March 17-21, 2019
Pennsylvania Convention Center - West, Philadelphia, PA, USA
MONDAY, MARCH 18TH, 8:30 AM
Impurity Control Strategies Using Impurity Mapping with Dynamic Purge Factor Calculations
Andrew Anderson, Graham McGibbon, Sanjivanjit K. Bhal, and Joe DiMartino
Abstract Number: 380-1
Session: 380—Quality Assurance, Regulatory, and Data Integrity
Abstract: Regulatory authorities expect pharmaceutical development to demonstrate process and product understanding according to Quality by Design (QbD) principles. The overarching goal of this is to ensure that medicines are safe and efficacious. To achieve these goals, control strategies must be developed which comprehensively assess, classify, and report process route development. Ultimately controlling process inputs and materials, their attributes, the design spaces around unit operations, methods, variability, and final product specifications. Impurity mapping lies as the foundation of this. While scientist have developed practices to gather this information, it remains a tedious manual process.
In this presentation we will provide an overview of a new software application developed specifically to address these challenges. LuminataTM offers the ability to construct process maps—allowing for visualization of the impurities at each stage of the route, and visual comparison of molecular composition across unit operations. This enables rapid assessment and decision-making around the effectiveness and efficiency of impurity control measures. The software also stores the context of the experiment and expert interpretations, and offers project teams the capability to perform both risk and comparative assessments. Connection of live analytical data with chemical entities enables easy visual confirmation of the veracity of numerical/textual interpretations and processed results without the need for access to multiple software applications.
Through the identification of process related impurities from well-managed and assembled analytical data, and impurity fate mapping with “real time” quantitative purge factor determination, the software empowers scientists to work with process data and develop control strategies more efficiently.
Design to Decision—Enhancing the value of high throughput chemistry in drug development while minimizing the risks and bottlenecks associated with data management
Michael Boruta, Andrew Anderson
Abstract: High throughput chemistry experiments have been around for many years and, with their associated robotics, have proven themselves as an effective method for screening many reactions or conditions while minimizing the use of materials. While the efficiency of the actual experiment execution has been improved, the means to transfer and manage information from design of experiment, material collection, stock solution creation, plating, execution of experiments, analytical data collection, data analysis and review, sample registration and submission, and reporting and archiving is only achieved by several different pieces of software. Using multiple pieces of software decreases the overall efficiency and creates risks where information needs to be manually associated or transferred. This presentation will examine some initial problems and results from several implementations of a solution designed to address the overall efficiency of these systems.