Precision therapies engineered for the next generation of cancer care
A sophisticated platform of algorithms where inputting specific biomarkers and target tumors delivers fully personalized oncological solutions for each unique cancer.
Nanomedicine
Smart nanoparticles engineered to seek and destroy tumor cells with precision.
AI Discovery
Deep learning models uncover hidden biomarkers and novel therapeutic targets.
Synthetic Biology
We program RNA therapies like software, customized for each tumor.
From Startup to Institute: A Scalable Vision for Oncology
We transitioned from conventional programming to transcriptomic and synthetic biology, focusing on spatial-temporal omics and AI pipelines to engineer next-gen oncological interventions.
Our Mission
Oncorithms operates as an Institute because the scope of our mission exceeds the limits of any single startup. We designed a structure capable of engineering multiple oncological solutions in parallel—independent in execution, unified in purpose.
Our starting point was creating an intelligent oncological immunotherapy framework. But we soon realized this mission required unprecedented, specific, and highly precise biomarkers. This led us to create a second pillar, dedicated exclusively to the discovery and validation of innovative therapeutic targets.
Precision Targeting
Precision biomarker engineering to enable personalized, tumor-specific therapies.
AI-Driven Discovery
AI models designed to discover, simulate and validate novel oncological safety layers.
Rapid Innovation
Synthetic biology tools engineered for rapid prototyping of next-gen RNA therapeutics.
This integrated architecture allows us to operate multiple decentralized labs simultaneously, accelerating the development, validation, and patenting of advanced oncological technologies.
A Unified Architecture of Cancer Innovation
Rooted in our core Oncorithms framework, we operate through three independent yet tightly integrated divisions, each focused on a critical layer of oncological transformation.
Molecular safety layers for RNA therapies, engineered to prevent off-target activation and ensure tumor-exclusive expression.
AI pipelines designed to decode single-cell data, identify novel biomarkers, and engineer precision-driven therapeutic logic.
Development of next-gen therapies, including programmable chimeric virotherapies and AI-designed immunologic treatments, activated using only tumor-specific data.
Our Core Technologies
Neural Framework for Biological Modeling
We integrate neural networks and biochemical simulation to model real-time celular behavior. Our framework transforms high-dimensional omics data into dynamic models that simulate intracelular pathways with precision.
Tumor-Driven Therapeutic Design
We engineer a new generation of cancer therapies, including chimeric oncolytic virotherapies and immunologic treatments, triggered solely by tumor-specific inputs.
Precision Oncology: What Comes Next
Our innovation pipeline spans from precision biomarker discovery to our ultimate goal: reversing malignant phenotypes at the molecular level.
Novel Biomarkers
Discovery of new specific biomarkers for different cancer types
Tumor Neoantigens
Personalized immunotherapy through the identification and validation of tumor-specific neoantigens.
circRNA Immunotherapy
Circular RNA-based therapies designed to modulate immune responses with tumor-level specificity.
saRNA Immunomodulation
Tumor immunomodulation therapies using self-amplifying RNA
Chimeric Oncolytic Virotherapy
Programmable synthetic viruses engineered to selectively target and destroy malignant cells.
Tumor Stroma Attack
Therapies targeting tumor microenvironment and extracelular matrix
Selective Molecular Activator
Smart systems that activate therapeutic RNAs only within cancerous microenvironments.
Therapeutic Bioequivalents
Engineered alternatives to costly treatments, preserving clinical efficacy while expanding accessibility.
Modular Innovation Units
Each startup in our ecosystem operates with a distinct focus: security, intelligence, virotherapy, or therapeutic design. Working in synergy to accelerate the next generation of oncological treatments.
We engineer molecular safety layers that block RNA translation until the therapy reaches tumor tissue, eliminating off-target expression risks.
We design tailored synthetic virotherapies by matching cancer types to custom viral agents equipped with programmable immunological payloads.
We are developing therapeutic platforms that combine immunomodulation and precision safety mechanisms to activate only within malignant environments.
Our platform leverages AI to identify actionable coding sequences and tumor-specific signatures for targeted therapy design.
Our long-term initiative focused on engineering total oncological reversal through integrated therapeutic ecosystems.
A computational hub for simulating, optimizing, and validating precision therapies using neural networks, genetic algorithms, and GRN inference.
Computational Oncological Engineering Institute
Oncorithms was founded not as another biotech startup, but as a computational institute, built to converge AI, synthetic biology, and molecular engineering into one unified offensive against cancer.
Neural Pipeline: 9 Architectures for Oncological Intelligence
Our precision AI framework orchestrates 9 distinct neural network architectures to decode single-cell data and accelerate biomarker discovery at an unprecedented scale.
Perceptron / MLP
Supervised classification of cancerous celular phenotypes
Our precision AI framework orchestrates 9 distinct neural network architectures to decode single-cell data and accelerate biomarker discovery at an unprecedented scale.
CNNs
Spatial transcriptomics pattern recognition
Processes spatial gene expression maps like tissue images, detecting localized and hierarchical patterns in situ.
RNNs / LSTMs
Temporal modeling of gene expression dynamics
Captures sequential changes in expression within differentiating or evolving cancer cell populations.
Transformers
Multi-level gene and cell interaction modeling
Model interactions between genes and cells using attention mechanisms, especially useful for multimodal data.Applies attention mechanisms to unravel complex multimodal relationships across gene regulatory layers and cell populations.
Autoencoders / VAEs
Latent encoding and dimensionality compression
Learns compact gene expression representations for data visualization, noise reduction, and downstream inference.
GANs
Synthetic cancer data generation
Generates realistic yet artificial gene expression profiles for data augmentation, hypothesis testing, and bias correction.
SOMs
2D clustering and topological mapping
Projects high-dimensional expression data into self-organizing maps, revealing molecular similarities across cell groups.
Graph Neural Networks
Cell-cell communication inference
Models celular interactions and regulatory signals through graph-based structures capturing tumor microenvironment dynamics.
Deep Learning Multimodal
Proteo-genomic-metabolomic integration
Combines diverse omics layers to uncover hidden signatures of cancer biology and emergent therapeutic vulnerabilities.
9-Step AI Framework for Biomarker Discovery
Our 9-layer AI framework decodes single-cell omics data with precision, uncovering hidden molecular patterns, novel biomarkers, and actionable insights that drive personalized oncology.
Integrative Proteo-Metabolomic Discover
We integrate proteomic and metabolomic layers using advanced methods like MOFA+, integrative variational autoencoders, and network-based inference, enabling the identification of biomarkers that define unique oncogenic states and therapeutic vulnerabilities.