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KNIME Data Talks: Drug Discovery — From Hit Generation to the Clinic

Presentations from KNIME Data Talks: Drug Discovery

June 1, 2022 | Online
In-Person / Hybrid
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KNIME Data Talks 2022: Drug Discovery: Blending KNIME Data ETL and Analytics Capabilities with an Enterprise LIMS, ELN and Cheminformatics Platform

Speaker: Kenneth Longo (Wave Life Sciences Ltd)

Hear from Kenneth Longo how Wave Life Sciences is using KNIME in the early drug discovery process and combines well-established enterprise software solutions for molecule registration, cheminformatics and data acquisition. Find out how KNIME can save hours and days of work by standardizing and automating ETL, modeling and analytics processes.

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KNIME Data Talks 2022: Drug Discovery: How can KNIME make your structure-based virtual screening campaign more successful?

Speaker: Emilie Pihan (Discngine)

Emilie demonstrates how KNIME is used at Evotec to improve the calibration step for structure-based virtual screening campaigns. Those steps taken using KNIME make the calibration easier, save time and improve the quality of the results.

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KNIME Data Talks 2022: Drug Discovery: Computer Vision for Resident-Intruder Monitoring using KNIME

Speaker: Aaron Hart (Idorsia Pharmaceuticals Ltd.)

The Resident-Intruder model is a standardized approach for monitoring stress and aggression levels in mice. Analyzing the video data from studies using this model is laborious, time-consuming and requires extensive manual scoring. Here Aaron Hart from Idorisa Pharmaceuticals Ltd. shows a method based on computer vision that helps automate this process. Orchestrated by KNIME, their solution is available to scientists on-demand, scores e.g. 10 hours of video in 30 minutes, and incurs zero idle costs.

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KNIME Data Talks 2022: Drug Discovery: Clinical Analysis Dataset Derivation using Visual Programming with KNIME

Speaker: Robert Adams (Bayer Pharma AG)

Clinical data analysis is a manual and error-prone process where SAS is used as a standard proprietary software. Robert proposes KNIME as a powerful feature-complete and open source alternative for data preparation of clinical data transformation. He highlights the advantages of KNIME’s visual programming environment for pipeline optimization and automation, working with clinical data in a GxP regulated environment.

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Drug Discovery: Community Spotlight

Speakers: RDKit (Greg Landrum), Vernalis (Stephen Roughley), OpenMS (Timo Sachsenberg)

Community extension developers introduce the software extensions they are currently working on and discuss the benefits of their most recent features. Timo highlights an example of analysis of MS data for proteomics with OpenMS nodes. Greg introduces extensive conformer generation and image generation for molecules with the RDKit nodes and Steve talks about additions to collection and binary compression nodes in the Vernalis extension.

Reach out to the community extension developers: RDKit, VernalisOpenMS

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