The world’s largest ex‑US real‑world data network.
Access diverse, longitudinal, multimodal real-world data for regulatory, epidemiology, HEOR and AI work. Size the patient universe in seconds, then analyze it inside a Trusted Research Environment.
Access is provided through partner networks. Availability varies by partner, country, modality and project.
Your evidence is only as global as your data.
Regulators, payers and AI models increasingly expect evidence that reflects the patients who will actually use a therapy. Most real-world data sources can’t provide it.
Evidence built on US and EU data
Claims databases and European registries miss most of the world’s patients, and the ancestries, diseases and care pathways that come with them.
Feasibility that takes weeks
Before a protocol is written, teams wait on vendor counts, data dictionaries and back-and-forth to learn whether the population even exists.
Data locked inside countries
The most diverse longitudinal records sit in hospitals bound by data-sovereignty rules, out of reach of models that require data to move.
A network and a platform, on one screen.
A federated network of hospital partners across 20+ countries, harmonized into one platform. You scope in the Scoping Engine, work in a Trusted Research Environment and take aggregate results home. Nexa sits alongside when you need to reach clinicians and patients.
Where the records come from.
The majority of records come from outside the US and Europe, across Latin America, Africa, the Middle East and South and Southeast Asia.
Representative network countries shown. Availability varies by partner, country and modality. Partner and client names are never published.
Three components are built and waiting for approved numbers.
(bar chart, nine countries)
(matrix: records · imaging · labs · notes · genomics)
(line, records and sources by year)
Each patient’s whole journey, not one claim at a time.
Longitudinal, episodic and multimodal records, harmonized so a query written once runs across every country in the network.
Modalities
Structured records, imaging, laboratory results, clinical notes and genomics, linked at the patient level inside the boundary.
Longitudinality
Episodic patient journeys over time: diagnoses, encounters, prescriptions, procedures and outcomes, in sequence.
Harmonization
Every source is mapped to one common data model, OMOP CDM, so analyses are portable across countries.
Code systems
Local source codes are mapped to standard vocabularies such as SNOMED CT, LOINC and RxNorm, with source values retained.
Data-availability flags
Each dataset is flagged by modality and field, so you can see what is there before you commit.
Six ways teams put Syntium to work.
Post-authorization evidence from the populations you’re launching into.
Support PASS, PAES, open-label extension follow-up and REMS evaluation with diverse, longitudinal data from outside the US and Europe.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- Post-authorization safety studies (PASS)
- Post-authorization efficacy studies (PAES)
- Open-label extension (OLE) follow-up
- REMS evaluation
Multi-country epidemiology, sized before you commit.
Incidence, prevalence and treatment-pattern studies across countries, with feasibility run in the Scoping Engine in seconds rather than weeks.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- Incidence and prevalence
- Treatment patterns and care pathways
- Country and site feasibility
Combine existing records with new data collection.
Build registries and hybrid primary/secondary designs on Syntium data, using Nexa for recruitment and patient-reported outcomes where the design needs new data.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- Disease and product registries
- Hybrid primary/secondary designs
- PRO collection through Nexa
Local evidence for markets where it has been hard to find.
Burden-of-illness, resource-use and outcomes evidence to support pricing, reimbursement and access in fast-growing markets.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- Burden of illness
- Healthcare resource utilization
- Local evidence for HTA submissions
Train and validate models that work for everyone.
Ethnically diverse, multimodal data for training, fine-tuning and external validation, with all work done inside the Trusted Research Environment.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- Model training and fine-tuning
- External validation on diverse populations
- Bias and performance testing across populations
Real-world evidence for new populations and indications.
Generate real-world evidence on new populations, age groups, indications and geographies to support label expansion.
One approved, blinded proof point for this use case, in the form “[client type] sized a [condition] cohort across [N] countries in [N] days” or “[client type] delivered a [study type] to [regulator] using Syntium data from [N] countries”.
- New populations and age groups
- Comparative effectiveness
- Evidence for new geographies
Know your universe before you commit.
A self-serve patient-universe sizer across the network. Pick datasets, set criteria, count in seconds, see distributions, then save and export. Feasibility becomes a workflow you live in, not a one-off request.
Scoping Engine demo video coming soon
Book a live walkthrough in the meantime.
From question to evidence in five steps.
One-off projects or ongoing access. Governance review is built into every project.
Scope
Size the patient universe in the Scoping Engine.
Feasibility
Confirm data availability, fields and quality with our real-world evidence team.
Study design
Agree protocol, variables and outputs, with governance review built in.
Access via TRE
Your analysts work in a per-project Trusted Research Environment.
Delivery
Approved aggregate outputs are released to you, once or on an ongoing basis.
Work inside the boundary. Take the answers home.
Each approved project gets its own secure analytic workspace, next to the data and inside the jurisdiction.
- Per-user, per-project. Every workspace is scoped to one approved project.
- Role-based access. People see only what their role allows.
- A full analytic stack. R, Python, SAS and machine-learning tooling.
- Aggregate outputs only. Results leave after review. Patient-level data never does.
Built to stand up to your compliance team.
De-identified at source
Records are de-identified in-country, before they are used for any research.
GDPR and local law
Processing is aligned to GDPR and to each partner country’s own data-protection law.
Consent
Consent and linkage permissions are respected under each jurisdiction’s rules.
Data stays in jurisdiction
Hosted in Syntium Cloud in-country. Analysis comes to the data, not the other way around.
No re-identification
Re-identification is prohibited, and only aggregate outputs leave the boundary.
Governance review
Every project is reviewed before access is granted and before outputs are released.
Scope the cohort in Syntium. Engage it through Nexa.
Find and size the cohort
Scope patient universes across the network in the Scoping Engine, then analyze them inside a Trusted Research Environment.
Reach the people behind it
Recruit into studies, capture patient-reported outcomes and run adherence programs through Nexa’s point-of-care network of clinicians and patients.
Not another claims database.
How Syntium differs from the real-world data sources most teams use today.
| US-centric claims data | Single-country registries | Data brokers | Syntium | |
|---|---|---|---|---|
| Population coverage | Mostly US insured populations | One country | Varies, often US and EU | 20+ countries, majority outside the US and Europe |
| Clinical depth | Billing codes, limited clinical detail | Deep within one disease area | Varies by source | Longitudinal and multimodal: records, imaging, labs, notes, genomics |
| Harmonization | Vendor-specific formats | Registry-specific | Mixed formats | One common data model (OMOP) |
| Feasibility | Vendor request cycle | Application per registry | Negotiation per dataset | Self-serve counts in the Scoping Engine |
| Data sovereignty | Data held by the vendor | Stays in-country | Often transferred | Stays in jurisdiction, federated |
| Delivery | Extracts or vendor platform | Application-based access | Extracts | Per-project TRE, aggregate outputs only |
| Value to source populations | Rarely shared | Varies | Rarely shared | Benefit-sharing built in |
Comparison reflects typical characteristics of each category of data source, not any specific provider.
Names stay private
We never publish partner or client names. References are available under NDA as part of a briefing.
Delivered work, on request
Details of studies, feasibility assessments and regulatory work supported are shared during a briefing.
Replaces the “Track record” card above when the figures are approved.
Questions customers ask first.
What is the access model?
How is pricing shaped?
How long does it take?
What leaves the boundary?
Who owns the outputs?
How does Nexa fit in?
Tell us what you’re trying to answer.
Share your therapeutic area, countries and study type. Our real-world evidence team will come back with an initial view of coverage and next steps.