple patents related to sensor-based health monitoring and algorithm development.
Michael Mendoza,
Senior Vice President, Biometrics and Data Science, Koneksa
Michael Mendoza leads the company’s biometrics strategy and oversees the design and execution of data-driven clinical development programs. He is responsible for ensuring that clinical data are structured, integrated, and analyzed to support decision-ready, regulatory-grade evidence.
With more than 28 years of experience across pharmaceutical, biotech, and CRO organizations, Michael brings deep expertise across the full clinical data lifecycle, including study design, data management, statistical analysis, and submission readiness. His work integrates advanced analytics, digital technologies, and scalable data architectures to enable more efficient, insight-driven trials.
Michael has extensive experience implementing systems and strategies across EDC, eCOA, RTSM, CTMS, centralized monitoring, and AI-enabled analytics. He is known for building high-performing global teams and aligning biometrics and data science capabilities with evolving clinical and regulatory expectations, helping sponsors accelerate development timelines while improving data quality and interpretability.
