实例探究 > Automating LC-UV-MS-Based Analytics in Therapeutic Oligonucleotide Process Development

Automating LC-UV-MS-Based Analytics in Therapeutic Oligonucleotide Process Development

公司规模
1,000+
地区
  • Europe
国家
  • Switzerland
产品
  • Genedata Expressionist
技术栈
  • LC-UV-MS-based analysis
  • Automated MS workflows
实施规模
  • Enterprise-wide Deployment
影响指标
  • Innovation Output
  • Productivity Improvements
技术
  • 分析与建模 - 数据即服务
  • 分析与建模 - 实时分析
适用行业
  • 药品
适用功能
  • 产品研发
  • 质量保证
用例
  • 质量预测分析
  • 根因分析与诊断
服务
  • 数据科学服务
关于客户
Roche is a leading provider of in-vitro diagnostics and a global supplier of transformative innovative solutions across major disease areas. The company is currently developing several oligonucleotide-based drugs to address a range of diseases. Their lab provides analytical support to the process chemistry department, which is responsible for optimizing oligonucleotide synthesis processes. They combine the information-rich data obtained from high-performance liquid chromatography (HPLC) and mass spectrometry (MS) to determine the number, amount, and identity of impurities in crude oligonucleotide samples. These insights are key to optimizing the oligonucleotide solid-phase synthesis process.
挑战
Roche, a leading biopharma company, was facing challenges in the analytical process of developing oligonucleotide-based drugs. The process involved the use of high-performance liquid chromatography (HPLC) and mass spectrometry (MS) to determine the number, amount, and identity of impurities in crude oligonucleotide samples. However, the number and complexity of samples combined with the laborious nature of the data analysis generated a significant bottleneck in the analytical process. The company was struggling to meet high analytical throughput demands due to the laborious manual operations for impurity quantification and any requested deeper analysis. The samples often contained many impurities, translating into the analytical challenge of assessing 20–30 peaks arising from 50–100 closely coeluting impurities. The large number of manual operations in the previous quantification process often required 5–6 hours of an analyst’s time, limiting the ability of MS experts to perform required deeper characterization in a timely manner.
解决方案
Roche collaborated with Genedata to develop and implement a tailored MS data processing workflow that increased their throughput and the level of characterization while reducing the burden on their MS experts. Genedata Expressionist® integrated seamlessly into Roche's analytical process and enabled them to directly import and process raw UV and MS data and combine these data streams for each analysis. The workflow-based approach enabled them to automate routine data processing, analysis, and reporting while still allowing their expert users to bring their expertise to bear on the critical stages of the analysis, such as identifying unexpected impurities. Automation of all routine data processing steps—such as blank subtraction, spectrum averaging, and MS quantification— enabled them to streamline and standardize their MS analyses, increasing both throughput and result quality. The data workflow presented here was created and optimized for a specific product synthesis process. However, the inherent flexibility of Genedata Expressionist enables them to use this workflow as a template that can easily be adapted for processing other molecules.
运营影响
  • Genedata Expressionist automated data processing increased analytical throughput by shortening the time required for analysis from 5–6 hours to just 30 minutes in the case of very complex samples.
  • By eliminating analytical bottlenecks, Roche was able to keep pace with the large number of samples generated by their process chemists systematically optimizing each parameter and step.
  • The additional expert analytical capacity provided by automation of routine data processing tasks enabled Roche to better characterize unexpected impurities and provide more detailed reports to stakeholders without impacting the overall laboratory throughput.
  • Automating MS data processing removed the burden of performing tedious manual data operations from Roche's analysts. By enabling them to focus on tasks that require their domain expertise and training rather than routine and repetitive manual operations, the Genedata Expressionist workflow not only enabled Roche to deliver higher-quality results faster, but also generated a more engaging and rewarding workload for their analysts.
数量效益
  • Increased analytical throughput by shortening the time required for analysis from 5–6 hours to just 30 minutes in the case of very complex samples.
  • Automated data processing increased the number of process-related impurities identified in each analysis.

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