BMSS, September 3-5, 2019 | ACD/Labs
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September 3-5, 2019
Royal Northern College of Music, Manchester, UK

Poster Schedule

Efficient Identification and Management of Degradant Data in Process Development
Veronica Paget, Andrew Anderson, Sanjivanjit K. Bhal, Joe DiMartino

During drug development an appreciable amount of time and effort is spent on chromatographic method design. Forced degradation studies (stress tests) are carried out to build a stability-indicating method (SIM) for the active pharmaceutical ingredient (API). Theoretical degradants are used by scientists for targeted analysis in forced degradation studies. Often this vital chemical information is disconnected from observed degradant data, making the identification of impurities and degradants challenging and thereby slowing down this process.

Analytical data assembled for Agomelatine, synthesized by a five-stage process route, was used in this work. The data was collected on an Agilent-1200-Series with an Agilent VWD-G1314B UV detector, acquiring spectra at 210 nm, and an Agilent 6110 Quadrupole API-ES Mass Spectrometer, collecting low resolution spectra in a 45-1000 Da mass range. Column separation was performed via an isocratic method using an ammonium formate Buffer H of 4.5/CAN (35:65). The flow rate was 1.2 mL/min with a run time of 50 min, and the column used was a Zorbax Eclipse XDB C18 5 μm – 4.6 x 150 mm. The software application Luminata™ (v2018.2), based on the ACD/Spectrus Platform, was utilized to manage analytical and chemical data for the process.

Luminata was developed specifically to address challenges associated with identifying impurities and degradants during pharmaceutical SIM development. A full process map of the API synthetic route, including intermediates and impurities, was created in the software for multiple batches of Agomelatine. ICH degradation study guidelines were applied in Luminata to visualize various Agomelatine degradation pathways, and theoretical degradants generated as an *.sdf list, while observed degradants were uploaded as an *.sk2 file. All associated LC/UV/MS data were connected to their corresponding entities and stages to consolidate synthesis information in a single repository.

Large quantities of data are generated in route development for an API. While scientists have designed processes to document and understand forced degradants associated with the API, this knowledge remains disconnected from experimental sources and is often distributed across a variety of systems. Luminata enables predicted degradants, with all metadata, to be stored with observed degradants. This empowers scientists to conveniently review and analyze stress test data in a single application, and identify degradants more efficiently.