DNA-encoded chemistry + AI platform for small-molecule drug discovery
X-Chem pairs DNA-encoded chemical libraries with machine learning to accelerate early-stage drug discovery for pharma and biotech partners. The tech stack reveals a hybrid architecture: Docker + Kubernetes on AWS for cloud-native services, alongside chemistry-specific tools (RDKit) and legacy databases (Oracle, PostgreSQL, MongoDB), with ML property prediction now in active development. Current hiring skews heavily research (3 of 6 roles) while tackling backend modernization and cross-product integration—suggesting the company is scaling discovery throughput while addressing infrastructure debt.
X-Chem, founded in 2010 and headquartered in Waltham, MA, develops a platform combining DNA-encoded chemical library technology, discovery chemistry, and AI to help pharmaceutical and biotech companies identify drug candidates. The company reports an 80% success rate in hit identification, ~100 programs licensed by partners, and 4 clinical candidates advanced since 2021. X-Chem serves partners across multiple discovery stages—screen-to-hit, hit-to-lead, lead optimization, and candidate identification—and offers flexible engagement models: full project support, screening services, or standalone access to their ArtemisAI software. The organization operates at 201–500 employees and actively hires across research, engineering, HR, and support functions in the United States, Hungary, and Canada.
X-Chem combines DNA-encoded chemical library screening, discovery chemistry expertise, and machine learning (ArtemisAI software) to identify small-molecule drug candidates. The platform supports partners from initial screening through lead optimization and candidate selection.
AWS (EKS, Lambda), Docker, Kubernetes, PostgreSQL, MongoDB, Oracle, Java, Python, React, RDKit (chemistry toolkit), Salesforce, and Power BI. The stack reflects both cloud-native backend services and chemistry-specific tooling for drug discovery workflows.
X-Chem, Inc.'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.