Sponsors & CRO

De-risk site feasibility and patient recruitment

Bitfount unlocks insights from imaging and EHR data to identify sites with patients during study feasibility and accelerate enrolment while reducing screen failures by finding the most eligible patients for the trial.

Use cases

Patient pre-screening

Empower sites to boost enrolment and reduce screen fails

AI-driven analyses custom-developed to match your trials’ inclusion/exclusion criteria to find eligible patients based on EHR- and image-based biomarkers. Increase site yield and accelerate recruitment while reducing site burden.

Site selection

Accelerate trial setup and improve patient diversity

Make faster, more informed site selection decisions based on objective data about the patient populations accessible via each site. No more relying on over-optimistic estimates of patient availability and diversity.

Feasibility studies

Augment your trial modelling with real-world data

Inform feasibility studies by collecting data on patient demographics, disease prevalence, current treatments and more by partnering with trial sites to share insights from their data, without requiring them to share any of it.

Protocol design

Optimise trial protocols with federated data science

Safely simulate and iterate different sets of inclusion/exclusion criterial to maximise the trial’s chances of success and minimise the need for time-consuming protocol amendments.

Trial monitoring

Move towards adaptive trial design by closing the feedback loop in real time

Get real-time insights directly from trial sites in order to inform decision-making and iron out bottlenecks. From image quality assessments to protocol adherence reports.

Post-market surveillance

Go to market with federated pharmacovigilance

Automatically monitor drug- and device safety, identify adverse events, and find opportunities for improvement by tapping into real-time source-of-truth imaging and EHR data using federated data science.

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.

Clinical trial pre-screening

Define study criteria and model selection

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Model deployment via Bitfount

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Model runs on site data

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Sites receive results

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Some of the AI-enabled sites using Bitfount

Stadtspital Zürich

Queen’s University Belfast

Moorfields Eye Hospital

Bay Area Retina Associates

RCMG

Berner Augenklinik

RVAF

Retina Macula Institute

University of Utah

The Retina Clinic London

Universität Regensburg

Erie Retina Research

Ganglion Orvosi Központ

Cascade Medical Research Inst.

Verum Research LLC

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.

Still have questions?

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