Revolutionizing

Preclinical R&D

Discover how BenchSci’s preclinical R&D platform, ASCEND, is changing the way scientists decode disease biology at scale.

The platform

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Mapping the path to future discoveries

Disease biology is highly fragmented and complex. Using state-of-the-art image-and-text-based machine learning models, we’ve created an unbiased, evidence-based map of the underlying biology of disease across all therapeutic areas. Through a suite of AI-powered applications, scientists can uncover the feasibility of new or existing pursuits, optimize testing strategies, and identify potential risks at the project’s onset.

ACCELERATED

Advance Your Research

Reach key milestones sooner with an optimized experimental path. Use patented machine learning technology to search, analyze, and extract scientific evidence from a comprehensive catalog of biomedical literature in minutes, not months.
Improve R&D Productivity

Increase throughput and be more efficient with your resources. Pursue only those approaches with the highest chance for success.
De-risk Your Portfolio

Focus on promising targets and indications, while identifying safety and efficacy risks for clinical translation. Build confidence in project strategies or support alternative avenues.

Why Drug Discovery Needs BenchSci

90%

Investigational New Drugs (INDs) that fail in clinical trials.

$500M+

Spendings per big pharma, per year, on preclinical R&D.

79.5%

Experiments that fail, are redundant, or are irreproducible.

See how ASCEND by BenchSci can work for you

The Platform

The Platform is really, really useful—we save a lot of time and energy, and it’s helpful to communicate between us.

Industry scientist at top 20 pharma

Without the platform, it would have taken me hours to find the antibody I needed, but with it, it took me a few minutes.

Industry scientist at top 20 pharma

The quality of the data is the number one value-add. I can narrow the field down to 2 or 3 candidates, compared to 10 or 20

Industry scientist at top 20 pharma

It would have been absolutely impossible to find a commercially available antibody for our experiment without the platform

Industry scientist at top 20 pharma