Litmus Health Platform

The Litmus Health Platform is a clinical trial data platform designed to support the full clinical trial lifecycle, from wearable and sensor data collection through to scientific analysis. It is built for life sciences organizations running early-stage trials, registry work, observational studies, and post-market research, and provides infrastructure for high-volume, high-velocity patient data capture, storage, and analysis across multiple wearable devices, sensors, and data streams.

The platform is device agnostic and offered as a Software-as-a-Service solution, with on-premises and private cloud deployment options available. It is designed to meet HIPAA, 21 CFR Part 11, and NIST Cybersecurity Framework requirements, and outputs data in CDISC CDASH format as required by the FDA.

Core Infrastructure Capabilities

• Built on scalable microservices architecture using production-grade technologies, with fault-tolerant and horizontally scalable data handling.
• Supports multi-tenant cloud, managed private cloud, hybrid, and multi-datacenter deployments, as well as on-premises installation.
• All patient data is stored in its original raw format, without transformation or normalization, preserving data quality for future use.
• Immutable records and audit trails allow full data lineage tracing.
• Patient data is collected and stored using industry-standard security and encryption practices, with monitoring, backup systems, and automated processes supporting compliance.

Trial Builder

• Provides a modular system for establishing electronic data capture systems for studies through a simple interface.
• Supports more than 200 data sources describing patient behavior and environment.
• Draws from a library of validated surveys and can integrate with additional instruments.
• Allows selection of one or more data streams, or the definition and addition of custom streams.
• Gathers data from wearables, non-wearable sensors, smartphones, other devices, surveys, and ePROs.
• Supports export to other systems for downstream analysis and interpretation.

Trial Companion App

• A mobile application available for iOS and Android that collects external wearable device and phone data, transmitting it to the platform in real time.
• Handles ePRO survey responses, which can be collected at regular intervals or triggered by external events.
• Designed to reduce friction for patients, supporting more timely and accurate data collection across multiple clinical trials within a single application.

Study Hub

• A unified dashboard displaying real-time data on study progress, patient population trends, and individual participant data.
• Supports monitoring of participant compliance and overall study progression.
• Provides at-a-glance views of enrollment and adherence.
• Allows configuration of customizable push notifications and text messages to remind patients to complete required actions.
• Supports download of whole or sliced raw JSON data.
• Enables configuration of persistent, faceted searches to monitor specific trends or cohorts.

Litmus ML

• Integrates with open, validated community tools used in research workflows.
• Provides modules for aligning and interpolating time series data, integrating multiple orthogonal data sources, and identifying correlations between behavior, environment, and patient outcomes.
• Combines heterogeneous data streams into a single normalized corpus for analysis.
• Provides direct access to data in the researcher's notebook of choice, without data wrangling or pipeline setup.
• Uses proprietary error modeling to normalize device variance and reduce uncertainty across clinical trial data.

The platform is designed to be operational within four weeks or less. It supports automated provisioning of electronic data collection systems and rapid deployment across diverse IT environments, handling data engineering and compliance infrastructure so research teams can focus on scientific work.