BenchSci and argenx Sign Two-Year Enterprise Agreement to Deploy AI-Driven Preclinical Drug Discovery Platform
核心洞察
BenchSci (搜索) announced a two-year enterprise agreement with argenx to deploy EMET (搜索), its agentic research environment for preclinical drug discovery, across argenx's global research organization.
The platform was selected through a competitive evaluation led by argenx's own scientists, marking a significant milestone in BenchSci (搜索)'s expansion across European biopharma.
EMET (搜索) unifies data, models, software, workflows, and scientific reasoning, reasoning across 38M+ publications and 100+ curated databases to support preclinical, computational, and drug development workflows.
BenchSci (搜索), a leading provider of AI software for biopharma research and development, announced a two-year enterprise agreement with argenx, a global immunology innovation company, to deploy EMET (搜索), BenchSci's agentic research environment for preclinical drug discovery, within the organization. The agreement, announced on September 2, 2026, was selected through a competitive evaluation led by argenx's own scientists and represents a significant milestone in BenchSci's expansion across European biopharma.
Under the agreement, scientists across argenx's global research organization will use EMET (搜索) to support preclinical, computational, and drug development workflows.
An Agentic Research Environment for Preclinical R&D
EMET (搜索) is positioned as an agentic AI workbench purpose-built for preclinical R&D. Just as AI coding gives every developer a team of expert engineers, EMET gives every scientist an agentic team of PhD scientists, unifying data, models, software packages, workflows, and scientific reasoning into a single environment.
The platform reasons across more than 38 million open- and closed-access scientific publications, a proprietary knowledge graph, clinical data, pre-print data, and over 100 curated scientific databases to execute complex, multi-step scientific workflows and deliver traceable, actionable insights across the full drug discovery journey.
Scientist-Led Selection and Strategic Rationale
The competitive evaluation was led by argenx's own scientists, a detail BenchSci (搜索) emphasized as a signal of platform credibility. "When scientists run a competitive evaluation and choose the platform themselves, it means the platform is earning trust where it matters most — at the bench, not in the boardroom," said Liran Belenzon, CEO & Co-Founder of BenchSci.
Tim Van Acker, Director of Business Development at argenx, framed the collaboration as an experiment in accelerating development. "We think of BenchSci (搜索)'s EMET (搜索) as a scientist in your pocket – always available, always reasoning across the evidence. For argenx, this is about testing whether this kind of always-on scientific support can meaningfully accelerate preclinical development and our broader computational and drug development workflows," said Van Acker.
Addressing the Root Cause of Drug Discovery Failure
BenchSci (搜索) applies AI to understand how disease biology works throughout the drug discovery pipeline, targeting what the company identifies as the number one reason drug discovery projects fail — getting the biology wrong. EMET (搜索) is designed to give every scientist an agentic team of PhD scientists to reason through the disease biology behind every question.
BenchSci (搜索) reports that its platform accelerates science at 16 top-20 pharmaceutical companies and over 4,500 leading research centers worldwide. The company has raised over $200 million, backed by investors including Generation Investment Management, iNovia Capital, TCV, F-Prime, Gradient Ventures (Google's AI fund), and Golden Ventures.