RDD 2016: API-Specific Particle Size Distribution and Agglomerate Analysis using the rap.ID Single Particle Explorer (SPE)

 

The Active Pharmaceutical Ingredient (API) size distribution within the final formulation of a drug product is critical as it relates to bioavailability, rates of absorption, and stability of that drug product. Due to the significant impact, gaining an understanding of this API particle size distribution (PSD) is becoming of greater importance to regulatory agencies. This includes, but is not limited to drug products such as nasal sprays, metered dose inhalers (MDI) and dry powder inhalers (DPI). In addition, bioequivalence (BE) testing for new drug applications (NDAs) and Abbreviated New Drug Applications (ANDAs) often require PSD information [1]. While there are current technologies that can aid in determining the PSD of APIs within drug products, we explored the utility, efficiency and value of utilizing an automated Raman technology.

Automated Raman spectroscopy using the Single Particle Explorer™ (SPE™/rap.ID) has been evaluated as a potential measurement tool for determining the particle size distribution of multiple pharmaceutical product types, including nasal sprays, MDIs and DPIs. The SPE™ combines optical microscopy and Raman spectroscopy to obtain particle size distribution and automated particle characterization of the API, excipients and foreign particulate. In this instance, we have applied the SPE™ technology to characterize the API particle size distribution of representative aerosol products including nasal spray (Mometesone), MDI (Albuterol) and DPI (Fluticasone/Salmeterol) products. The automated data collection, sizing, counting and database searching features of the system allow us to understand the size distribution of a representative population of API particles. The automated Raman collection and subsequent database searching also allows for the identification of various API polymorph types within a sample.

The presence of agglomerated API-API particles and API-excipient particles can significantly affect the interpretation of the data [2]. Methodologies to identify and account for agglomerates should be evaluated when considering an automated methodology for API particle size characterization. The methodology and results for this evaluation will also be described.

 

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