The Architecture of Discovery
OncoFi operates on a simple, high-leverage philosophy: computational agility must directly translate into clinical impact. Our engine is evaluated against three core metrics of success.
The Discovery Metric
If the engine surfaces a single biomedically sound protocol—identifying a novel multi-modal synergy viable for in vivo testing—the platform succeeds. It acts as an untiring hypothesis engine, unlocking treatment pathways that manual literature reviews might miss.
The Mitigation Metric
If the architecture identifies a critical biological conflict in silico before a clinical trial begins, the platform succeeds. By serving as an early-stage risk detection firewall, it prevents the misallocation of crucial time, capital, and most importantly, patient safety.
The Acceleration Metric
By systematically cross-referencing vast ontologies of biomarkers, conditioning regimens, and viral vectors in seconds, the platform compresses months of conceptual design. It transforms raw research capital into actionable structural execution.
Precision Parameter Control
Before the logic engine synthesizes a protocol, researchers define the exact physical and toxicological boundaries of the clinical environment.
Massive Scalability
Dynamically orchestrates multi-modal therapeutic cascades across 44 distinct oncological targets in real-time, allowing for rapid cross-indication hypothesis generation.
Hardware-Aware Engineering
Enforces strict real-world physical constraints—such as viral vector packaging limits for CAR-T constructs—to rigorously model in vivo biological feasibility and structural limitations.
Modular Toxicity Gating
Flexibly toggles severe systemic interventions like SBRT and targeted immunomodulators to match host fitness, enabling advanced "chemo-free" trajectory modeling.
Dynamic Biomarker Integration
Following baseline parameter selection, researchers can optionally introduce specific physiological and molecular biopsy data to constrain the algorithm to a localized, real-world context.
Comprehensive Deep-Phenotyping
Ingests highly granular patient biometrics, hematological baselines (ALC/ANC), TNM staging, and deep molecular biopsy data—including specific tumor antigens and viral receptor densities.
Biomarker-Anchored RAG Integration
Continuously maps the patient’s exact molecular fingerprint against our Retrieval-Augmented Generation (RAG) architecture to extract only the most highly relevant, phenotypically matched clinical trials and literature.
Targeted Vector Matching
Algorithmically scores biological payloads (oncolytic viruses, anaerobic bacteria, vaccines) by directly cross-referencing the patient's available viral receptors and antigen targets, proactively eliminating low-probability agents.
Pervasive Algorithmic Logic
This multi-dimensional profile is not a static filter; it dynamically dictates biological synergies, strict safety gating, and the precise chronological sequencing at every single step of protocol creation.
Algorithmic Payload Scoring & Selection
Translating molecular phenotypes into a ranked hierarchy of synergistic biological vectors for precise TME deconstruction.
Multi-Dimensional Scoring Matrix
Algorithmically evaluates and ranks biological agents (oncolytic viruses, anaerobic bacteria, vaccines) by calculating granular sub-scores for cellular Entry, Replication viability, Immune activation, and physical Stromal barriers.
Proactive Toxicity Profiling
Instantly surfaces organ-specific safety alerts and physiological contraindications (e.g., systemic sepsis risk, bone marrow suppression) to prevent the selection of lethal or overlapping toxicities.
Mechanistic Target Matching
Highlights precise mechanistic synergies—such as targeting hypoxic cores or exploiting specific receptor densities (e.g., HIF1A, CD46)—ensuring the chosen payload perfectly matches the tumor's vulnerabilities.
Spatial "Anvil & Hammer" Synergy
Strategically limits primary biological payload selection to a dual-agent architecture. This enforces a highly calculated, spatially distributed attack—such as pairing an oncolytic virus with an anaerobic bacteria—designed to simultaneously dismantle the oxygenated tumor perimeter while colonizing the hypoxic core.
Dynamic AI/RAG Architecture & Clinical Grounding
Driving protocol generation through precise metadata filtering and real-time synthesis of over 30,000 clinical trials.
