Pushing the boundaries of Oncology with Chimeric and Synthetic Virotherapy
Powered by ONCORITHMSIntelligent framework for chimeric and synthetic RNA-based oncolytic virotherapy, capable of automatically generating complete and personalized therapies
Cutting-Edge Technology
Artificial Intelligence
State-of-the-art AI integrated with advanced viral engineering to design modified viruses
Tumor Selectivity
Viruses that selectively infect tumor cells with multiple layers of safety
Integrated Database
Vast database composed of the union of various public databases and scientific portals
Oncolytic Virotherapy
What is Oncolytic Virotherapy?
Oncolytic virotherapy is an innovative therapeutic approach that uses modified viruses to selectively infect and destroy cancer cells while preserving healthy cells.
Our oncolytic viruses infect tumor cells and replicate intracellularly without causing cell lysis, avoiding any risk of contaminating the body, and instead induce tumor cell death from within.
Mechanism of Action
Oncolytic viruses infect tumor cells, replicate, and cause cell lysis, releasing tumor antigens that stimulate immune response
Personalized Oncolytic Virotherapy
Complete Personalization
Our platform automatically generates complete and personalized therapies based on the specific type of cancer informed, using advanced machine learning algorithms.
Specific Therapeutic Payloads
Immunomodulators, immune checkpoint inhibitors, CD8+ cell ligands, NK and pro-apoptotic proteins selected based on tumor cell biochemical metabolism
Customized Viral Chassis
Replication and immune escape profiles optimized for different tumor microenvironments
Temporal Modulation
Control of action timing (lysis versus programmed apoptosis), adjusting infection dynamics, replication and immune activation
Revolutionary Innovation
Sequential Dual Virotherapy
With the desire to further increase the efficiency of our Virotherapy, we developed an innovative technique using two oncolytic viruses in sequence.
This approach was inspired by the revolutionary work of a virologist who implemented this technique in self-experimentation to treat her own cancer in 2024, obtaining exceptional results.
Dual Therapy Advantages:
- Efficiency superior to 80%
- Synergistic action between viruses
- Reduction of tumor resistance
Optimized Sequence
Two oncolytic viruses working in sequence to maximize therapeutic efficacy and overcome individual limitations
Advanced Molecular Safety
RNA Inhibitor
RNA reading inhibitor in healthy cells, ensuring absolute tumor selectivity
Genetic Logic
Conditional genetic logic (AND/OR gates) for precise control of viral activation
Safety Mechanisms
Multiple layers of molecular safety to ensure safe and effective treatment
Our Comprehensive Framework
Design and Viral Engineering Focus
Chimeric Viral Design Module
- • Intuitive interface for combining genetic sequences from different viruses
- • Library of characterized viral genetic "building blocks"
- • In silico prediction tools for genetic stability and replication capacity
- • Integration of synthetic elements like genetic switches
- • Multi-virus sequence incorporation for enhanced potency
Tropism and Selectivity Optimization
- • Design module for receptor-specific targeting
- • Options to "deactivate" tropism for normal cells
- • Modeling tools for virus-cell interaction prediction
- • Superexpressed receptor targeting in tumor cells
Synthetic Therapeutic Payload Integration
- • Gene insertion for therapeutic protein expression (immunomodulators, cytokines, monoclonal antibodies)
- • Design module for gene editing system delivery (CRISPR-Cas9)
- • Integration with synthetic peptide libraries with antitumor activity
Evaluation and Prediction Focus
In Silico Virus-Tumor Interaction Simulation
- • Modeling of infection and viral replication dynamics
- • Prediction of immune response induced by chimeric virus
- • Virtual efficacy assessment in different cancer types
Safety Prediction Module
- • Viral sequence analysis for recombination potential
- • Algorithms for off-target effect probability prediction
- • Integration with viral toxicity databases
Production and Scalability Optimization
Suggestions for virus design that are more efficient for large-scale production in cell culture systems.
