DISCOVERY FOR Clinical studies

ACCELERATING & OPTIMIZING clinicAL WORKFLOWS

Clinical Studies without Discovery

1
Start of Study
Trial candidates
screened
2
3
Images sent for review at Reading Centre
Patient
recruited
4
5
Monitoring Images sent to Reading Centre
Study
analysed
6
7
Reports finished
THIS CURRENT DATA TRANSFER PROCESS ADDS TIME FOR:
Recruitment
Reading
Reviewing
Transferring data

Clinical Studies with Discovery

Discovery transforms data workflows, enabling parallel workflows and centralizing data analysis to accelerate clinical study timelines

ONE PLATFORM FOR ALL TRIAL DATA
Secure & Global
Instant access for authorised users
Cost-effective (no need for vendor-specific software)
Full control of data for additional analysis
More flexibility in location of sites and stakeholders
Real-time Insight collection & understanding
Ensure data transparency & consistency
Simultaneous AI processing
Real time decision making
Full control of data for additional analysis
Ability to deploy automatic reading tools on the platform,       potentially reducing reading centre costs
Use case:
Accelerate Clinical Studies' Process
CHALLENGES

DELAYS & LOSS TO FOLLOW UP: Enrolling patients in a study may involve a third-party evaluation, increasing onboarding time and risking a potential loss to follow up between first visit and enrollment. Additionally, pivotal GO/NO GO decisions can be delayed due to the operational challenges of aggregating data from multiple sites.

A SIGNIFICANT INVESTMENT & RISK: Clinical studies are one of the largest expenses for pharma and life science companies and many risk failure due to suboptimal study design or an inadequate definition of patient subgroups.

SOLUTIONS:

With Discovery for Clinical Trials it is possible to:

- Centralize data collection: to increase visibility and monitoring throughout the study development and make real time decisions

- Evaluate in real time enrollment criteria and endpoints: to support patient enrollment with real time data analysis 

RESULTS:

MONITORING STUDY PROGRESS ANYWHERE AT ANYTIME 

SAME DAY PATIENT EVALUATION WORKFLOWS

DiscoverY is currently involved in:
RAZORBILL STUDY
STUDY OVERVIEW: observational, non-interventional, open-label study in nAMD. Up to 20 centers across 5 countries, 424 patients (clinicaltrials.gov)

SPONSOR: Novartis 

STUDY OBJECTIVES: 

1. Evaluate the influence of automated OCT image enrichment (using AI) on disease activity assessment in nAMD patients treated with anti-VEGF injections

2. Assess if RetinAI’s Discovery can optimize clinical workflows

DISCOVERY’S ROLE:

in phase I of the study → data collection
in phase II of the study → automatic OCT enrichment using RetinAI’s fluid and layer segmentation certified models
Learn More
BETTER STUDY
STUDY OVERVIEW: Phase IIa, multicenter study to evaluate ISTH0036, an antisense targeting mRNA of TGF-β and protein downregulation in DME and nAMD. Plan to enroll up to 50 patients.

SPONSOR: Isarna Therapeutics GmbH

STUDY OBJECTIVE: Evaluate the influence of automated OCT image enrichment (using AI) on disease activity assessment in nAMD patients treated with anti-VEGF injections

DISCOVERY’S ROLE: Provide a same day data evaluation workflow for enrollment by review of the clinical and imaging data between sites and reading center. RetinAI’s fluid and layer segmentation models are used to evaluate the primary endpoints (reduction of fluid and center macula thickness).
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CARDS STUDY
STUDY OVERVIEW: Validation of the LuxIA algorithm, an automated screening algorithm for Diabetic Retinopathy. Study conducted across multiple centers in Spain with a plan to enroll 960 subjects.

STUDY OBJECTIVE: Evaluate the statistical significance (sensitivity and specificity) of the LuxIA algorithm for screening Diabetic Retinopathy, compared to three, independent and blinded graders.

DISCOVERY’S ROLE: Platform was used for the data collection and data review phases. In the data collection phase, Discovery’s eCRFs were used to collect clinical patient data as well as multi-modality imaging data such as fundus images (used for analysis of the algorithm) and OCTs. During the review phase, the workflow deployed in Discovery, ensured graders were blinded to each other’s grading outcomes for robust, unbiased analysis.
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*Disclaimer

RetinAI Discovery® and the AI models are CE-Marked medical devices according to the Medical Devices Directive 93/42/EEC.
RetinAI Discovery® is a 510(k) FDA Cleared medical device in US.
RetinAI Discovery® and Retinai® are both trademarks of RetinAI Medical AG.

Discovery and AI Models are CE-Marked medical devices since April 2020 & December 2020 respectively.