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How Making Informed Decisions With Data Visualization Works

Global regulatory authorities have been raising the expectation of incorporating quality by design (QbD) into pharmaceutical development.

by ACD/Labs
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Luminata—a single application for management of chemical and analytical impurity data and process development workflows.

Problem: Global regulatory authorities have been raising the expectation of incorporating quality by design (QbD) into pharmaceutical development. While QbD offers many important long-term benefits, these expectations are having a dramatic impact on product development groups, specifically on impurity control strategies that must be addressed. To follow these QbD principles, data visualization for decision making is essential. Currently in pharmaceutical development, chemical structure information may be available from the chemists' individual electronic laboratory notebooks, but data characterization information is not always easily accessible. Processed datasets are abstracted from rich interactive analytical data to images, numbers, and text because organizations lack systems that natively handle this data. Additionally, some of that data and interpreted information may have been transcribed and summarized into MS Excel spreadsheets, with cross functional teams contributing. While spreadsheets are effective for handling and managing numerical data—helping formulate and understand relationships through sorting and plotting—they are a weak tool for relating chemical structures with the analytical spectra and chromatograms used to identify and characterize them.

Solution: Luminata™, a software application built on the ACD/Spectrus Platform, offers scientists in process development the ability to construct live, interactive process maps that enable visualization of the impurities at each stage of the route, and visual comparison of molecular composition across unit operations. This allows for rapid assessment and decision making around the effectiveness and efficiency of impurity control measures. The software stores the context of the experiment, expert interpretations, and decisions resulting from it. Connection of live spectroscopic and chromatographic data with chemical entities allows analytical and process chemists alike to visually confirm the authenticity of numerical or textual interpretations, and to examine processed analytical data without having to open separate applications. The software offers the capability for different users to see the information most relevant to their work from the central database—this includes all chemical entities in the process with their related LC/UV/MS data, and the visualization of impurity fates for batches from the milligram to kilogram scale. Comprehensive process development data is easily reported across all stages with convenient export to Microsoft Word and Excel for reporting and further manipulation of data if desired. Decision support tools facilitate batch assessments for investigations around alternative catalysts, reagents, and batches prepared on various scales.

The software also enables risk assessment conclusions pertaining to fate and purge. That is, identifying the formation and fate of the impurity from the chemical information. Through the identification of process related impurities from well-managed and assembled analytical data, the impurity fate mapping functionality allows for real-time quantitative purge factor determination. These tools, designed specifically with process development workflows in mind, ease the burden on project team members, whatever their role, to facilitate collaboration through robust and facile sharing of chemical and analytical information.

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