Precision Biomarker RAG Routing
Cross-references the patient's exact molecular fingerprint and selected biological payloads against a vector database of >30,000 clinical studies. Strict metadata filtering ensures the engine only synthesizes highly relevant, evidence-backed intelligence.
Categorical Protocol Optimization
Automatically structures retrieved clinical data into targeted therapeutic domains—such as Priming & Oncolytic Optimization, Trial Safety & Toxicity, and Genetic Mutations—ensuring every chronological step of the protocol is scientifically anchored.
Dynamic Output Modality
Programmable evidence thresholds dictate the engine's output. Restricting queries to Phase I–III trials generates highly translational protocols (ideal for in-vivo murine validation), while enabling in-vitro/ex-vivo data shifts the engine into an advanced "discovery mode" for novel hypothesis generation.
Seamless Proprietary Scalability
Architected for infinite data integration. While currently powered by open-access literature, ingesting proprietary, "behind-the-wall" Big Pharma trial data will instantly and exponentially multiply the platform's predictive power and commercial asset value.
Chronological Orchestration & Pharmacokinetic Gating
Translating complex polypharmacy into a precise, mathematically day-by-day execution blueprint.
Algorithmic Temporal Sequencing
Generates a highly precise, day-by-day clinical roadmap—orchestrating everything from Day -30 metabolic pre-conditioning through Day +90 systemic maintenance.
Mandatory Biological Washouts
Automatically calculates drug half-lives to enforce strict "Clinical Stabilization Gaps" (e.g., 48-hour empty spaces), ensuring highly cytotoxic conditioning agents are fully cleared before delicate CAR-T cells are infused.
Integrated Safety Brakes
Schedules precise "Antibiotic Brakes" (e.g., Ceftriaxone) to halt bacterial/viral replication at the exact moment of maximum tumor colonization, actively preventing fulminant sepsis and capillary leak syndrome.
Temporal Conflict Resolution
Intelligently separates conflicting mechanisms by shifting aggressive immunomodulators (e.g., CD47 blockade) strictly into the post-infusion maintenance phase, preventing catastrophic overlapping toxicities like Macrophage Activation Syndrome (MAS).
Proactive Microbiome Restitution
Anticipates the collateral damage of antibiotic and chemotherapeutic interventions by hardcoding targeted tissue recovery and microbiome restoration phases directly into the treatment runway.
Predictive Clinical Safety Gating
Translating theoretical timelines into safety gates with hard clinical stops and algorithmic rescue branches.
Phase-Specific Risk Anticipation
Automatically predicts severe temporal toxicities and overlapping adverse events (e.g., bacterial sepsis colliding with deep lymphodepletion) at every critical chronological phase transition.
Hard Clinical "Proceed" Criteria
Eliminates guesswork by defining uncompromising, quantifiable biometric thresholds—such as exact Mean Arterial Pressure (MAP) targets, strict clearance gaps, and absolute negative blood cultures—that must be met before advancing.
Algorithmic Rescue Branches
Moves beyond simple warnings by generating immediate, step-by-step medical contingencies. If a safety gate fails, the system provides precise alternative pathways, ranging from specific antibiotic escalations to the activation of extrinsic biological safety brakes.
High-Dimensional Protocol Design
The Combinatorial Hypothesis Matrix
The engine generates billions of testable biological hypotheses by calculating complex interactions across customizable patient biometrics, tumor phenotypes, and advanced therapeutic modalities.
Patient Biometrics
- 44 specific tumor phenotypes.
- Precise spatial tumor locations.
- Unique biopsy and receptor data profiles.
Biological Primers
- 30+ Viruses, Bacteria, and Vaccines.
- Configurable single or dual-agent combinations.
- Strict chemo-free protocol toggles.
Cellular Therapy
- CAR-T integration with 2 to 7 genetic modifications.
- Configurable delivery vectors (e.g., in vivo LNP).
- Chemo-based vs. biologic (Alemtuzumab, ATG) lymphodepletion.
Adjuvants
- Enable/Disable targeted SBRT consideration.
- Toggle immunomodulators and define maximum combination limits.