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Mestrelab Research
Mestrelab Research je společnost zabývající se vývojem softwaru zaměřená na vývoj a dodávku vysoce kvalitního softwaru pro analytickou chemii (NMR, LC/GC/MS) a správu dat analytické chemie (databáze, elektronická archivace atd.)
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Automating the processing of analytical data for multiple drug discovery applications at AstraZeneca

ZÁZNAM | Proběhlo Út, 9.4.2024
Připojte se k tomuto webináři, kde se vědci a IT odborníci ze společnosti AstraZeneca setkají, aby společně prozkoumali složitost správy analytických dat v prostředí purifikační laboratoře.
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Mestrelab Research: Automating the processing of analytical data for multiple drug discovery applications at AstraZeneca

Mestrelab Research: Automating the processing of analytical data for multiple drug discovery applications at AstraZeneca

Join us for an insightful session where scientists and IT professionals from AstraZeneca come together to explore the complexities of managing analytical data within a purification lab setting. In this session, Carolina Sanchez, Senior Scientist, and Katie Proctor, Senior Scientist, will discuss the challenges of manually processing and reviewing large volumes of analytical data, and explain how automation software solutions are boosting efficiency and benefiting them in their day-to-day work. Following that, Dr. Christoph Bauer, Associate Principal Scientist, will discuss the IT architecture and integration aspects of the solution implementation.

SESSION 1

Tuesday, Apr 9th
  • 10:00 am (EDT)
  • 4:00 pm (CEST)
  • 7:00 pm (PDT)

SESSION 2

Wednesday, Apr 10th
  • 10:00 am (CEST)
  • 1:30 pm (IST)
  • 5:30 pm (ACST)

Abstract

A lab with significant analytical capacity entails managing a large number of instruments and extensive analytical data on a daily basis. Within our purification labs, analytical screening data generated for compounds submitted for purification, as well as data from instrument suitability testing, was traditionally reviewed manually by an analyst to determine the most appropriate method for purification. However, this changed with the implementation of the automation solution from Mnova. The solution includes the Chrom SST brick, which monitors the performance of our instruments, and Chrom Best Method, which automatically processes the screening data and identifies the best conditions for purification, thereby freeing up analyst time.

In this webinar, we will explain how these solutions fit into our day-to-day work and the benefits they have brought us. We will also discuss the IT architecture and integration aspects, the server-based processing logic, as well as the content and formats of the output.

Presenter: Katie Proctor (Senior Research Scientist, AstraZeneca)

Katie is a Senior Research Scientist in the Analytical and Purification group at AstraZeneca Cambridge since 2018. She has a keen interest in data science and has a focus on developing software solutions to automate system suitability assessments and analytical to purification method selection. In the lab, Katie focuses on achiral SFC and RP purification of small molecules.

Presenter: Carolina Sanchez (Senior Scientist, AstraZeneca)

Carolina is a chemical engineer and biotechnologist with a keen interest in data science. Since 2015, she’s been deeply involved in chromatography, getting better at developing analytical techniques for various uses. For the past four years, she’s been at AstraZeneca, working as a separation scientist where she focuses on preparative chromatography of small molecules, using both liquid and supercritical fluid chromatography methods.

Presenter: Christoph Bauer (Associate Principal Scientist, AstraZeneca)

Christoph holds a PhD in theoretical Chemistry and has transitioned to the field of chemoinformatics and modeling where he applies quantum chemistry, statistical analysis, and machine learning methods to chemical data within the pharmaceutical science domain. Over the past four years, he has been working in the Pharm Sci Data Science & Modelling group at AstraZeneca, developing cheminformatics and computational solutions aimed at streamlining chemistry workflows.

Mestrelab Research
 

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