BenchSci

About BenchSci

BenchSci's ASCEND platform utilizes multimodal AI and ontologies to analyze extensive biomedical datasets, enhancing the understanding of disease biology for pharmaceutical research and development. This evidence-based solution streamlines drug discovery processes and complex research workflows, improving efficiency across various therapeutic areas.

```xml <problem> Pharmaceutical research and development faces challenges in efficiently understanding complex disease biology, leading to delays and increased failure rates in drug discovery. Scientists struggle to navigate vast amounts of biomedical data, hindering their ability to identify novel connections and make informed decisions. </problem> <solution> BenchSci's ASCEND platform addresses these challenges by providing a disease biology generative AI platform tailored for pharmaceutical R&D. ASCEND leverages multimodal AI and ontologies to analyze extensive biomedical datasets, including closed-access papers, patents, preprints, and internal pharma data. The platform acts as an AI assistant, guiding scientists through research complexities, elevating biology-related decision-making, and uncovering novelty while increasing experimental productivity. By decoding and harmonizing data from diverse sources, ASCEND helps scientists generate better ideas and identify optimal experimental paths, ultimately accelerating the discovery of novel medicines. </solution> <features> - Multimodal AI that understands experiments from both text and figures - Access to a comprehensive biomedical dataset, including closed-access papers and patents - Proprietary and robust ontology knowledge base (OKB) - Integration of internal pharma data (ELNs, SharePoints, materials) - Specialized AI assistants with a deep understanding of pharma workflows - GUI interfaces and collaboration areas - Enterprise-ready integrations and report generation - In-silico prediction capabilities </features> <target_audience> The primary users are drug research scientists in the pharmaceutical industry who aim to accelerate drug discovery by leveraging AI to understand disease biology and improve experimental outcomes. </target_audience> ```

What does BenchSci do?

BenchSci's ASCEND platform utilizes multimodal AI and ontologies to analyze extensive biomedical datasets, enhancing the understanding of disease biology for pharmaceutical research and development. This evidence-based solution streamlines drug discovery processes and complex research workflows, improving efficiency across various therapeutic areas.

Where is BenchSci located?

BenchSci is based in Toronto, Canada.

When was BenchSci founded?

BenchSci was founded in 2015.

How much funding has BenchSci raised?

BenchSci has raised 174190000.

Location
Toronto, Canada
Founded
2015
Funding
174190000
Employees
377 employees
Major Investors
Generation Investment Management

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BenchSci

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Executive Summary

BenchSci's ASCEND platform utilizes multimodal AI and ontologies to analyze extensive biomedical datasets, enhancing the understanding of disease biology for pharmaceutical research and development. This evidence-based solution streamlines drug discovery processes and complex research workflows, improving efficiency across various therapeutic areas.

benchsci.com20K+
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Crunchbase
Founded 2015Toronto, Canada

Funding

$

Estimated Funding

$100M+

Major Investors

Generation Investment Management

Team (250+)

No team information available.

Company Description

Problem

Pharmaceutical research and development faces challenges in efficiently understanding complex disease biology, leading to delays and increased failure rates in drug discovery. Scientists struggle to navigate vast amounts of biomedical data, hindering their ability to identify novel connections and make informed decisions.

Solution

BenchSci's ASCEND platform addresses these challenges by providing a disease biology generative AI platform tailored for pharmaceutical R&D. ASCEND leverages multimodal AI and ontologies to analyze extensive biomedical datasets, including closed-access papers, patents, preprints, and internal pharma data. The platform acts as an AI assistant, guiding scientists through research complexities, elevating biology-related decision-making, and uncovering novelty while increasing experimental productivity. By decoding and harmonizing data from diverse sources, ASCEND helps scientists generate better ideas and identify optimal experimental paths, ultimately accelerating the discovery of novel medicines.

Features

Multimodal AI that understands experiments from both text and figures

Access to a comprehensive biomedical dataset, including closed-access papers and patents

Proprietary and robust ontology knowledge base (OKB)

Integration of internal pharma data (ELNs, SharePoints, materials)

Specialized AI assistants with a deep understanding of pharma workflows

GUI interfaces and collaboration areas

Enterprise-ready integrations and report generation

In-silico prediction capabilities

Target Audience

The primary users are drug research scientists in the pharmaceutical industry who aim to accelerate drug discovery by leveraging AI to understand disease biology and improve experimental outcomes.

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