life sciences & healthcare
Creating the therapies of tomorrow requires safe data collaborations today
Federated data science and AI help biopharma, researchers and healthcare providers develop and validate new treatments and dramatically reduce the time they take to reach patients.
use cases
Take your project from code to clinic
with federated AI and data science
CLINICAL trials
Federated data science and AI for clinical research
Today’s clinical trials involve more moving parts and data than ever before. Use federated data science and AI to cut through complexity at every stage of the trial lifecycle.
patient pre-screening
Boost patient enrolment rates with privacy-preserving AI
Send algorithms and AI models to imaging and EMR data within trial sites. Accelerate recruitment while reducing screen fail rates.
biomarker development & validation
Validate the next generation of digital endpoints
Develop and evaluate the performance of digital biomarkers against real-world datasets which weren’t part of the training data.
patient stratification
Make the promise of precision medicine a reality
Move away from one-size-fits-all patient selection and match patients to treatments based on their individual characteristics.
real-world data & evidence
Accelerate and de-risk the entire trial lifecycle
Tap into real-world data at its source in order to enable true evidence-based decision making and research breakthroughs.
post-market surveillance
Monitor drug safety with full data safety
Improve pharmacovigilance by getting the insights you need and nothing more, directly from source-of-truth healthcare data.
operational research
Improve system efficiency with federated analytics
Collect aggregated insights from your fragmented data systems to drive operational improvements. No centralisation required.
use case
Accelerating clinical research with federated patient identification
88% reduction in costs for patient pre-screening in retinal disease trials with federated AI
Deploying deep-learning AI models on data directly within hospital systems helped identify ~100x more eligible patients than would normally be found via the current system of manual image analyses and health record searches.
Frequently asked questions
Can Bitfount access my data?
No, Bitfount’s zero-trust architecture ensures Bitfount never receives data or analysis results. Analysis results are transferred between data custodians and data scientists end-to-end encrypted using encryption keys held by each party and not accessible to Bitfount. Read more here.
What will my Information Governance team think of this?
Information Governance and Legal teams love Bitfount since it removes the need for complex Data Sharing Agreements (DSA) and Material Transfer Agreements (MTA), and massively simplifies Data Protection Impact Assessments (DPIA). Bitfount is also fully GDPR, HIPAA and ISO27001 compliant. Visit our online Trust Centre here.
Do I need to be able to code?
No. Our desktop application has been designed to be operated without requiring any coding knowledge. This includes connecting datasets, joining projects, running tasks and accessing analysis results. Data scientists and algorithm developers can choose to interact with Bitfount via our python SDK.
Are there any hardware requirements?
There aren’t any specific requirements, however AI analysis at scale can be compute-intensive and will run more efficiently, especially for image analysis, if you have access to a machine (physical or virtual) with a GPU. Suitable devices include any Apple silicon model, or a Windows or Linux machine with an Nvidia GPU. Not sure if you have the right setup? Reach out to us at support@bitfount.com for guidance.
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