Case Studies Efficient, automated data processing for a novel MS-based high-throughput screening platform

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	Efficient, automated data processing for a novel MS-based high-throughput screening platform

Efficient, automated data processing for a novel MS-based high-throughput screening platform

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries	Healthcare & Hospitals Pharmaceuticals
Applicable Functions	Product Research & Development Quality Assurance
Use Cases	Predictive Quality Analytics Process Control & Optimization Root Cause Analysis & Diagnosis
Services	Data Science Services System Integration
Challenge	AstraZeneca, a global biopharmaceutical company, was facing challenges in automating data processing and increasing the quality of results. The company was using Acoustic Droplet Ejection (ADE) technology for high-throughput screening (HTS), which introduced samples into a mass spectrometer. However, the increase in throughput brought by Acoustic Mist Ionization Mass Spectrometry (AMI-MS) technology resulted in large amounts of data that needed efficient processing. The main challenges included eliminating laborious and potentially error-inducing manual interventions, guaranteeing data quality and traceability, adapting data processing to different targets and screening strategies, obtaining insightful visualization to speed assay development, and integrating MS data into screening data analysis platforms. Read More
About Customer	AstraZeneca is a global, science-led biopharmaceutical company that develops innovative medicines used by millions of patients worldwide. The company is committed to discovering, developing, and delivering innovative, meaningful medicines and healthcare solutions that enrich the lives of patients. The medicines developed by AstraZeneca are used in three main therapy areas - Oncology, Cardiovascular & Metabolic Disease and Respiratory. The company also is selectively active in the areas of autoimmunity, neuroscience and infection. AstraZeneca operates in over 100 countries and its innovative medicines are used by millions of patients worldwide. Read More
Solution	AstraZeneca partnered with Genedata to develop a flexible, automated data processing workflow for efficiently processing the large amounts of data generated by the AMI-MS screening platform. The solution, Genedata Expressionist, is based on automated, customizable workflows, in which data is subjected to sequential processing steps. The software automatically parses and assigns spectra to their respective 384-well plate well, eliminating the need for manual scanning of barcodes. Advanced algorithms ensure the highest data quality by automatically quantitating peaks of interest using dynamic peak detection and clustering algorithms. The software also offers flexibility in assay design, allowing AstraZeneca’s scientists to employ any MS-based screening approach. The results are seamlessly exported to Genedata Screener, where plate-wise visualization of results enables routine QC and fast identification of potential hits. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Industries

Healthcare & Hospitals

Pharmaceuticals

Applicable Functions

Product Research & Development

Quality Assurance

Use Cases

Predictive Quality Analytics

Process Control & Optimization

Root Cause Analysis & Diagnosis

Services

Data Science Services

System Integration

Challenge

AstraZeneca, a global biopharmaceutical company, was facing challenges in automating data processing and increasing the quality of results. The company was using Acoustic Droplet Ejection (ADE) technology for high-throughput screening (HTS), which introduced samples into a mass spectrometer. However, the increase in throughput brought by Acoustic Mist Ionization Mass Spectrometry (AMI-MS) technology resulted in large amounts of data that needed efficient processing. The main challenges included eliminating laborious and potentially error-inducing manual interventions, guaranteeing data quality and traceability, adapting data processing to different targets and screening strategies, obtaining insightful visualization to speed assay development, and integrating MS data into screening data analysis platforms.

About Customer

AstraZeneca is a global, science-led biopharmaceutical company that develops innovative medicines used by millions of patients worldwide. The company is committed to discovering, developing, and delivering innovative, meaningful medicines and healthcare solutions that enrich the lives of patients. The medicines developed by AstraZeneca are used in three main therapy areas - Oncology, Cardiovascular & Metabolic Disease and Respiratory. The company also is selectively active in the areas of autoimmunity, neuroscience and infection. AstraZeneca operates in over 100 countries and its innovative medicines are used by millions of patients worldwide.

Solution

AstraZeneca partnered with Genedata to develop a flexible, automated data processing workflow for efficiently processing the large amounts of data generated by the AMI-MS screening platform. The solution, Genedata Expressionist, is based on automated, customizable workflows, in which data is subjected to sequential processing steps. The software automatically parses and assigns spectra to their respective 384-well plate well, eliminating the need for manual scanning of barcodes. Advanced algorithms ensure the highest data quality by automatically quantitating peaks of interest using dynamic peak detection and clustering algorithms. The software also offers flexibility in assay design, allowing AstraZeneca’s scientists to employ any MS-based screening approach. The results are seamlessly exported to Genedata Screener, where plate-wise visualization of results enables routine QC and fast identification of potential hits.

Impact #1	Significant time savings: The data processing workflow requires a single click and takes around 25 minutes for a data set obtained from 150 × 384-well plates. Previously, processing of such data sets—including the potential error-inducing manual steps—required 3 hours.
Impact #2	Higher-quality, more reliable data: By eliminating potential error-inducing manual steps, automated Genedata Expressionist data processing greatly increases the level of confidence in the quality of the data.
Impact #3	Flexibility in assay design: Because it can be used for processing data from any MS instrument or application, Genedata Expressionist offers AstraZeneca’s scientists the ability to employ any MS-based screening approach, and the opportunity to explore biological experimental spaces outside conventional substrate/product assay strategies.

Impact #1

Significant time savings: The data processing workflow requires a single click and takes around 25 minutes for a data set obtained from 150 × 384-well plates. Previously, processing of such data sets—including the potential error-inducing manual steps—required 3 hours.

Impact #2

Higher-quality, more reliable data: By eliminating potential error-inducing manual steps, automated Genedata Expressionist data processing greatly increases the level of confidence in the quality of the data.

Impact #3

Flexibility in assay design: Because it can be used for processing data from any MS instrument or application, Genedata Expressionist offers AstraZeneca’s scientists the ability to employ any MS-based screening approach, and the opportunity to explore biological experimental spaces outside conventional substrate/product assay strategies.

Benefit #1	Seven-fold decrease in processing time with elimination of potentially error-inducing manual interactions.

Benefit #1

Seven-fold decrease in processing time with elimination of potentially error-inducing manual interactions.

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Overview

Efficient, automated data processing for a novel MS-based high-throughput screening platform

Operational Impact

Quantitative Benefit