PathAI - Real-World Data

RWD (1)-1

Real-world data (RWD) is a valuable resource that enhances our understanding of healthcare outcomes and supports the development of more effective and personalized treatments. RWD refers to health-related information collected from various sources outside the context of traditional clinical trials. It includes data derived from routine patient care and health interactions, providing insights into patient journeys, treatment patterns, and outcomes in real-world populations

Real-world data is collected through a variety of sources, but generally contains information that captures the complete patient journey from disease diagnosis, biomarker testing, treatment selection, and outcomes. Examples of RWD sources include:

Electronic Health Records (EHRs)
Claims and Billing Data
Patient Registries
Wearable Devices and Health Apps
Patient-Reported Outcomes (PROs)
Molecular Biomarker Tests

Patient Diversity
Captures data from diverse and different patient populations, including those not typically included in clinical trials

Speed & Cost-Effectiveness:
Using readily available data helps reduce the time and cost associated with clinical trial operations and data collection

Real-World Insights:
Provides a continuous, longitudinal view into patient journeys, treatment patterns, adverse events, and outcomes

Clinical Trial Operations:
Enhancing clinical trial protocol development, study feasibility, and population-level eligibility assessment

Regulatory Decision-Making:
Supporting new drug approvals or post-approval requirements through continuous data collection and surveillance

Health Economics and Outcomes Research:
Generate evidence and inform market access decisions by analyzing real-world clinical and cost-effectiveness

Advances in digital pathology and machine learning are now enabling researchers to use routine histopathology samples to obtain a single-cell, spatially-resolved view of tissue structures and cell populations.
PathAI’s products transform unstructured digital images into human interpretable features (HIFs) allowing for more detailed and actionable insights from histopathology data.
Integrate quantitative pathology data with other RWD to understand disease intricacies at molecular, cellular, histological, and anatomical levels

PathAI has built a network of industry-leading RWD partners, including Aster Insights and ConcertAI , allowing you to access a comprehensive range of curated real-world datasets. These datasets include clinical, molecular, and AI-derived quantitative pathology data, enabling multi-modal analyses across the drug development lifecycle. These datasets are available across oncology indications, including lung, breast, colorectal, melanoma, gastric, kidney, pancreatic, prostate, lymphoma, ovarian, bladder, head & neck, and liver cancers to address your specific use cases.

PathAI also licenses the PathExplore data generated from H&E WSIs from The Cancer Genome Atlas (TCGA), allowing researchers to analyze quantitative pathology features alongside clinical and molecular data from TCGA.

Reach out to us

Reach out to us to enrich your RWD with AI-powered pathology. Our solutions transform raw WSIs into standardized and structured tissue and cell insights, enhancing your ability to derive meaningful insights and accelerate discoveries in translational research and clinical development.

Reach out to us

PathAI offers academic researchers access to PathExplore's HIFs associated with publicly available H&E WSI from The Cancer Genome Atlas (TCGA). This program allows researchers to access PathExplore HIFs via our digital pathology platform AISight® to use alongside existing clinical and molecular data from TCGA.

This data is free to academic researchers, and available via license for non-academic partners. To learn more and apply to the PathExplore data access program, please contact pathexplore.hifs@pathai.com. Non-academic researchers may additionally reach out to bd@pathai.com

Learn more about the program