For clinical trials
Natural History Studies
Understand disease course. Build evidence for the next clinical study.
BioSensics partners with pharmaceutical sponsors to design and conduct observational research on disease activity, daily function, and progression. We combine clinical assessments, digital measures, participant reports, and selected biological biomarkers to investigate disease course and build longitudinal cohorts around your program's research questions.
Research that follows the disease over time
Connect what happens between clinic visits with clinical and biological findings, and plan data collection around the future questions your program needs to answer.
A study built around your scientific objectives
Design a new longitudinal study, incorporate digital assessments into an existing cohort, or use relevant BioDigit Database analyses to inform the research. Together, we define the population, assessments, follow-up, and analysis needed to investigate your indication. The central question is how the disease behaves: its course, variability, and relationships across symptoms, function, and biomarkers.
Research questions your study can answer
Define the scientific purpose before selecting assessments or technology.
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Understand disease activity and progression
Study disease activity, progression, and variability across participants and disease stages. Repeated measurements connect changes in symptoms and clinical status with everyday function.
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Discover and validate candidate biomarkers
Identify candidate biomarkers of disease activity or progression and evaluate their reliability and clinical relationships. Studies can combine digital, clinical, participant-reported, and selected biological measures, with validation matched to the intended research question.
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Develop external control cohorts
Design longitudinal cohorts with potential external-control use in mind. Align population definitions, outcomes, follow-up, and treatment documentation with the anticipated trial question.
What your team receives
Agree on concrete research outputs at the start of the engagement.
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Protocol and analysis plan
Defined objectives, eligibility criteria, assessment schedules, follow-up, analysis populations, and methods, with responsibilities agreed across the sponsor and study partners.
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Documented longitudinal data
Agreed datasets and data dictionaries, with measure definitions, processing records, collection windows, and quality summaries to support interpretation and subsequent analyses.
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Disease-course findings
Analyses of change, variability, and relationships across measures, presented through figures, tables, and a scientific report addressing the study's primary and exploratory questions.
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Implications for future research
A clear account of findings, uncertainties, and remaining evidence needs, including implications for subsequent studies and potential trial comparisons where part of the agreed scope.
Design the cohort around the question
Make the choices that determine what the study can explain.
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Population and clinical context
Define diagnosis, disease stage, relevant subgroups, and eligibility. Record care and treatment history needed to understand the observed course and potential differences between cohorts.
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Complementary assessments
Select clinical scales, wearable recordings, digital tasks, and participant reports. Include biological biomarkers when relevant and available, with compatible collection timing and documentation.
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Follow-up that captures change
Match visit frequency, home recording periods, and study duration to expected disease change. Plan for participant burden, retention, missing observations, and consistent assessment conditions.
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Future external-control use
Anticipate the trial's eligibility, baseline, outcomes, and follow-up. Collect relevant prognostic factors and treatment information so comparability, confounding, and data completeness can be evaluated.
Longitudinal research in practice
Examples from our public research portfolio illustrate complementary approaches.
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Progressive supranuclear palsy
Connect daily function with clinical change
PSP research combines repeated wearable recordings and digital assessments of speech, cognition, and motor function with clinical outcomes to investigate longitudinal patterns.
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Inclusion body myositis
Follow mobility and upper-limb function
IBM research combines at-home recordings of daily mobility and upper-limb movement with repeated strength assessments, functional ratings, and participant reports.
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Friedreich ataxia
Study digital and biological relationships
FA research examines wearable measures alongside clinical severity and selected biological measures. Longitudinal collection extends the investigation to changes in function over time.
From sponsor question to longitudinal evidence
Coordinate study design, conduct, analysis, and interpretation around the agreed research objectives.
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Define the research
Clarify disease-course questions and intended data uses. Review existing evidence and cohort coverage to identify what new collection must address.
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Design and prepare
Develop the protocol and analysis plan, select assessments, and agree on site responsibilities, ethics and consent requirements, and data governance.
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Conduct and follow
Support study-specific assessment deployment, training, and data collection. Monitor completion and quality, coordinating follow-up through the agreed operating plan.
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Analyze and interpret
Evaluate disease trajectories and relationships across measures. Deliver documented findings and discuss their implications for the sponsor's next research decisions.
Planning your research
How does this differ from Endpoint Development and Validation?
Natural history research asks how disease evolves and how clinical, digital, and biological findings relate. Endpoint Development and Validation evaluates whether a specific measure is suitable for its intended trial use. One study can inform both when those objectives are planned explicitly.
Do participants receive a study treatment?
Natural history studies observe participants without assigning treatment as part of the research. Participants may receive standard care; relevant therapies and changes in care are documented to help interpret the disease course.
Can the cohort become an external control?
Potential use should inform study design early. Suitability depends on the future trial's question, population, outcomes, timing, treatment context, data quality, and ability to address confounding. An existing cohort is assessed against those requirements before a comparison is proposed.
Can existing data and new collection be combined?
Yes, where populations, measures, assessment timing, and permitted uses support the research question. Relevant BioDigit Database analyses can inform a new study, with compatibility and gaps reviewed before sources are combined.
How are the scope and data use agreed?
The project agreement defines research responsibilities, deliverables, access, ownership, permitted reuse, and publication arrangements. These reflect the participating organizations, source permissions, and study consent.
Connect your research with the right support
Coordinate complementary research, data, and scientific expertise around your program.
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Endpoint Development and Validation
Design focused studies to develop and validate candidate measures for a defined clinical-trial use.
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BioDigit Database
Assess existing digital, clinical, and selected biological data for relevance to your research question.
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Data Analysis and Scientific Reporting
Connect study data with documented analyses, clear findings, and scientific reports.
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Regulatory Support
Organize evidence for discussions about the proposed use of digital measures and study findings.
Build the natural history study your program needs
Share your indication, population, and scientific questions. We can define a study that connects disease understanding with the evidence needs of your development program.