Expand your evidence ecosystem.

Evidence networks bring together data sources (e.g., groups of sites, providers, or other data contributors) to provide scalable access to patients, participating sites, and data to support research. Many evidence networks are therapeutic area specific, bringing deep expertise and data depth in a given disease area. Evidence networks accelerate contracting and study activation through master contracts and established processes that enable expedited study initiation. Beyond speed and efficiency, evidence networks improve delivery through data driven feasibility and by enabling data extraction from clinical records with data enrichment where needed to generate clinically rich, patient level datasets. In some TA networks (e.g., oncology), there is also access to biobanks and archival tissue, enabling tissue testing and linkage of tissue derived results to patient-level clinical data.

Evidence Platforms connect multiple real world data sources, such as hospital based clinical data, registries, and other routinely collected healthcare data, technologies, analytics, and expertise, to enable evidence generation across an ecosystem rather than relying on one database or a single study. They support the collection, harmonization, and analysis of data from diverse healthcare settings to answer clinical, regulatory, and commercialization questions that cannot be addressed with one data source alone.

Whilst Evidence Platforms typically comprise different types of data (for example Claims, EMR, Registries) in order to enable answers to a variety of research questions spanning evidence types, Evidence Networks are typically centred on a common characteristic and offer a single point of entry to a wide group of similar sources of data which can be scaled rapidly to the needs of a given study. As such, Evidence Networks can contribute to Evidence Platforms as one data type/ source amongst others.

Evidence Platforms are most appropriate when the research question requires broader coverage than a single dataset can provide. This includes studies involving multiple care settings, geographically diverse populations, rare or hard to find patients, or evidence needs that evolve over time.

Evidence Platforms can support regulatory and commercialization decisions by enabling access to representative, granular clinical data, combined with advanced analytics. This can help generate fit for purpose evidence to demonstrate safety, efficacy, and differentiation, while supporting more precise targeting of new medicines in an increasingly dynamic commercial and regulatory environment.

Evidence Platforms draw on real world data from hospitals, registries, healthcare providers, and other sources globally. Depending on the research objective, this can include claims, longitudinal prescription data, observational study data, patient reported outcomes, genomics, and other clinically relevant datasets.

Evidence Platforms are designed and configured at the local level to meet country , source , and institution specific data privacy and security requirements. The required data infrastructure is built upfront, ahead of evidence generation, to enable efficient execution of global or multi country studies. Data are refreshed and harmonised in line with agreed governance, supporting cross study insight generation while maintaining local control, security, and regulatory compliance.

Evidence platforms improve speed and efficiency by increasing access to existing real-world data, reducing reliance on standalone primary data collection, and leveraging pre-established master agreements with data sources for ongoing research use. Additionally, evidence platforms enable data-driven feasibility and identification of hard-to-find populations, reducing uncertainty and accelerating study start-up timelines.

Hybrid study designs that combine secondary data with targeted, site-based primary data collection can minimize data capture burden while still capturing the depth needed for complex clinical endpoints, overall improving execution efficiency.

Evidence platforms enable analysis of real-world data across multiple care settings, providing a more representative view of clinical practice, treatment patterns, and patient outcomes. This broader perspective allows for a deeper understanding of real-world treatment pathways, variation in clinical practice, and differences in outcomes across patient segments, providers, and care settings.

These insights support identification of unmet need by highlighting gaps in care, delays in diagnosis or treatment, and subpopulations with poorer outcomes. In turn, this informs more targeted study design, clearer evidence strategies, and stronger positioning in both regulatory and commercial contexts.