Our Partners and Collaborations Validating Our Platform

Systems Architecture

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Global Genes gained systems-level insights into hidden gene interconnections across rare diseases, inspiring unified, mechanism-driven research and advocacy strategies.

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Stanford’s Sakamoto Lab in collaboration with CytoSolve® created the first full-scale systems architecture of AML, revealing hidden pathway interconnections and novel therapeutic targets.

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Forsyth Institute in collaboration with CytoSolve® created the first full-scale systems architecture of Periodontitis, revealing hidden pathway interconnections and novel oral microbiome therapeutic targets.

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MIT’s Kamm Lab in collaboration with CytoSolve® built the first systems architecture of ALS neuromuscular junction microenvironment, revealing hidden mechanobiological drivers.

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Applying CytoSolve®’s supervised bioinformatics workflow, the team structures lupus biology across tissues, cells, and interactions for hypothesis-driven research faster translation.

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CytoSolve® and Wapiti Labs built a systems architecture linking Elk Velvet Antler bioactives to seventeen biological functions and health mechanisms.

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CytoSolve and UHN curated 20,231 papers to 5,243 studies, extracting human OA interactions into a navigable, evidence-traceable architecture.

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CytoSolve modeled contact activation and bradykinin pathways to predict Alnylam siRNA knockdown-response relationships, guiding combination strategies for HAE more effectively.

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CytoSolve integrated validated gut motility pathway models to explain Actazin™ and Livaux™ synergy across inflammation, mucus, and bulking mechanisms.

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CytoSolve and UofT’s Keating Lab validated an integrated MSC niche model, improving mechanistic understanding and translational optimization pathways.

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CytoSolve® modeled liver detoxification subsystems to predict D-glucaric acid effects on oxidative stress, β-glucuronidase, apoptosis, and deconjugation biomarkers.

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CytoSolve converted NMO pathway blueprints into integrated in silico models, enabling cross-cell signaling analysis and cytokine prediction for therapeutic prioritization.

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CytoSolve integrated validated pathway models to predict cinnamon bark oil synergy across GLUT-4, inflammation, and α-glucosidase mechanisms in silico.

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CytoSolve integrated validated pain-pathway models to quantify apigenin–hesperidin synergy, generating patent-ready evidence across inflammation, nociception, and oxidative stress.

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CytoSolve built an integrated lung-congestion model to quantify ClearLungs® multi-botanical synergy across inflammation, mucus regulation, and airway relaxation.

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CytoSolve integrated validated skin-pathway models to quantify SeaMeal™ ingredient synergy, linking improved coat appearance to barrier synthesis and oxidative reduction.

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CytoSolve modeled Redoxx® and Bug Check® to substantiate multi-ingredient mechanisms, confirming systems-level synergy, safety alignment, and NASC-ready validation.

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CytoSolve® screened a multi-ingredient equine joint formula in silico, quantifying synergy across inflammation, oxidative stress, degeneration, and regeneration pathways.

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CytoSolve® enabled peer-validated, systems-level modeling of pericyte biology, revealing predictive neurovascular mechanisms and accelerating translational insights into neurodegenerative diseases.

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CytoSolve® enabled a structured systems architecture to organize cannabis molecular complexity, supporting precision chemotype design and translational, patient-focused medical applications.

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CytoSolve® modeled transplant immunomodulation to predict green tea bioactives’ effects, identifying EGCG as a key driver of tolerance.

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CytoSolve® converted NMO pathway blueprints into integrated in silico models, enabling cross-cell signaling analysis and cytokine prediction for therapeutic prioritization.

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CytoSolve enabled in silico discovery of an FDA-approved multi-drug combination for pancreatic cancer through systems-level modeling of cancer signaling pathways.

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A modular systems architecture using CytoSolve® enabled scalable integration of endothelial signaling pathways to accurately model shear-stress-induced nitric oxide production.

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CytoSolve partnered with Harvard Stem Cell Institute to model spinal muscular atrophy mechanisms in silico, enabling systems-level insight into motor neuron degeneration.

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CytoSolve supported Nu Skin by computationally evaluating individual and combined ingredient efficacy for joint pain, muscle soreness, and headache symptoms.

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CytoSolve® partnered with Nanosynergy Worldwide to computationally analyze, test, and optimize Vitamin D’s molecular effects on immune function.

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CytoSolve created the first mechanistic molecular digital twin of an ALS patient to simulate disease progression and therapeutic interventions virtually.

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CytoSolve® integrated six molecular relaxation pathways to quantify individual and combined ingredient effects, accelerating mechanistic insight and formulation optimization strategies.

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CytoSolve® enabled a systems architecture–driven, in silico workflow to design and optimize three plant-based formulations targeting testosterone metabolism.

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CytoSolve® built a mechanistic systems architecture to model low-grade chronic inflammation and predict synergistic phytonutrient effects validated by clinical observations.

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A modular systems architecture using CytoSolve® enabled scalable integration of endothelial signaling pathways to accurately model shear-stress-induced nitric oxide production.

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CytoSolve’s systems architecture enabled quantitative, mechanistic modeling of endothelial nitric oxide regulation under shear stress by integrating multiple interacting molecular pathways.

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CytoSolve® delivered a modular systems architecture enabling Pfizer to mechanistically model interferon-driven autoimmune biology across multiple cell types.

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CytoSolve® delivered a modular systems architecture enabling rapid mechanistic discovery of an USFDA-approved drug combination for pancreatic cancer intervention.

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CytoSolve® enabled a systems architecture–driven, in silico evaluation of caffeine and L-arginine interactions to support cardiovascular risk screening for military use contexts.