Versatile and Open Analytics for the Life Sciences

Accelerate drug discovery and development, optimize manufacturing and improve marketing precision by turning data into insight.

KNIME Powers Solutions for Life Science Teams



  • Accelerate the time of taking a drug to market with streamlined data analysis

  • Standardize lab automation and improve experimental reproducibility

  • Ensure regulatory compliance with transparent, automatic documentation of processes

  • Provide patients with timely access to safe pharmaceuticals by optimizing supply chain and inventory management

"KNIME is a feature-complete, powerful alternative to working with clinical data. It has verbose logging and validation capabilities. Its visual programming is especially useful for pipeline optimization, automation, and education."

Robert Adams, Bayer Pharma AG

Why KNIME for Life Sciences

Sophisticated Analytics, Intuitive Interface

Easy-to-use, visual programming interface allows scientists to build analytic models and automate tedious spreadsheet work, without any coding, independent of analytics bottlenecks or resource constraints. The no-code/low-code environment lowers the barrier to data science, providing access to novel and highly advanced algorithms that can be applied on big datasets. Teams also have the flexibility to script custom algorithms in a language of their choice with built-in integrations with R, Python, Java and more.

Sophisticated Analytics, Intuitive Interface
A Single Environment for the Entire Pipeline from Drug Discovery to Sales and Marketing

A Single Environment for the Entire Pipeline from Drug Discovery to Sales and Marketing

Data is siloed and disorganized in internal archives, at clinical institutions, with research organizations, or even external partners. With end-to-end coverage, from easy data access and prep, to visual data exploration and modeling, to enterprise-wide deployment, monitoring and management, life science companies can use a single platform to support projects from start to finish. Access to advanced analytics within one consistent environment enables companies streamline their entire pipeline from drug discovery through to production, sales, and marketing.

Extensible & Flexible

From electronic medical records, to x-ray images, from diagnosis records to personal patient information, from clinical trial data to audit trails, from inventory management data, to supply chain documents, insurance records and financial information – life science companies need access to a lot of different data types. With access to over 300+ data sources, they can work with their specific life science data types easily and within a single, consistent environment.

Extensible & Flexible


The data science ecosystem is rapidly evolving. To forecast the future of diseases, medicines, gene expressions, or patient health, data analysts in life science need to keep abreast of new technologies and techniques. KNIME’s open-source approach keeps companies in the life sciences space on the bleeding edge of modern data science. No vendor-developed tool can keep pace with the innovation driven by an active open-source user community. KNIME has many native functionality dedicated to the life science field in addition to community extensions, such as RDkit, ImageJ2, SeqAn, and more.

Scale as You Grow

From disease diagnosis instruments, patient records, or lab test results, pharma companies are collecting data from an ever-growing number of sources. As their technology environment evolves, KNIME ensures companies can continue to access and connect to all types and sources today and in the future. Available in the cloud or internal data centers, with KNIME, teams can process and analyze petabytes of data quickly. Multi-disciplinary teams can work and collaborate in their preferred environment and language to create models and custom functionality. Easy sharing and reusability ensures analytics are pervasive across the organization.

Scale as You Grow

Recommended Resources

Learn how to use Python code in KNIME
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Watch presentations from hit generation to the clinic
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How manufacturers can handle volatile markets
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How to Better Leverage Data to Unblock Pharma R&D
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