Personalization and Clinical Application Focus
Patient Data Integration Interface
- • Upload of genomic, transcriptomic and immunological patient data
- • "Tailored" chimeric virus recommendations based on patient's molecular profile
Combinatorial Therapy Selection Module
- • Data-based suggestions for synergistic therapies
- • Immunotherapies and targeted therapies compatibility analysis
Monitoring and Results Analysis Tools
- • Interface for tracking patient response to treatment
- • Statistical analysis of results for model refinement
- • Imaging data and viral/tumor biomarkers integration
Additional Features
Updated Knowledge Base
Integration with scientific and clinical databases on virotherapy
Collaborative Interface
Enabling researchers and clinicians to work together
Regulatory Compliance
Incorporating relevant regulatory guidelines and information
Interactive Visualization
Clear presentation of viral design data and simulations
Our Viral Options Portfolio
List of our viral options that have great affinity with various types of cancer:
Adenovirus (AdVs)
Herpes Simplex Virus (HSV)
Vaccinia Virus (VV)
Reovirus (ReoV)
Newcastle Disease Virus (NDV)
Measles Virus (MeV)
Vesicular Stomatitis Virus (VSV)
Viral Armament Optimization
In addition to virus-specific modifications, our framework also features various strategies that are aligned with the immunological barriers present in the specific tumor, making the virotherapy response as specialized and efficient as possible:
Abolition of Immunosuppression
Tumors frequently escape immune responses via checkpoint ligand expression (PD-L1), recruitment of Tregs and MDSCs, and secretion of immunosuppressive cytokines (TGF-β, IL-10). Engineering tactics include:
Viral Evasion Gene Deletion
- • ICP47 (HSV)
- • B18R (VV)
Local Checkpoint Inhibitor Expression
- • anti-PD-1/PD-L1, anti-CTLA-4
- • Costimulatory Ligands (CD40L, 4-1BBL)
Cytokine Diversification
- • DC Maturation
- • Th1 Polarization
- • APC Enhancement IFN-α/β
- • Chemokines (CCL5, CXCL10)
APC Function Enhancement
- • FLT3L
- • CD40L TNF Family Transmembrane Protein
- • GM-CSF
Effector T Cell Response Enhancement
- • Costimulatory Molecules
- • Local Checkpoint Blockers
- • Targeted T Cell Recruitment (BiTEs)
Delivery Improvements
Capsid Engineering and Receptor Redirection
Fiber modifications (AdV): Inserting RGD motifs or scFvs targeting tumor antigens (e.g., HER2) in the fiber knob allows infection of cells with low CAR expression, using alternative receptors (integrins or specific antigens).
Directed Evolution of OVs
Through multiple rounds of controlled error replication, recombination and selection in tumor cell cultures, viral variants with optimized tumor tropism, enhanced replication kinetics and immune evasion profiles are generated.
Protease-Activatable Vectors (PAVs)
Incorporating protease-dependent "locks" (e.g., tetra-aspartic acid motifs flanked by MMP-2/9 sensitive sites) in AAV capsids blocks infectivity until highly active TME proteases release the virus locally.
Personalized Neoantigen Vaccination Integration
Loading OVs with patient-specific neoantigens (identified by tumor exome sequencing) enables personalized intratumoral vaccination, promoting T responses directed to the tumor's unique mutational profile.
Nanocarrier-Mediated Systemic Delivery
Encapsulation of OVs in liposomes, polymeric nanoparticles or extracellular vesicles coated with tumor-homing peptides hides the virus from neutralizing antibodies, increases circulation half-life and favors accumulation in metastases via active targeting (e.g., RGD-modified liposomes).
Challenges and Considerations
Despite advances, several obstacles remain in the clinical translation of enhanced OVs:
Antiviral Neutralization
Problem:
Pre-existing neutralizing antibodies (NAbs) against viral capsids can eliminate systemically administered OVs.
Our Solution:
Pseudotyping with rare serotypes, detargeting via MREs or nanoparticle encapsulation. We possess a vast database on pseudotyping correlated to each cancer we work with, currently 15.
Tumor Heterogeneity and Receptor Expression
Problem:
Variations in receptor expression (CAR, CD46, integrins) between patient tumors reduce OV infectivity.
Our Solution:
Development of multi-ligand or bispecific capsids aims to cover heterogeneous receptor profiles in tumors.