End-to-End RWE Across the Drug Development Lifecycle
An end-to-end real-world evidence platform integrating patient, clinician, registry, and trial data to support drug development from preclinical research through post-approval.
Patient Registries
Build fit-for-purpose real-world data foundations
- Capture structured, longitudinal real-world data in rare and complex diseases
- Enable earlier patient identification and site feasibility assessment
- Create reusable data assets that support clinical, regulatory, and commercial needs
Natural History Studies
Understand disease progression and clinical variability
- Generate longitudinal evidence to characterize disease progression over time
- Inform endpoint selection, trial design, and sample size planning
- Support regulatory alignment in areas where randomized data are limited
External Comparator Arms (ECA)
Strengthen trials with regulatory-ready real-world controls
- Develop high-quality external control arms using standardized real-world data
- Reduce trial cost, duration, and patient burden
- Enhance regulatory submissions with robust real-world evidence
Phase IV & Post-Approval
Meet post-approval regulatory requirements and generate long-term real-world evidence
- Support long-term safety, pharmacovigilance, and regulatory follow-up obligations
- Design decentralized and hybrid long-term follow up (LTFU) studies that minimize patient and site burden
- Generate real-world effectiveness and outcome data over extended follow-up periods
Commercialization & Market Access
Support pricing, reimbursement, and post-marketing value evidence
- Generate real-world outcomes and utilization data to inform payer and HTA decisions
- Support pricing and reimbursement narratives with clinically grounded evidence
- Enable robust subgroup analyses to demonstrate value across real-world populations
An integrated real-world evidence ecosystem, under one roof
Regulatory-grade data, operational efficiency, and scientific depth delivered through a single, unified model.
Singular, extensible platform
Patient-centric data and re-contact
Uncommon access to rare & complex disease data
Cross-therapeutic expertise and global KOL network
Nimble, cost-efficient delivery model
Early-stage: Feasibility, registries, and natural history
Build a real-world evidence foundation that informs feasibility, trial design, and clinically meaningful endpoints in early development.
What the platform enables
Launch disease registries and natural history studies that collect longitudinal data on progression, outcomes, and treatment patterns in rare and complex conditions.
Conduct multi-stakeholder interviews and site landscape reviews to understand data availability, regulatory expectations, and operational feasibility across geographies.
Configure indication-specific data structures (clinical data, genomics, PROs, ‘omics, wearables) within a unified model to support protocol and informed consent development.
Use ambispective designs to refine retrospective data on unmet need while prospectively collecting richer quality-of-life and functional outcomes.
Case Study: End-to-End Evidence Generation in Dilated Cardiomyopathy (DCM)
From feasibility to natural history to an external comparator arm, delivered within a single, scalable platform.
Pulse conducted multi-stakeholder interviews and a global site landscape review to assess feasibility and inform study design. This phase identified clinically meaningful endpoints, available data sources, and key regulatory and scientific requirements, while evaluating the potential for decentralized patient recruitment in a rare disease setting.
Based on feasibility findings, the Pulse Platform was configured with a DCM-specific data model spanning clinical variables, genomics, and patient-reported outcomes (PROs). The platform design supported protocol and informed consent development, regulatory submissions, and efficient site onboarding.
Pulse enabled execution of a longitudinal natural history study across eight global sites, collecting standardized real-world data over an 18-month period with real-time analytics dashboards. These data are being used to generate a regulatory-ready external comparator arm to support future clinical development and submissions.
Build once. Scale across development. Generate regulatory-ready evidence without fragmentation.
Clinical development: External comparators and pivotal studies
Transform registries and natural history data into regulatory-ready external comparator arms.
What the platform enables
Evolve natural history registries into external control arms that inform trial design, endpoint selection, and comparative effectiveness in rare and complex diseases.
Generate regulatory-grade external comparator datasets to enhance FDA/EMA submissions, support label expansion, and fulfill post-marketing commitments.
Re-contact consented patients to collect additional data points, such as new PROs, labs, or imaging, overcoming typical data gaps in external control arm development.
Run synchronous studies within a single platform. Natural history, endpoint validation, external comparators, and safety or long-term follow-up studies as connected sub-studies.
External comparator arm development in a rare, progressive kidney disease
A scalable, real-world data-driven approach to external comparator arm development
Pulse Infoframe partnered with a patient advocacy organization to design and launch a decentralized, participant-driven registry for a rare, progressive genetic kidney disease. The registry was built to capture longitudinal real-world data across North America using a flexible design that combined retrospective clinical history with prospective follow-up.
Data collection leveraged standardized electronic Patient-Reported Outcomes (ePROs) supported by source documentation, including medical records, laboratory reports, audiology assessments, and genetic testing results. This approach enabled consistent capture of disease characteristics, progression markers, treatment history, and medication information across a geographically dispersed population, while minimizing burden on both patients and clinical sites.
From inception, the registry was designed as a reusable real-world data asset, supporting natural history research, peer-reviewed publications, and future regulatory-grade evidence generation.
As enrollment reached a robust and representative threshold, Pulse released a second-phase registry module designed to capture additional retrospective data directly from participants. This phase focused on efficiently maximizing the depth and breadth of longitudinal patient-reported data while maintaining data quality and regulatory rigor.
Participants completed structured retrospective surveys on a range of critical lab values, supplemented by secure upload of laboratory reports. Pulse implemented source data verification workflows to validate patient-reported information and align historical data with clinical records.
This phase significantly increased data completeness and longitudinal depth, enabling rapid expansion of analyzable patient histories without increasing site burden. The enhanced dataset strengthened the registry’s readiness for downstream comparative analyses and positioned it for use in external comparator arm development.
