Our Projects

Translating Research into Real-World Impact

Our comprehensive portfolio of projects represents the practical applications of our research, focusing on solving real problems in cancer detection, diagnosis, and treatment through innovative AI solutions.

Featured Projects

AI & Early Detection

CancerVision AI

An advanced deep learning system designed to enhance early cancer detection through the analysis of medical images. Currently focused on lung, breast, and colorectal cancer, CancerVision AI combines multi-modal imaging data with clinical information to identify subtle patterns that human radiologists might miss.

93% accuracy in preliminary testing on historical image datasets, with significantly higher sensitivity for early-stage lesions

Clinical validation underway at three major cancer centers, with initial results expected Q4 2023

Partners: National University Hospital, RadiTech AI Labs, Global Cancer Data Initiative

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CancerVision AI platform visualization
GenomiX Platform interface and visualization
Genomic Analysis

GenomiX Platform

A comprehensive AI-powered platform that analyzes multi-omics data (genomic, transcriptomic, proteomic, and epigenomic) to identify potential biomarkers, therapeutic targets, and personalized treatment strategies for cancer. GenomiX integrates advanced graph neural networks with natural language processing to mine both structured biological data and scientific literature.

12 novel biomarkers identified in preliminary research, with 3 now entering validation studies

Beta version deployed at 5 research institutions with expanding access planned for 2023

Published research: 4 peer-reviewed papers in leading journals, including Nature Methods

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Drug Discovery

MoleculeForge AI

A revolutionary AI-driven drug discovery platform that accelerates the identification and optimization of novel cancer therapeutics. Using advanced generative models, reinforcement learning, and physics-based simulations, MoleculeForge AI explores vast chemical spaces to design compounds with optimal efficacy, selectivity, and safety profiles.

100x acceleration in lead compound identification compared to traditional high-throughput screening approaches

3 candidate compounds currently advancing to preclinical testing for novel cancer targets

Partners: PharmaTech Innovations, Synthetic Biology Institute, Global Oncology Alliance

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MoleculeForge AI molecular modeling visualization

Key Initiatives

Beyond our flagship projects, we're driving forward several key initiatives that apply our AI expertise to critical challenges in cancer research and treatment.

TumorSphere 3D

An advanced computational platform for modeling the complex 3D architecture of tumors and their microenvironment. TumorSphere 3D integrates spatial transcriptomics, advanced imaging, and AI to create detailed digital replicas of patient tumors for studying cancer biology and testing therapeutic interventions.

Active developmentDetails

TrialMatch AI

A comprehensive platform that matches cancer patients with appropriate clinical trials based on their molecular profile, medical history, geographic location, and other factors. Using natural language processing and advanced patient similarity metrics, TrialMatch AI helps overcome the critical bottleneck of patient recruitment in oncology trials.

Beta testingDetails

ResponseTrack

An AI system that integrates multimodal data (imaging, circulating biomarkers, digital health metrics) to track treatment response in real-time. ResponseTrack enables early detection of resistance, allowing clinicians to adapt therapy strategies promptly and potentially improving patient outcomes.

Clinical validationDetails

NeoEpitope Explorer

A specialized AI platform for identifying and prioritizing cancer-specific neoantigens for personalized immunotherapy development. Integrating genomic, proteomic, and immunological data, NeoEpitope Explorer helps design more effective cancer vaccines and cell therapies tailored to individual patients.

Early researchDetails

MultiOmics Integrator

A sophisticated computational framework that seamlessly integrates diverse molecular data types (genomics, transcriptomics, proteomics, metabolomics) to provide a comprehensive view of cancer biology. The platform enables researchers to discover novel biomarkers, pathways, and therapeutic targets through unified data analysis.

Research releaseDetails

OncologyKnowledge AI

An AI-powered system that continuously analyzes scientific literature, clinical trial reports, and real-world data to identify emerging trends, promising research directions, and potential breakthrough areas in cancer research. The platform helps researchers stay at the cutting edge and identify new opportunities for innovation.

Active developmentDetails

Advanced Platform Initiatives

Ion Channel Drug Discovery Platform

Collaboration with Ontario Institute for Cancer Research

Our ML-powered platform analyzes gene expression profiles across thousands of tumor samples to identify ion channels critical for cancer cell survival. By integrating genomic data with functional experiments, we've identified approximately 30 ion channels as promising therapeutic targets, with a special focus on glioblastoma and other aggressive brain cancers.

Analysis of 9,000+ tumor samples across 33 cancer types

Experimental validation in human-derived cancer cell lines

Two lead compounds entering preclinical development

Learn about our approach

Accelerated Drug Discovery Compute Platform

High-Performance Computing Initiative

Inspired by the UChicago Medicine-Argonne collaboration, we've developed a specialized high-performance computing platform that dramatically accelerates cancer drug discovery. By combining quantum-inspired algorithms, machine learning, and cloud computing, we can screen millions of compounds against novel cancer targets in days rather than months.

