A process control system based on PAT can compensate for variations in particle size, resulting in more consistent coating thickness.
Aug 02, 2018 - By Chris O’Callaghan, Ian Jones, Piyush Patel, Edward Godek - Pharmaceutical Technology - Volume 42, Issue 8, pg 38–41,64
Drug-layered multiparticulates are a common dosage form for extended or modified-release pharmaceutical formulations. Delivered either in capsules, tablets, or as food additives in pediatric or geriatric applications (1), these formulations typically feature a functional coating designed to delay dissolution of the drug in the body.
Wurster coating, using bottom-spray fluid-bed technology, is commonly used to manufacture these formulations, in a multi-phase process. Manufacturing is typically controlled by spraying a fixed quantity of coating factor on the substrate. For a well-developed coating process, spray efficiencies can be highly consistent. However, variability in product quality can often result from raw material variations in the substrate.
This article will discuss research into ways to improve control of the overall process, to minimize substrate raw material and final product variability. In this work, microcrystalline cellulose (MCC) multiparticulates were used as a substitute for a drug-layered substrate and were layered with an aqueous-based enteric coating.
Because coating thickness is the primary critical material attribute influencing dissolution rate (2–4), the goal of this research was to minimize the impact of varying substrate raw material particle size and surface area on the resultant coating thickness. A smart process control system was used in conjunction with process analytical technology (PAT) to monitor and dynamically control key process parameters in order to improve consistency in measured coating thickness at the end of spraying. The automated fluid-bed control system was designed so that the spraying process would stop once a pre-determined coating thickness had been reached that would provide the required dissolution profile.
The approach was demonstrated in application to two different substrate materials, with marginally different particle size characteristics in order to represent real-world raw material variability. Results showed that even a small variation in median diameter can have a significant influence on the total surface area. Experiments documented the differing quantities of coating factor that were required to achieve target growth in each case.
Materials and methods
Materials. Cellets 500 (MCC) (Ingredient Pharm) were used as a substrate material for coating. No API layer was applied for this development study due to processing limitations. A 15% w/w aqueous suspension of 80:20 Surelease:Opadry (Colorcon Inc.) was used to coat the particles. Surelease (aqueous dispersion of ethyl cellulose) was applied as a barrier membrane coating on the Cellets while Opadry (a hypromellose-based coating system) acted as a pore former in the coating formulation.
The Cellets 500 (approximately 500–710 µm) were screened with a 600-µm sieve to create two populations of marginally different sizes (approximately 67-µm difference in Dv50, which is a measure of the volumetric median particle diameter). Both populations fall within the material specification for Cellets 500 and may be considered to represent a batch-to-batch variation for this application.
Three batches of each size were coated to establish the repeatability of results. The three batches of larger size pellets are referred to as L1, L2, and L3, and the three batches of smaller material are referred to as S1, S2, and S3.
Equipment. Wurster coating was conducted in a Glatt GPCG2 lab-scale fluid-bed system with a six-inch, PAT-compatible, bottom-spray product container. A Schlick 0.8-mm nozzle was used to spray the coating solution with a 4.5-mm air-collar spacing. A type-B orifice plate was used for appropriate fluidization, with a Wurster column height of 25 mm.
The Eyecon2 Direct Optical Imaging Particle Analyser (Innopharma Technology) was used for real-time measurement of the particle size distribution inline, through the lowest window of the product container, as shown in Figure 1. Direct imaging involves capturing images of the particles in-process through the window/inspection port, and running these through a series of image analysis steps to measure the size and shape of each particle present. Analysis parameters were set to fluid-bed coating defaults, with a results integration period of 120 seconds to optimize data for smooth process control.
By Chris O’Callaghan, Ian Jones, Piyush Patel, Edward Godek
Pharmaceutical Technology
Volume 42, Issue 8, pg 38–41,64