Building on the established registry infrastructure, Pulse partnered with a pharmaceutical sponsor to construct a propensity score–matched external comparator arm to support a single-arm Phase 2 clinical study. A suitable comparator cohort was defined directly from the existing registry based on sponsor and protocol-aligned eligibility criteria, including baseline disease severity, longitudinal outcome availability, treatment history, and genetic characteristics.
Pulse led data curation and extraction to generate a balanced external control cohort, enabling comparative evaluation of key efficacy endpoints over time. The resulting analyses were designed to support regulatory interactions, including inclusion in an end-of-Phase 2 briefing package, while preserving flexibility for future follow-up and expanded evidence generation.
Because the comparator arm was built within the same platform and registry, the sponsor avoided standing up new systems, reduced timelines, and maintained continuity between natural history research and clinical development.
Phase IV and post-approval: Safety, LTFU, and post-marketing requirements
Extend registries into regulatory-ready long-term safety and real-world effectiveness studies.
What the platform enables
Extend existing registries into long-term safety and pharmacovigilance programs, capturing outcomes over years in real-world clinical practice.
Design decentralized and hybrid LTFU studies that minimize clinic visits and leverage digital tools for remote clinical and lab data capture.
Re-contact and roll patients who complete interventional trials into LTFU or safety studies within the same platform, preserving data continuity.
Add new endpoints, questionnaires, or sub-studies over time using flexible consent models and a multi-use registry architecture.
Case Study: Long-Term Follow Up
FDA-accepted decentralized LTFU in an ultra-rare disease
This prospective observational study used the Pulse Platform (healthie) to support long-term follow-up (LTFU) and real-world data collection for pediatric patients receiving olipudase alfa for Acid Sphingomyelinase Deficiency (ASMD), addressing a U.S. Food and Drug Administration request for extended post-approval evidence generation.
- A multicenter, open-label, observational study enrolling pediatric patients under 2 years of age with ASMD, a rare lysosomal genetic disorder characterized by progressive sphingomyelin accumulation and multi-system manifestations.
- Designed for a total follow-up duration of five years, the study aimed to characterize long-term safety and immunogenicity of olipudase alfa in routine clinical practice and explore the relationship between anti-drug antibodies and safety outcomes.
- Data collection was integrated into usual care settings, including clinical and laboratory results at defined intervals (e.g., each infusion during dose escalation, quarterly up to 24 months, and again at 36 months), enabling rich real-world evidence capture without requiring patients to transfer to specialized research sites.
- The study implemented a decentralized recruitment model facilitated through the Pulse Platform, allowing caregivers and clinicians to enroll through site-based or online pathways, complete eConsent, and contribute longitudinal data with reduced burden.
- Pulse’s platform centralized eligibility, enrollment, clinical, and laboratory information, supporting streamlined data entry directly from local treating physicians and caregivers while mimicking routine care and minimizing unnecessary visits.
- This hybrid approach reduced geographic barriers and accelerated enrollment, allowing participants to remain under usual clinical management while contributing high-quality follow-up data to the observational study
- The single digital platform eliminated the need to spin up separate systems for site activation, data capture, and follow-up, dramatically lowering operational overhead and improving data consistency.
- Remote clinical data and pre-specified lab collection reduced patient burden and improved retention, while still delivering regulatory-relevant safety and outcome evidence over multiple years.
- By leveraging a decentralized design and hybrid enrollment process, the study collected real-world insights in a rare pediatric population where conventional long-term follow-up studies are exceptionally challenging.
View the full ASMD poster presented at the WORLD Symposium
Commercialization and market access: Pricing & reimbursement
Generate real-world evidence to support market access decisions and post-marketing requirements.
What the Platform Enables
Generate real-world outcomes data that contextualize clinical trial results and demonstrate the impact of therapies in routine practice.
Provide evidence to support pricing and reimbursement discussions, including unmet need, treatment patterns, and durability of benefit in defined populations.
Harmonize data and disease models across multiple sites and conditions, enabling consistent analytics and credible cross-site comparisons.
Build large cohorts and well-powered subgroups (e.g., by mutation, stage, or demographic factors) to refine value propositions and inform payer decision-making.
Case study: POTENT Study
EGFR-mutated Non-small cell lung cancer pricing and reimbursement support
Pulse supported the POTENT study, a retrospective, longitudinal real-world analysis of patients with resected stage IB–IIIA EGFR-mutated non-small cell lung cancer across multiple Canadian cancer centers. Using registry-based real-world data, the study evaluated mutation prevalence, treatment patterns, and survival outcomes in routine clinical practice.
Despite receiving standard-of-care surgery and adjuvant chemotherapy, patients demonstrated suboptimal disease-free survival and high recurrence risk, highlighting a significant unmet need in a large early-stage population. These real-world findings provided critical context alongside clinical trial data and reinforced the limitations of existing treatment approaches.
The Pulse Platform enabled aggregation of data from multi-site registries using a uniform disease and data model, ensuring consistency, quality, and regulatory-grade curation across sites. This infrastructure supported robust sub-analyses by:
- EGFR mutation subtype (common and uncommon mutations)
- Disease stage (IB vs II vs IIIA)
- Demographic and clinical characteristics, including under-represented populations
By supporting deep, mutation-specific and population-level analyses within a single harmonized dataset, the platform generated evidence that more closely reflects real-world clinical complexity than traditional trial populations alone.
Findings from the POTENT study have been used to inform treatment decision-making and reimbursement discussions by demonstrating real-world outcomes that mirror or contextualize trial control arms. The evidence highlighted persistent recurrence risk and distant metastases despite chemotherapy, reinforcing the need for improved adjuvant treatment options.
Because the registry infrastructure remains in place, the same data model can continue to support post-marketing commitments, long-term follow-up, and future effectiveness or safety analyses, without the need to build new systems or studies from scratch.
