About QuAD3 Platform
Leveraging Our QuAD³ Platform for Clinical Development and Novel Drug Discovery
Our proprietary QuAD³ platform, powered by our AI and ML capabilities, allows us to extract deep phenotypic and genomic data that defines novel biological insights from our patient cohorts. We plan to apply our QuAD3 platform across a range of biologically relevant queries to provide us with additional context around the role the adaptive stress response and innate and adaptive immunity play in treatment resistance, cancer relapse and metastasis. We believe that such insights will, in turn, inform our ongoing efforts in adaptive stress target discovery, patient enrichment, and clinical development of our innovative therapeutic programs.
Applying Our QuAD³ Platform to Strengthen Our Pipeline
The Importance of Integrating Both Molecular and Clinical Data Sources
We believe it is critical to integrate multi-omic data sets to inform our understanding of the role of adaptive stress in cancer progression.
Despite the complexity of multi-omics data, our QuAD3 platform allows us to integrate and deconvolute genomic and multi-omic data sets, which has allowed us to develop a preliminary 30 gene stress signature, which was supported which was supported by our in vivo signal cell RNA sequencing, or RNA seq, data.
Differentiated Computational Tools to Develop a Deep Understanding of the Drivers of Disease
Our QuAD3 platform integrates multidisciplinary inputs to generate insights to guide our clinical development. Our platform takes a statistics-based ensemble-AI approach to help determine causality and improve replicability of findings. This innovative computational platform uses multiple AI/ML algorithms to incorporate different data types, cluster data without losing information, generate novel insights, and tie them back to existing literature. We believe this approach will allow us to refine our understanding of the complexity that underscores adaptive stress in cancer.
Our Key Capabilities and Strategies
Biomarker DiscoveryBiomarker Discovery
Algorithms utilized to allow us to better project patient response to our therapeutic candidates
qML Computing StrategiesqML Computing Strategies
Machine learning strategies capable of superior performance on smaller, Phase 2 clinical trial-sized datasets
Ensemble AI ApproachEnsemble AI Approach
Multiple algorithms applied in sequence which is an approach that is intended to improve performance and ensure replicability of findings
