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Current challenges for treatment decision
🔗Silos
Isolated information with inefficiencies, and inconsistencies of decision making.
🔗Fragmented
Imcomplete, heterogeneous, missing data, with lack of unified view of patient disease
🔗Interoperability
Lack of standardized labels across systems and research
🔗Different modalities
Complex data integration and harmonization between different modalities
Our approach
Our approach
Multimodal Patient Data
Multimodal Patient Data
Patient data including multiple clinical modalities for a full heterogeneous view of patient trajectory
Access to up-to-date data
Access to up-to-date data
Access to retrospective and latest patient diagnosis at the single and large-population scale longitudinal data.
Harmonized Clinical Data
Harmonized Clinical Data
Cohesive, standardized patient records converted into harmonized and interoperable health data ecosystems.
Cancer Digital Twin's solutions
Cancer Digital Twin
Cancer Digital Twin
Provides an integrated platform that converts disparate clinical and molecular data into harmonized, standardized digital twins, empowering clinicians and researchers to simulate disease progression and optimize personalized treatment strategies.
Case studies
Glioblastoma
Glioblastoma
Our digital twin model, built from thousands of clinical and molecular features of glioblastoma patients, to predict treatment responses at both the individual and population levels.
Neuroblastoma
Neuroblastoma
Our glioblastoma digital twin uses advanced data from thousands of patients to predict treatment response, both individually and across populations.
Contact us
Contact us
Wanting to test our products? Fill out this form and our experts will reach out to demonstrate how digital twin technology can accelerate your programs, reduce costs, and deliver better outcomes for patients.
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