For clinical trials
Digital Endpoint Strategy
Choose digital endpoints around the question your trial needs to answer.
BioSensics helps sponsors select digital measures for a defined clinical trial. We connect the treatment target, patient population, trial duration, and intended endpoint role with available evidence, measurement sensitivity, and practical collection requirements.
The right measure. A clear rationale. A defined trial use.
Turn your trial objectives into a prioritized endpoint strategy, with supporting evidence, collection requirements, and remaining gaps made clear.
Which digital measures belong in your trial?
Start with the aspect of disease or function the treatment is intended to affect. We assess which available measures address that question, what their evidence supports in your population, and whether the proposed trial can collect and interpret them consistently. The result is a reasoned selection and an operational endpoint definition your clinical and statistical teams can review.
What your team receives
Recommendations are tailored to your protocol stage, available evidence, and study objectives.
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Prioritized endpoint shortlist
Recommended measures with a rationale for their proposed primary, secondary, or exploratory role. Alternatives and tradeoffs are documented for sponsor review.
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Evidence and gap assessment
A comparison of relevant measurement performance, clinical relationships, and longitudinal findings, with limitations and evidence gaps specific to the proposed trial use.
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Endpoint and assessment specification
Proposed endpoint variables, assessment schedules, aggregation windows, quality criteria, and data requirements for protocol and statistical planning.
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Implementation and evidence roadmap
A practical handoff covering collection needs, operational dependencies, and further analyses or validation studies required before the proposed use.
Select for the clinical question and the trial
Consider gait, balance, daily activity, upper-limb function, speech, cognition, and video-based measures according to the treatment target and supporting evidence.
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Clinical relevance
Connect the measured concept to the treatment target and outcomes that matter to patients. Define what a change would represent clinically.
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Population and setting
Review evidence in the intended disease stage, functional range, and collection setting. Consider floor and ceiling effects, assistive devices, and relevant participant characteristics.
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Sensitivity and variability
Assess observed change, measurement error, and between- and within-participant variability over relevant intervals. Distinguish evidence of disease progression from demonstrated treatment responsiveness.
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Reliability and interpretation
Review repeatability, measurement performance, clinical associations, and meaningful-change evidence. Identify which findings apply to the specific device, task, and processing method.
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Collection feasibility
Balance measurement needs with participant burden, adherence, accessibility, site workflow, and home collection. Anticipate missing data and the support required for consistent assessments.
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Trial design and endpoint role
Match measures to trial duration, assessment timing, and planned comparisons. Align the proposed endpoint role with the sponsor's clinical, statistical, and regulatory strategy.
From a selected measure to a defined endpoint
The endpoint definition connects what is collected with the comparison the trial will make.
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Define the variable
Specify the task or sensor measure, unit, direction of interpretation, and processing version. Distinguish the measured feature from the endpoint derived from it.
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Set the assessment windows
Define baseline and follow-up windows, recording duration, repeat assessments, and aggregation across observations. Match those choices to the expected timing of change.
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Specify usable data
Propose completion or wear requirements, quality checks, and valid-assessment rules. Agree how gaps and unusable observations enter the statistical planning.
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Connect to the analysis
Define the proposed summary, such as change from baseline at a specified time point. Align population, comparisons, and handling of treatment changes with the statistical team.
From trial objectives to an endpoint recommendation
Work with your clinical and statistical teams before the assessment schedule and endpoint definitions are finalized.
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Frame the trial question
Confirm the treatment target, population, study duration, development stage, and proposed role of digital measures.
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Compare the candidates
Review relevant publications, technical documentation, and available study findings against agreed selection criteria.
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Recommend and specify
Discuss the shortlist, resolve tradeoffs, and define the recommended endpoints and assessment requirements.
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Plan the next step
Coordinate deployment and documentation, or recommend focused research where an evidence gap prevents the proposed use.
Planning your endpoint strategy
How does this differ from Endpoint Development and Validation?
This service evaluates available measures and evidence to recommend endpoints for a particular trial. Endpoint Development and Validation conducts research to develop a measure or establish evidence for its proposed use. Selection may identify the need for that research.
Can we bring an existing endpoint shortlist?
Yes. We can review a proposed shortlist, compare alternatives, or refine endpoint definitions and collection schedules. The scope follows the decisions your team still needs to resolve.
Does a sensitive measure necessarily detect a treatment effect?
No. Evidence that a measure detects disease-related change helps evaluate its suitability, but treatment responsiveness depends on the intervention, population, trial design, and relevant interventional evidence.
What if the available evidence is insufficient?
The recommendation may be a different measure, an exploratory role, additional analysis, or prospective validation. We identify the evidence needed to support the proposed use and a practical next step.
How does endpoint strategy connect with Interim Trial Decision Support?
Endpoint strategy establishes which measures to use and how to collect and summarize them. For a trial with a planned interim review, we also consider the assessment timing and data needed for that review. Interim Trial Decision Support then uses accumulating trial data to assess emerging signals, reassess power, and evaluate sample-size scenarios within the agreed trial design.
Connect your endpoint strategy with trial delivery and decisions
Carry the endpoint plan into study delivery, planned interim reviews, analysis, and regulatory preparation.
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Endpoint Development and Validation
Conduct focused research when a candidate measure needs development or additional validation for the intended trial use.
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Clinical Trial Operations
Translate selected assessments into configured workflows, site training, participant support, and documented data delivery.
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Interim Trial Decision Support
Use sensitive digital measures in planned interim reviews to assess emerging treatment signals, reassess power, and evaluate sample-size changes within the agreed trial design.
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Data Analysis and Scientific Reporting
Scope targeted analyses of available data and prepare documented methods, interpretable findings, and scientific reports.
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Regulatory Support
Organize the scientific rationale and supporting technical evidence for sponsor-led regulatory discussions.
Define the digital endpoints for your next trial
Share your treatment target, indication, study design, and proposed measures. We will help identify the strongest choices and the evidence needed to support them.