Development of a design space and predictive statistical model for capsule filling of low-fill-weight inhalation products

Abstract

The objectives of this study were to develop a predictive statistical model for low-fill-weight capsule filling of inhalation products with dosator nozzles via the quality by design (QbD) approach and based on that to create refined models that include quadratic terms for significant parameters. Various controllable process parameters and uncontrolled material attributes of 12 powders were initially screened using a linear model with partial least square (PLS) regression to determine their effect on the critical quality attributes (CQA; fill weight and weight variability). After identifying critical material attributes (CMAs) and critical process parameters (CPPs) that influenced the CQA, model refinement was performed to study if interactions or quadratic terms influence the model. Based on the assessment of the effects of the CPPs and CMAs on fill weight and weight variability for low-fill-weight inhalation products, we developed an excellent linear predictive model for fill weight (R(2 )= 0.96, Q(2 )= 0.96 for powders with good flow properties and R(2 )= 0.94, Q(2 )= 0.93 for cohesive powders) and a model that provides a good approximation of the fill weight variability for each powder group. We validated the model, established a design space for the performance of different types of inhalation grade lactose on low-fill weight capsule filling and successfully used the CMAs and CPPs to predict fill weight of powders that were not included in the development set.

A Quality by Design Framework for Capsule-Based Dry Powder Inhalers

“…A study by Faulhammer et al, investigated the CPP of the microdosing comparing the performance of different types of powders. The study provided evidence that the accurate filling of 1 -45 mg of DPI powders into capsules depends on processing parameters that can be adjusted for the different types of powders [ 142 ]. Different from dosator systems, tamp filling system is an automated filling system requiring a lower degree of formulation compaction, and is very suitable for loading highly potent compounds [ 143 ].…”

“…In an additional study, they found a correlation between the capsule filling weight and the particle size, the air permeability, and the compressibility. For lower dosed powders, additional critical factors were observed like the wall friction angle, the tapped density, and the particle shape proved to be important factors [ 142 ]. These studies were complemented by Stranzinger et al, who investigated that higher filling speed, the compression ratio of dosing chamber to powder bed height (1:1, rather than > 1:1), and smaller dosator size can result in an increasing filling weight variability in the case of low bulk density (<45 g/mL) lactose with the particle size <10 µm [ 148 ].…”

The Effect of Formulation Variables on the Manufacturability of Clopidogrel Tablets via Fluidized Hot-Melt Granulation—From the Lab Scale to the Pilot Scale

“…It is an integral part of the Process Analytical Technology (PAT) methodology, which aims to improve the understanding, optimization, monitoring, and control of various processes involved in the manufacturing of pharmaceutical products [ 7 ]. Moreover, MVDA proves to be a powerful tool in the modeling and prediction of end products, being an important asset in granulation techniques [ 8 , 9 , 10 , 11 ], various pharmaceutical applications [ 12 , 13 , 14 , 15 ], and the scale-up process (from the laboratory scale to the pilot scale or the pilot scale to the industrial scale) during production development [ 16 , 17 , 18 ].…”

A two-step approach for fluidized bed granulation in pharmaceutical processing: Assessing different models for design and control

“…To provide a mechanistic basis for process understanding, a design of experiment (DoE) approach is recommended. In this approach, a design space with the desired characteristics is established, and the high-risk variables critical to the final product quality are identified [4]. Granulation parameters should be properly controlled in order to obtain high-quality granules.…”