BioBox Platform

Bioinformatic data mining using natural language, without hallucinations.

95% of drug programs fail and most of them because the target was wrong. BioBox helps scientists identify and validate drug targets using evidence directly from sequencing data quickly.

Trusted by scientists

Unlock discoveries with the first LLM/KG hybrid system

A new data-layer that harnesses the power of both technologies to make biological data-mining easy.

Foundation Graphs

Make your data searchable. Curate a proprietary knowledge graph with harmonized properties from Ontology databases.

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Annotate Data
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Unmask hidden discoveries

Converse with Data

Get evidence-based answers, not hallucinations. Using natural language, retrieve data-driven answers from your knowledge graph.

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Ask questions
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Get data-driven answers
How it works

It's easy to start

Start mining your data with natural language in 3 easy steps.

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1. Create your dictionary

Build out a controlled dictionary of data properties collaboratively to make sure everyone on the team is on the same page.

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2. Connect your data

Leverage API integrations include REST services to stream in data from s3 and gcs. Hook up your workflows to connect the outputs to the platform.

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3. Get results

Let the platform work its magic. Sit back and watch your sequencing data self-organize into a semantic knowledge graph and search it with the Knowledge Engine

More features

All the tools you need

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Data Dashboards

Share a compelling narrative with your team. Leverage collaborative, interactive and customizable multi-omic dashboards to explore large cohorts of data.

Experience a new way to converse with your data

Get answers based on evidence, not hallucinations.


Use cases

Learn more about how modern biotechs are deploying BioBox to hit R&D milestones and make mission-critical decisions with confidence.

Target Identification

Identify and prioritize disease specific targets. Obtain a comprehensive understanding of the biological underpinnings of a disease. Compare and contrast targets identified in the public domain and in your proprietary data.

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Evaluate Feasibility
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Establish Causality
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Public Data Access
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Evidence Ranking

Target Prioritization

Find compelling evidence across public and private data to support the efficacy of a target. Identify target and disease relationships across multi-omic observations. Share findings and collaborate with team members.

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Customer feedback
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Hypothesis Testing
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Stakeholder Collaboration
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Multi-omic data integration

Drug Repurposing

Find additional indications for your therapeutic asset to expand its value. Use the BioBox Knowledge Engine to create in-silico models and uncover hidden connections between drug and diseases.

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Market Expansion
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Causal Inference
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Predict Outcomes
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Find Indications