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protoXell

Cell Response Discovery Software
Explore, Compare & Interpret
Perturbation Data across experiments,

without pipelines, infrastructure, complexity, or specialized expertise.

Showcases

The Power of Cell Response

Understanding Biology Through Perturbation

Chemical and genetic perturbations trigger measurable cellular responses that reveal biological pathways, mechanisms, and therapeutic opportunities. protoXell helps researchers explore these responses across experiments at scale.

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Cell Response Discovery

Understand how cells respond to genetic or chemical perturbations across conditions, models, and datasets, revealing patterns missed by single-study analysis.

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Mechanism of Action Clarity

Connect perturbation signatures to biological pathways and molecular mechanisms, moving from observation to understanding.

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Novel Therapeutic Identification

Uncovering unexpected biological connections to identify new therapeutic opportunities beyond hypothesis-driven approaches.

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Drug Repositioning

Identify existing compounds with signatures aligned to new disease indications, surfacing hidden opportunities in known molecules.

Challenges

But Understanding Perturbation Data is Still hard.

Advances in single-cell perturbation sequencing have created unprecedented visibility into cellular responses. Yet translating these signals into biological insight remains slow, fragmented, and resource-intensive. As a result, answering even simple biological questions can take weeks or months.

Data fragmented across experiments, modalities, and teams
Perturbation datasets spanning gene targets, compounds, and disease models are disconnected, limiting cross-study comparison and integrative analysis.
Infrastructure complexity
slows analysis
Large-scale perturbation data requires sophisticated, compute-intensive pipelines that are difficult to scale across cloud and HPC environments.
Interpreting results requires specialized computational expertise
Extracting insights requires coding skills and deep understanding of data structures, statistical models, and algorithms.
Connecting results to mechanisms and literature is time-consuming
Linking computational findings to known molecular pathways and prior studies requires extensive manual curation and domain expertise.

We Made It Easy

See how protoXell instantly unlocks a new level of discovery

Exploring perturbation data thoroughly can revolutionize your understanding of biology and advance therapy development.

Cell Response Discovery

Understand how cells respond to genetic or chemical perturbations across conditions, models, and datasets, revealing patterns missed by single-study analysis.

About the screenshot
protoXell excels at identifying molecular signatures of potential side effects by detecting sub-clinical cellular responses that traditional screening misses. By mapping a candidate drug’s impact at molecular resolution, the platform can flag when a compound mimics the transcriptomic or proteomic profile of known toxins or gene perturbations. For example, protoXell can identify shared disruptions in electron transfer and ion channels—similar to the pathway overlap observed between Saquinavir and Norepinephrine—which may signal risks of mitochondrial dysfunction or cardiotoxicity.

This predictive capability allows researchers to categorize a drug’s safety profile based on established biological precedents, enabling the proactive development of safety biomarkers and the refinement of chemical structures to bypass toxicities long before clinical trials begin.
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Cell Response Discovery

Mechanism of Action

Connect perturbation signatures to biological pathways and molecular mechanisms, moving from observation to understanding.

About the screenshot
The discovery of RREB1 downregulation via protoXell highlights the platform's precision in uncovering non-canonical mechanisms of action for AZD2858. While standard assays focus on the Wnt pathway, protoXell reveals that AZD2858 fundamentally rewires cellular identity by suppressing the Ras-responsive "stemness" architecture. Across diverse lines like PANC-1 and LoVo, the tool identified that lowering RREB1 levels effectively "grounds" aggressive cells, shifting them from a migratory state to a differentiated one.

By mapping these systemic changes, protoXell provides a high-resolution view of how a GSK-3 inhibitor can simultaneously drive bone growth and act as a potent anti-invasive agent, identifying critical vulnerabilities and cross-talk pathways that traditional research methods often overlook.
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Mechanism of Action

Novel Drug Target

Uncovering unexpected biological connections to identify new therapeutic opportunities beyond hypothesis-driven approaches.

About the screenshot
protoXell enhances traditional discovery workflows by bridging the gap between broad pathway shifts and gene-level precision. While standard GSEA can identify a general upregulation of cholesterol homeostasis in HEC1A cells treated with Berbamine, protoXell’s high-resolution mapping pinpoints the exact regulatory nodes involved. By integrating AI-assisted narration, the platform can automatically highlight key genes like PCSK9 or LDLR, providing immediate context on how a compound modulates lipid clearance versus synthesis.

This level of detail allows researchers to work backward from a pathway of interest to identify specific, druggable targets that drive the observed phenotype. In the context of endometrial cancer, these insights enable the discovery of new drug candidates or combination therapies designed to exploit specific metabolic vulnerabilities, transforming a high-level biological observation into a precise, actionable roadmap for drug development.
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Novel Drug Target

Drug Repositioning

Identify existing compounds with signatures aligned to new disease indications, surfacing hidden opportunities in known molecules.

