Solutions
Life science
Accelerate adoption of new therapies and advance patient care
Leverage real-world data, powerful analytics, and the Truveta Language Model to support therapy development and access and improve patient outcomes.
How we can help
Safety
Fulfill post-market regulatory requirements and assess long-term product safety more efficiently with real-time data.
- Meet regulatory evidence standards faster and at lower cost by eliminating the need for expensive and long-running registries
- Quickly assess the validity of potential safety signals with real-time data
- Conduct studies assessing the long-term, real-world safety of different treatments with access to complete medical records, including notes and images
Assessing the safety of novel interventions
Comparative bleeding incidence 7 days post-procedure for pulmonary embolism interventions
HEOR
Evaluate clinical- and cost-effectiveness to differentiate products using real-world data from health systems representative of the US.
- Assess the clinical- and cost-effectiveness of therapies to inform access and reimbursement decisions
- Generate scientific evidence on comparative effectiveness and long-term outcomes to connect the right patients to the right therapies
- Analyze real-world treatment pathways and healthcare resource utilization patterns to inform access and engagement programs
Comparing real-world treatment outcomes
Hazard of cardiovascular events associated with SGLT2i vs metformin
Clinical trials
Validate trial design and supplement trial data with real-world arms.
- Build and analyze precise populations from representative data for 120M+ patients
- De-risk clinical programs with dynamic, real-time analyticsÂ
- Generate evidence for real-world control arms using regulatory-grade data
Testing I/E criteria to de-risk clinical programs
Sample heart failure population with inclusion/exclusion criteria applied
AI model training
- Identify patient subgroups with distinct treatment responses or disease trajectories to improve therapy targeting and effectivene
- Predict the likelihood of adverse events, disease progression, hospital readmission, or device failure to optimize patient outcomes
- Discover opportunities for label expansion or product enhancement by uncovering unmet needs or new therapeutic applications
Exploring the association between heart failure and medication use
Population clustering to facilitate drug discovery
Market access
Monitor and ensure patient access to therapies using real-time EHR data.Â
- Assess product utilization and market share trends
- Generate compelling evidence of real-world effectiveness and economic value to inform coverage and reimbursement decisions
- Monitor and remediate the impact of potential supply chain shortagesÂ
Assessing the impact of drug shortages
Rate of amphetamine/dextroamphetamine prescription fills per eligible population, stratified by age
How we can help
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
Safety
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
HEOR
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
Clinical trials
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
AI model training
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
Market access
Safety
Fulfill post-market regulatory requirements and assess long-term product safety more efficiently with real-time data.
Quickly assess the validity of potential safety signals with real-time data
Conduct studies assessing the long-term, real-world safety of different treatments with access to complete medical records data, including notes and images
Assessing the safety of novel interventions
![Comparative-bleeding-incidence-7-days-post-procedure-crop Comparison table from a scientific publication using Truveta Data to illustrate bleeding events associated with two medical devices for treating pulmonary embolism: the USCDT (Unspecified Superiority Clot Dissolver) and MT (Standard Mechanical Thrombectomy). The data is presented for two distinct time periods—2009 to 2023 (primary analysis) and 2018 to 2023 (contemporary analysis). Bleeding events are categorized into six types, with results presented as counts and percentages. Statistical significance is indicated by p-values, providing insights into the safety profiles of the two devices over time.](/wp-content/uploads/2024/05/Comparative-bleeding-incidence-7-days-post-procedure-crop-1.jpg)
Comparative bleeding incidence 7 days post-procedure for pulmonary embolism interventions
HEOR
Evaluate clinical- and cost-effectiveness to differentiate products using real-world data from health systems representative of the US.
Generate scientific evidence on comparative effectiveness and long-term outcomes to connect the right patients to the right therapies
Assess the clinical- and cost-effectiveness of therapies to inform access and reimbursement decisions
Analyze real-world treatment pathways and healthcare resource utilization patterns to inform access and engagement programs
Comparing real-world treatment outcomes
![ISPOR-SGLT2-Chart-crop October 2023 Respiratory Viruses hospitalizations trend report](/wp-content/uploads/2024/05/ISPOR-SGLT2-Chart-crop.jpg)
Hazard of cardiovascular events associated with SGLT2i vs metformin
Clinical trials
Validate trial design and supplement trial data with real-world arms.
Build and analyze precise populations from representative data for 120M+ patients
Generate evidence for real-world control arms using regulatory-grade data
Testing I/E criteria to de-risk clinical programs
![Sample-HF-population-with-I-E-criteria-applied Diagram detailing inclusion and exclusion criteria applied to a heart failure population in Truveta Data. The criteria encompass medication use, length of stay, outpatient encounters, laboratory results, comorbidities, and device use. The visual representation offers a comprehensive overview of the selection criteria, aiding in understanding the parameters used to define the study population.](/wp-content/uploads/2023/12/Sample-HF-population-with-I-E-criteria-applied.jpg)
Sample heart failure population with inclusion/exclusion criteria applied
AI model training
Train AI models for discovery and product enhancement with complete and representative EHR data.
![Population-clustering-based-on-heart-failure-rates-crop Population clustering visualization featuring two panes in Truveta Studio. The first pane explores the absence or presence of Type 2 diabetes, with distinct clusters or patterns representing different groups within the population. The second pane depicts heart failure rates, offering insights into how these rates vary or cluster within the analyzed population. The visualization provides a comprehensive overview of the relationships between Type 2 diabetes and heart failure prevalence.](/wp-content/uploads/2024/05/Population-clustering-based-on-heart-failure-rates-crop.jpg)
Population clustering to facilitate drug discovery
Market access
Monitor and ensure patient access to therapies using real-time EHR data.
Assess product utilization and market share trends
Generate compelling evidence of real-world effectiveness and economic value to inform coverage and reimbursement decisions
Monitor and remediate the impact of potential supply chain shortages
Assessing the impact of drug shortages
![fill_rate_under18_allagegroups-crop Truveta Research explores the potential impact of Adderall shortage using EHR data to explore trends in prescription fills for patients with ADHD](/wp-content/uploads/2024/05/fill_rate_under18_allagegroups-crop-1.jpg)
Rate of amphetamine/dextroamphetamine prescription fills per eligible population, stratified by age
Why Truveta
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
Complete EHR data
Truveta offers complete, timely, and clean EHR data linked with SDOH, mortality, and claims data for more than 120 million patients representing the full diversity of the US.
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)
Regulatory-grade, audit ready
![](/wp-content/uploads/2023/09/Truveta-Frond-Leaves-Small.png)