Data exploration & insights
+ Qualify data
+ Biomarker discovery
+ Covariate adjustments
= Streamlined data integration & analysis
✓ Automatically assess and detect tissue lesions, MRI abnormalities, and PET SUVr.
✓ Uncover novel biomarkers and evaluate their predictive value through pattern detection in complex, heterogeneous datasets.
✓ Analyze the influence of different biomarkers on clinical outcomes during trial planning.
✓ Integrate open and proprietary datasets within your company's infrastructure, significantly cutting annual personnel and costs by automating 70% of data engineering efforts.
Predictive models
+ Responder identification
+ Casual AI in clinical trial design
= Accelerated drug development
✓ Validate responder patients and predict the occurrence and severity of treatment-related adverse events.
✓ Leverage causal AI to uncover the underlying mechanisms of treatment effects.
✓ Shorten trials and improve accuracy of endpoints selection.
Neuroimaging
+ Neuroimaging expertise
+ Automated segmentation
+ Surrogate biomarkers
= Enhanced clinical outcomes
✓ Leverage our extensive expertise in NDDs and neuroimaging, including proficiency in DICOM standards.
✓ Automate brain tissue segmentation and lesion quantification to optimize diagnosis and patient selection.
✓ Extract surrogate imaging biomarkers to improve the probability of success of your trials.
✓ Accelerate diagnosis and treatment outcomes while efficiently managing complex imaging data.
Feasibility studies
+ Site integration
+ Site selection & enrichment
= Improved trial management
✓ Automate trial feasibility assessments across multiple clinical sites and registries, saving significant time and reducing personnel effort.
✓ Enhance site selection and streamline the enrollment process.
✓ Accelerate trial initiation, reduce operational costs, and improve overall efficiency.
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Cohort enrichment
+ Complex disease analysis
+ Progression prediction & randomization
= Reduce trial size
✓ Use advanced analytics for accurate disease classification and prediction models to determine the right patient cohort.
✓ Identify slow- and fast-progressing patients to guide pre-treatment randomization, ensuring balanced treatment and control trial arms.
✓ Enhance cohort homogeneity and increase treatment effect size. Even a reduction in clinical trial participants by 5-10%, could potentially save millions in trial costs.
Screening – PET tool
+ Multimodal selection
+ PET prediction
= Patient screening effectiveness
✓ Implement AI models to estimate patient suitability for a clinical trial based on vital signs, clinical scores, and PET imaging results.
✓ Select patients based on predicted positive PET results, providing significant cost savings during clinical trials and future commercialization.
✓ Reduce screening costs and accelerate clinical trial enrollment by quickly excluding unsuitable candidates, minimizing the need for extensive exams.
Companion diagnostic
+ Target patients
+ Mitigation strategies
= Expedite market entry & improved patient care
✓ Streamline patient access to treatment with developed companion diagnostics (i.e. SaMD) based on new or established digital biomarkers.
✓ Implement strategies to reduce the incidence of adverse events, enhancing patient safety.
✓ Accelerate market access while saving costs with improved safety monitoring.
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AI-driven drug repurposing
+ Novel drug-disease interactions
+ Efficacy predictions
+ Identification of the right patients
= Maximized market impact with de-risked, fast-tracked repurposed therapies
✓ Optimize drug repurposing and trial precision by identifying novel drug-disease interactions, predicting therapeutic effects for specific indications, and enhancing patient selection criteria, streamlining development with integrated data assets.
✓ Benefit from accelerated market entry, reducing development time to 3–12 years and costs by over 80% through drug repurposing, leveraging existing safety and preclinical data.
✓ Expand patient access by targeting neglected or rare diseases, using AI-driven designs to enhance trial management and bring treatments to underserved populations.
Case studies
Demonstrating real-world impact in healthcare and life sciences, thecase studies showcase the transformative potential of data and AI within the AICURA Platform.
Multimodal AI system for Alzheimer's & Frontotemporal Dementia (FTD) advance diagnosis
+ Precision disease staging
+ Cognitive decline predictions
+ Differential diagnoses
= Outperform traditional diagnostic methods
In this case study, you'll discover:
✓ How multimodal AI leverages MRI, cognitive assessments, and biomarkers to achieve superior diagnostic precision.
✓ TelDem’s capabilities in distinguishing Alzheimer’s from diverse Frontotemporal Dementia subtypes.
✓ Breakthroughs in predicting the progression of mild cognitive impairment (MCI) to Alzheimer’s.
✓ Clinical insights into AI's role in streamlining clinical trials and research.
✓ Enhanced decision-making with TelDem’s transparent, interpretable AI insights for clinical application.
