BenchSci is a cloud-based software platform designed to accelerate biomedical research by leveraging artificial intelligence to decode and organize experimental data from millions of scientific publications, patents, and third-party databases. The platform enables academic researchers to efficiently search for and validate antibodies, reagents, and model systems—such as recombinant proteins, RNAi, cell lines, CRISPR, animal models, and PCR—by extracting and structuring experimental evidence from published literature. BenchSci’s proprietary machine learning models analyze both text and images from over 27 million full-text scientific publications and millions of abstracts, providing experiment-specific insights and validation data. The user interface allows researchers to filter results by experimental context, compare reagent specifications, and access figures directly from scientific papers. The academic version of BenchSci is offered free of charge to researchers at universities and non-profit institutions, supporting more than 30,000 scientists at over 3,600 institutes. This platform reduces the time and cost associated with experimental planning, increases reproducibility, and helps researchers make more informed decisions in preclinical research.

Key Features

AI-Assisted Reagent and Model System Search Rapidly identifies validated reagents and model systems for specific experimental needs.

• Search by target protein, reagent type, or model system
• Access validation data and experimental context from scientific literature

Comprehensive Biomedical Database Aggregates and organizes data from a vast range of sources.

• Over 27 million full-text publications and millions of abstracts
• Includes peer-reviewed articles, preprints, patents, and third-party databases

Experiment-Specific Filtering and Comparison Enables precise selection of reagents and models.

• Filter results by experimental context, application, and species
• Compare specifications and performance data side-by-side

User-Friendly Interface Simplifies navigation and data interpretation.

• Visual display of figures and data from publications
• Proprietary ontology organizes biological relationships

Free Academic Access Supports the academic research community.

• No-cost access for university and non-profit researchers
• Tailored features for academic workflows

Benefits

Accelerated Experimental Planning Reduces time spent searching for and validating reagents.

• Enables rapid identification of suitable antibodies and models
• Minimizes failed experiments due to poor reagent selection

Cost Savings Decreases research expenses by improving reagent selection.

• Reduces waste from ineffective reagents
• Saves millions annually for institutions

Increased Reproducibility and Success Improves experimental outcomes and reliability.

• Provides evidence-based validation from published studies
• Enhances confidence in reagent and model system choices

Supports Open Science Promotes accessibility and collaboration in academia.

• Free access for academic researchers
• Facilitates sharing of experimental insights