We de-risk clinical development by enabling smarter, faster and more valuable decisions
Clinical trials increasingly generate continuous data from wearable and connected devices. Yet much of that data remains difficult to interpret, difficult to operationalise, and underused in trial decision-making.
LONGITUDINAL helps sponsors and CROs turn continuous data into decision-ready insight.
Our platform is being developed to support earlier visibility between patient visits, helping trial teams identify signals related to adherence, tolerability, physiological response and patient burden.
Solving critical pain points in phase II & phase III
Protocol Optimisation
Better visibility into patient behaviour, burden and response can support smarter protocol design and reduce avoidable trial complexity. Continuous data has the potential to identify issues earlier, before they become costly operational or clinical problems.
Go/no-go Decisions
Development decisions are often made with incomplete visibility between scheduled visits. LONGITUDINAL is designed to help trial teams identify meaningful signals earlier, supporting greater confidence in whether to continue, adapt or stop a programme.
Patient Stratification
Continuous data can reveal patterns that are not always visible through intermittent assessments. By helping identify differences in patient response, burden and behaviour, LONGITUDINAL supports more informed stratification and trial decision-making.
Platform Snapshots
Identify patients who may need earlier attention
LONGITUDINAL is designed to help trial teams identify signals that may indicate adherence issues, tolerability concerns, physiological change or increasing patient burden. The aim is to provide clearer visibility between visits and support earlier, more informed clinical trial decisions.
Trigger actions directly from trial insight
The platform is being developed to help clinical and operational teams move from insight to action. This includes identifying where follow-up, escalation, review or intervention may be required, while keeping the workflow focused and practical for trial teams.