« Back
Applying QbD in Process and Impurity Control Strategy Development
Applying QbD in Process and Impurity Control Strategy Development
Submitted on 06 Dec 2017

Andrew Anderson, Graham A. McGibbon, Sanjivanjit K. Bhal, and Joe DiMartino
Advanced Chemistry Development, Inc. (ACD/Labs)
This poster was presented at AAPS
Poster Views: 661
View poster »
Poster Abstract
Global regulatory authorities continue to push Quality-by-Design (QbD) in pharmaceutical development to support risk management. While QbD affords many important long-term benefits, these expectations are having a dramatic impact on product development groups and their supporting corporate informatics infrastructure.
In order to effectively leverage QbD in risk mitigation, firms should consider informatics platform innovation—particularly to support reduction of data abstraction, data assembly, and human data preparation. Informatics software for Impurity control should optimally provide users with the ability to construct ‘process maps’ which allow for visual comparison of molecular composition across unit operations. The platform should also allow the user to visualize the wide variety of related spectroscopic and chromatographic data in a single environment for each stage and substance for efficient and informed decision-making.

This paper will provide an overview of a new software application (LuminataTM) developed specifically to address these platform innovation needs. Analytical data from Agomelatine, a CNS agent, is used to exemplify these embodiments.

Analytical data collected for Agomelatine, synthesized by a five stage process route, was used in this work.
The analytical data was collected on an Agilent-1200-Series with an Agilent VWD G1314B UV detector, acquiring spectra at 210nm; and an Agilent 6110 Quadrupole API-ES Mass Spectrometer, collecting low resolution spectra in a mass range of 45-1000Da. Column separation was done with an isocratic method using an ammonium formate Buffer pH of 4.5/ACN (35:65). The flow rate was 1.2ml/min with a run time of 50min, the column used was a Zorbax Eclipse XDB C18 5um - 4.6 x 150mm.
The software application, LuminataTM (v2016.2 beta-release) based on the ACD/Spectrus Platform was used to manage analytical and chemical data for the process.

LuminataTM provided 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 platform stored the context of the experiment, expert interpretations, and decisions resulting from it. Connection of live analytical data with chemical entities allows users to visually confirm the veracity of numerical or textual interpretations or processed results without having to open separate applications.
Configurable screen forms enabled visualization of all entities in the process with their related LC/UV/MS data; and visualization of impurity fates of process data for batches/lots in a milligram to manufacturing scale.
Comprehensive process data was easily reported across all stages with direct export to Word and Excel.
Although not shown for the present example, it would be straightforward for a user to compare future batches prepared on different scales; or for investigations around alternative catalysts and reagents, for the same API endpoint.

Dynamic visualization of assembled and aggregated information preserves data integrity while supporting decision-making. An informatics solution that effectively supports process and impurity control strategy development enables:
• Risk assessment conclusions pertaining to impurity onset, fate, and purge
• Comparative assessments of different purification methods
• Comparative assessments of different control strategies
Report abuse »
Ask the author a question about this poster.
Ask a Question »

Creative Commons

Related Posters

MODEL-AD: Late-Onset Alzheimer’s Disease Models
Bruce Lamb on behalf of the MODEL-AD Consortium

MODEL-AD: Characterization of Familial AD Models (5xFAD, APP/PS1, hTau, 3xTg-AD)
Adrian Oblak on behalf of the MODEL-AD Consortium

Characterizing the APOE4/Trem2R47H Mouse Model for Late Onset Alzheimer’s Disease
Harriet Williams on behalf of the MODEL-AD Consortium

Investigation of the graphene-on-silicon-carbide and CVD graphene as a basis for bioimpedance sensor applications
Natalja Sleptsuk (a), Raul Land (a), Jana Toompuu (a), Alexander Lebedev (b), Valery Davydov (b), Ilya Eliseyev (b), Evgenia Kalinina (b), Oleg Korolkov (a) and Toomas Rang (a)

Unique Users-Initiated Biotransformation Reactions for Analysis of Xenobiotic Metabolism
Richard Lee, Rytis Kubilius, Vitaly Lashin, Alexandr Sakharov, Anne Marie Smith