About the screenshot
protoXell supports drug repurposing by identifying hidden similarities between compounds through their shared impact on biological pathways. Rather than relying solely on chemical structure, the platform analyzes high-resolution cellular responses to find overlaps between seemingly unrelated drug classes. For instance, discovering that the nucleoside analog Trifluridine produces a pathway signature similar to the mTOR inhibitor Everolimus suggests that it may have untapped therapeutic applicationsin growth-signaling disorders. By mapping these molecular-level convergences, protoXell helps researchers find new uses for "de-risked" drugs that have already passed safety trials.

This pathway-centered approach provides a data-driven way to expand a drug's indications, potentially shortening development timelines and offering a clearer understanding of how existing treatments might be applied to new disease contexts.
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Drug Repositioning

Core Capabilities

How protoXell Works

protoXell combines curated perturbation data, comparative analytics, AI-powered interpretation, and enterprise deployment flexibility into a unified scientific workflow.

Curated Perturbation Catalog
Easily explore large-scale, harmonized datasets across cell lines, tissues, and conditions—continuously updated and analysis-ready.

Enterprise deployments can extend the catalog to include proprietary data.
Purpose-built Comparative Analysis
Efficiently compare perturbation effects across experiments to uncover shared and distinct biological responses at the gene and pathway level.
AI-Powered Insight Interpretation
inXighter Interpreter, DataXight’s AI-powered capability, connects analytical results to underlying biological mechanisms and relevant scientific literature, accelerating hypothesis generation and validation.
Enterprise Integration & Deployment
Deploy protoXell across cloud, on-premise, or hybrid environments with a platform-agnostic architecture. Integrate proprietary data and existing systems as part of enterprise deployments.
Curated Perturbation CatalogCurated Perturbation Catalog
Purpose-built Comparative AnalysisPurpose-built Comparative Analysis
AI-Powered Insight InterpretationAI-Powered Insight Interpretation
Enterprise Integration & DeploymentEnterprise Integration & Deployment
Background

Individually, these capabilities are powerful.
Together, they create something fundamentally new.

Where Capabilities
Converge

At the intersection of data access, comparative analysis, and AI-driven interpretation, protoXell enables a new mode of discovery—where researchers can move seamlessly from perturbation data to mechanistic insight.

This unified system connects diverse data sources to biological understanding, supporting hypothesis generation, target discovery, and decision-making.

Inputs
Giga large perturbation datasets
Target gene of interest
Proprietary Data
Biological pathway
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Biology-
Grounded AI
Cross-Study
Insight
AI-Augmented
Mechanistic Insights
Insights
Mechanism of Action
Drug Repositioning
Cell Response Discovery
Novel Drug Targets
  • Access curated perturbation catalog
  • Integrate public + proprietary data
  • Query across experiments at scale

Perturbation Intelligence

Venn Diagram
Biology-
Grounded AI
Cross-Study
Insight
AI-Augmented
Mechanistic Insights

AI-Driven Insight

  • Interpret results with AI
  • Support virtual cell modeling
  • Power LLM-driven agents

Comparative Insight Engine

  • Compare perturbations
  • Uncover biological relationships
  • Reveal mechanisms of action

This unified system connects diverse data sources to biological understanding, supporting hypothesis generation, target discovery, and decision-making.

Giga large perturbation datasets
Target gene of interest
Proprietary Data
Biological pathway
Inputs
Insights
Mechanism of Action
Drug Repositioning
Cell Response Discovery
Novel Drug Targets
Background
Make Previously
Impractical
Analyses Routine

FAQs

Have questions? We're here to help.
Any more questions?
protoXell is a scientific software for cell response discovery, enabling you to explore, compare & interpret perturbation data across experiments, without pipelines, infrastructure, complexity, or specialized expertise. It unifies data access, comparative analysis, and AI-driven interpretation into a single, continuous workflow, enabling researchers to move from raw data to mechanistic insight in minutes, not months.
protoXell supports both genetic and chemical perturbation data across diverse experimental systems, including cell lines and in vivo models. It also enables cross-species analysis through homolog mapping (e.g., human, mouse). The platform is optimized to scale across complex experimental designs, enabling consistent analysis and comparison across large, heterogeneous datasets.
protoXell is built on a curated perturbation data catalog from large-scale public datasets (e.g., Tahoe100, Xaira/Orion), harmonized for consistent cross-study analysis. New data is continuously added, with availability as often as 3 days after a dataset is requested. protoXell also supports private data integration, allowing you to bring your own datasets and have them harmonized into the same catalog for unified analysis.
Yes. protoXell is designed to be platform-agnostic, with modular components that can be deployed within your own infrastructure. Individual components can run on separate environments, allowing you to integrate flexibly with your existing systems while keeping full control over your data.
Yes. Security is a core priority. When deployed in your private cloud, all data remains within your controlled environment. In a SaaS deployment, protoXell follows strict security and privacy standards in line with our terms, ensuring your data is protected. Customer data is never used to train shared AI models without explicit agreement.
protoXell uses large language models (LLMs) through the inXighter tool to explain and summarize analysis results, connecting computational outputs to biological context and helping reduce manual literature review. The LLM does not generate or alter results; it only interprets deterministic outputs to accelerate understanding and insight generation.

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