Ingredient-Specific Particle Sizing
ChemImage contract pharmaceutical services can provide you with ingredient-specific particle sizing (ISPS) for your drug development projects. Our ISPS method provides simultaneous spatial information (size, distribution, shape) and spectral information (chemical identification of particles) that is key to measuring the drug particle size distribution within nasal, inhalable, semi-solid, transdermal drug delivery systems. This technique addresses the need for a fundamental understanding of API particles in the presence of other undissolved excipients in the formulation and can be used to study ISPS, aggregation and dispersion characteristics.
- Drug particle size distribution (PSD)
- Drug PSD measurements faster than optical microscopy and other methods combined
- Easy identification and analysis of aggregates
- Automated identification of drug substance
- Critical support for in vitro bioequivalence testing
Traditionally it has been a challenge to determine drug particle size distribution (PSD) in a nasal spray suspension or inhalation drug products containing more than one drug substance. Using ChemImage (ISPS) this information is now easily attainable.
Nasal sprays formulated as suspensions typically contain micronized drug substance within large droplets, and in the presence of multiple excipient materials. Formulators and researchers can use Raman Chemical Imaging (RCI) to can obtain drug-specific PSD (or other ingredient-specific particle size) information of pharmaceutical nasal spray suspensions, aerosols and other metered-dose inhalers. This measurement gives you critical information to compare the specific size, shape and distribution of one or more active ingredients.
ChemImage contract pharmaceutical services provide an in vitro test method which saves time, increases reproducibility and precision in addition to being cost-effective. Now you can reduce development costs, speed up the approvals of abbreviated and new drug applications, and enter to in vivo biostudies with greater confidence in your pre-clinical data, effectively lowering risk of failure.
