Trials begin where the regulatory pathway demands — often without the longitudinal evidence that would inform protocol design, population selection, and feasibility upstream, or the post-approval evidence and access strategy that would be sharpened by understanding how the same patients move through care.
Pedestal Health is built to change both: an integrated evidence partner with the cohorts, technology, and clinical relationships to support your evidence strategy from clinical development to care delivery.
Trials begin where the regulatory pathway demands — often without the longitudinal evidence that would inform protocol design, population selection, and feasibility upstream, or the post-approval evidence and access strategy that would be sharpened by understanding how the same patients move through care.
Pedestal Health is built to change both: an integrated evidence partner with the cohorts, technology, and clinical relationships to support your evidence strategy from clinical development to care delivery.
Pedestal Health's longitudinal cohorts support evidence generation that compounds over time — insights from our longitudinal cohort data shape the trials and prospective studies we run, and what those studies produce flows back into the cohorts as therapies move into care.
Each phase strengthens the next, rather than starting from scratch. The model supports three categories of decisions, each grounded in the same underlying infrastructure.
Clinical development
Translational and Study teams
Program teams
Disease characterization, natural history, biomarker work, and feasibility informed by longitudinal cohort data.
Protocol design and population selection grounded in real clinical contexts.
Prospective studies and clinical trials run within Pedestal's cohort and site infrastructure.
External control arms.
Sub-phenotyping and risk stratification.
Regulatory
HEOR / Market Access
Payers
Medical Affairs
Post-authorization safety studies.
Supplementation of regulatory submissions with longitudinal evidence.
External control arm contributions to FDA and EMA filings.
Comparative effectiveness.
Market access evidence.
Publication strategy and support.
Clinicians
Health systems
Care delivery teams
PI-led research
Treatment pattern characterization in routine practice.
Long-term effectiveness and safety.
Clinical decision support evidence.
Therapeutic inertia and treat-to-target gap analyses.
Partnership infrastructure for clinician-led research and publications.
Our work has shown us what the field actually needs: not just another retrospective data source or another standalone clinical trial, but a hybrid system that keeps generating evidence on the same patients as the questions evolve. Our approach guides the decisions that matter most to clinical programs in active development as they arise:
At enrollment, we capture structured and unstructured EHR data and patients consent to prospective data collection. The starting point is richer than claims or registry data alone, and the same patient stays in the system from there.
The same patients, followed over years. Continuously updated structured and unstructured EHR data alongside the prospectively collected measures from enrollment. The substrate for natural history, disease characterization, treatment patterns, and comparative effectiveness.
Programs that need additional PROs, biomarkers, imaging, or other measures can activate them through dedicated protocols layered on the same patient population.
A network of activated sites and a continuously enrolled patient population already in the system, ready to support embedded prospective studies, external control arms, and trial work that draws on what's already running.
Patients enrolled before approval and followed past launch on the same continuous infrastructure, with partner-specific protocols providing the rigorous structure required for post-authorization safety, real-world effectiveness, and long-term outcomes work.
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