100x faster virtual screening compared to traditional methods

Initial focus on ovarian and pancreatic cancers

Cloud-based architecture enables global research collaboration

Technical specifications

AI-Enhanced Radiotherapy Planning

Precision Radiation Oncology Initiative

Our system integrates AI with real-time MRI imaging to revolutionize radiation treatment planning and delivery. By continuously monitoring tumor position and surrounding healthy tissues during treatment, the platform enables dynamic adjustment of radiation beams, significantly improving targeting accuracy while reducing side effects.

Sub-millimeter targeting precision for moving tumors

25-35% reduction in radiation toxicity to healthy tissues

Compatible with existing linear accelerator hardware

Clinical implementation guidelines

Multimodal Treatment Decision Platform

Precision Oncology Initiative

Building on Artera's pioneering work in prostate cancer, we've developed a comprehensive AI platform that integrates clinical, genomic, imaging, and pathology data to personalize cancer treatment decisions across multiple tumor types. The system balances efficacy, toxicity, quality of life, and patient preferences to recommend optimal treatment strategies.

22% improvement in treatment outcomes in initial studies

Expanded from prostate to breast, lung, and colorectal cancers

Integration with electronic health record systems

Evidence-based validation studies

Emerging Projects

We're constantly exploring new applications of AI in cancer research. These pioneering projects represent our most innovative and forward-thinking endeavors as of March 2025.

Digital Patient Twins

Creating comprehensive computational models of individual cancer patients that can simulate responses to different treatment options and predict disease progression.

Radiomics-Guided Biopsies

Developing AI systems that guide precise tumor sampling based on imaging features, ensuring that biopsies capture the most informative regions of heterogeneous tumors.

Synthetic Biology Design

Using AI to design engineered cellular therapies and synthetic biological systems for targeted cancer treatment with minimal side effects.

Quantum Computing Applications

Exploring how quantum computing can accelerate complex simulations of protein folding and molecular interactions for cancer drug discovery.

Federated Learning Networks

Building secure, privacy-preserving systems that enable collaborative AI model training across institutions without sharing sensitive patient data.

Microbiome-Cancer Interactions

Investigating how the human microbiome influences cancer development and treatment response using advanced metagenomic analysis and AI.

Breakthrough 2025 Initiatives

DermaScan AI

Inspired by Chelsea and Westminster Hospital's Derm system, our mobile-based AI platform enables rapid, autonomous skin cancer diagnosis. Using standard smartphone hardware with a specialized lens attachment, clinicians can capture and analyze suspicious lesions within seconds, achieving a near-perfect accuracy rate in ruling out melanoma.

99.7% accuracy in clinical testingView collaboration opportunities

MammoInsight

Parallel to the NHS's landmark breast cancer diagnosis trial, we're developing an advanced mammography analysis platform that combines computer vision with clinical data integration. MammoInsight not only detects suspicious findings but also risk-stratifies patients and optimizes radiologists' workflows, potentially reducing diagnostic delays by up to 40%.

Validation cohort: 150,000 mammogramsLearn about our approach

ProstateCare Precision

Building on Artera's groundbreaking work, our multimodal AI platform integrates patient records, genomic profiles, pathology slides, and radiological images to develop truly personalized treatment plans for prostate cancer. The system balances the risks of overtreatment and undertreatment, potentially reducing unnecessary interventions by 27% while maintaining optimal oncological outcomes.

In validation at 3 major oncology centersPartnership details

TNBC Response Predictor

Similar to the AI-VISION initiative, our research focuses on discovering and validating biomarkers of chemotherapy response in triple-negative breast cancer. Using spatial transcriptomics and deep learning, we're creating a comprehensive atlas of TNBC tumor microenvironments to guide immunotherapy decisions and identify patients most likely to benefit from specific treatment regimens.

Analyzing 2,500+ tissue samplesResearch updates

NeuroTarget Discovery

Expanding on breakthrough research from the Ontario Institute for Cancer Research, we're using machine learning to explore ion channels as novel therapeutic targets in glioblastoma. Our platform has analyzed over 12,000 tumor samples to identify ion channels critical for cancer cell survival, with lead compounds now entering preclinical testing.

5 novel targets identifiedScientific publications

AdaptiveRT AI

Building on Dr. Waddington's pioneering work at the University of Sydney, our platform integrates AI with MRI-guided linear accelerators to enable truly adaptive radiotherapy. The system continuously monitors tumor position and nearby healthy tissues during treatment, automatically adjusting radiation delivery in real-time to maximize tumor coverage while minimizing toxicity.

30% reduction in treatment toxicityTechnical specifications

Partner With Us

We believe in the power of collaboration to accelerate progress in cancer research. Our projects thrive on partnerships with diverse organizations that share our vision of transforming cancer care through AI innovation.

Research Collaborations

Partner with us on cutting-edge research in AI for oncology, accessing our expertise and technologies

Technology Partnerships

Work with us to develop and scale innovative technologies that address critical challenges in cancer care

Clinical Validation

Collaborate on validating our AI approaches in clinical settings, bringing cutting-edge tools to patients

Explore Our Research Areas

Learn more about the foundational research behind our projects and initiatives.

View Research Areas