Presented at the 12th World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology, 2021
Introduction
Mannitol is a widely used excipient due to the near absence of reducing sugars, combined with a negligible hygroscopicity and the absence of amorphous state. Certainly, for this reason, the Ph. Eur. recommends the use of mannitol for filling hard shell capsules.
There are several mannitol grades available commercially, possessing different material attributes such as particle size distribution, density and flow properties.1 Fluctuations of the powder properties might have an impact on the machinability and the quality of the filled capsules.2 Especially variations in bulk density of mannitol are considered as critical factor in magisterial formulations. Thus, its standardization is proposed by the DAC (NRF p. 38) by using blends of mannitol and silica with stable density. Mannitol is known to provide high friction in tableting or by capsules filling, requesting a consequent lubrication.3This study was designed to investigate the process performance of different mannitol grades on a dosing-disc capsule filling machine. The interactions between Critical Process Parameters (CPPs) and Critical Material Attributes (CMAs) are complex due to the large variety of possible machine settings and the differences in powder properties. Many experiments would be needed to test all various possible combinations of factors that impact the final product in terms of Critical Quality Attributes (CQAs) such as uniformity of weight. Thus, the approach is to plan statistically optimized experiments, which is achieved by Design of Experiments (DoE) and perform the trials on a fully automated capsule filling machine4,5 to provide a fast and effective process development for each of the mannitol grades.
Material and Methods
Materials
Four different mannitol grades of PEARLITOL® provided by Roquette Frères, France, have been investigated in this study. The crystalline grades PEARLITOL® 50 C and 160 C obtained from crystallization from water consist exclusively of the β- crystalline form and differ in their particle size. The spray dried grade PEARLITOL® 200 SD designed to have free flowing properties contains two different crystalline forms (α and β). PEARLITOL® Flash is a compound of mannitol and starch and has been selected due to the content of 20% maize starch, which is known to be an effective glidant. Each of the PEARLITOL® grades was blended with 0.5% magnesium stearate (Ligamed MF-2-V, Peter Greven, Germany). Hard gelatin capsules size 4 were supplied by Capsugel (Lonza, France).
Powder characterization
Bulk density (BD) and tapped density (TD) were measured using the jolting volumeter (STAV II, Engelsmann, Germany). The Carr’s compressibility index (CI) was then calculated. The particle size distribution of the powders was determined via laser diffraction (HELOS BR, Sympatec, Germany). For measuring the ejection forces (EF), a quantity of 48 mg of each mannitol grade was filled into a dosing sleeve for capsule size 4 mounted in the measurement set-up of the Texture Analyser (TA.XTplus, Stable Micro Systems, UK). After compaction with 90 N, the powder slug is ejected out of the dosing sleeve while recording the ejection force.
Design of experiments (DoE)
DoE enables to investigate the whole process with a minimum amount of experiments as several factors are varied at the same time. Effects and interactions between potential CPPs and CMAs as well as their impact on CQA can be described. However, it is important to fit the design to the actual process and determine potential CPPs4,5 and their range of variation (table 1). Statistically optimized experiments were planned using Cornerstone (camLine, Germany) resulting in 29 experiments for each mannitol grade.
Table 1. Parameter range for potential CPPs

Capsule filling and automated process development
All trials were performed on the capsule filling machine GKF702 with standard format parts for capsule size 4 and a 5.0 mm dosing disk (Robert Bosch Packaging Technology, Germany). This tamp filling machine was equipped with the setup for automatic adjustment of all process parameters, as described in.4,5 To determine the capsule fill weight and the coefficient of fill weight variation, 400 randomly selected capsules of each trial were weighed automatically on a capsule checkweigher (KKE 1700, Robert Bosch Packaging Technology GmbH, Germany) connected to the GKF702. The mean values and the coefficient of fill weight variation were calculated from the corrected capsule weights.
RESULTS
As obvious from table 2, the four mannitol grades differ in their bulk and tapped densities as well as their flowability and particle size distribution. Among all, PEARLITOL® Flash shows the lowest ejection forces which can be explained by the content of 20% maize starch in the compound. Maize starch is acting as a glidant, reducing the friction between the powder slug and the dosing sleeve.
Table 2. Material attributes of the four mannitol grades.

For the impartial comparison of the different mannitol grades, the statistical process model required 29 experiments for each grade. These experiments were performed within 2 h on the fully automated capsule filling machine. From the bar graphs resulting from the statistical model, it becomes clear that the impact of different CPPs on fill weight and dosing accuracy depends from the CMAs of each mannitol grade.

The dosing accuracy (green) of PEARLITOL® 160C and 200SD is mainly influenced by the tamping pressure. In contrast, the main influencing factor for PEARLITOL® 50C is the powder bed height. The pin immersion depth plays an important role for PEARLITOL® Flash. The fill weight (blue) of PEARLITOL® 50C is mainly affected by the powder bed height. However, for PEARLITOL® 160C, 200SD and Flash, the tamping pressure has a major influence on the mean value.
The algorithm from the statistical process model for each mannitol grade was used to determine the specific process parameters required to achieve a low coefficient of fill weight variation (RSD). The machine settings predicted by the algorithm could be verified by the machine run for each mannitol grade. This validated the statistical process model. The setting of the process parameters for highest dosing accuracy are summarized in table 3. It appears that a powder reveals its qualities only when it is handled with the individual, optimal process parameter settings.
Table 3. Settings of the critical process parameters and capsule filling results for different mannitol grades.

The results show, that all PEARLITOL® grades provide excellent uniformity of fill weight. The RSD for fill weight variation varies between 1.10% and 1.35%. Therefore, a high yield and overall equipment efficiency is anticipated for the capsule filling process.
The results show, that all PEARLITOL® grades provide excellent uniformity of fill weight. The RSD for fill weight variation varies between 1.10% and 1.35%. Therefore, a high yield and overall equipment efficiency is anticipated for the capsule filling process.
Conclusions
This study illuminates the opportunities that a combination of DoE and a high level of automation of the capsule filling process can provide for good process understanding. Once the CPPs are determined and the right settings are chosen, the GKF702 was capable to achieve a high dosing accuracy (RSD below 1.5%) for each of the mannitol grades. In addition, different settings of the CPPs led to excellent filling performance and RSD depending on the material attributes. The compound of mannitol and maize starch and PEARLITOL® Flash provided the best tribolic properties.
Continue reading the original article here
Source: Roquette, website Mannitol performances as capsule filler, Published February 19, 2026, Stéphanie Otterbach, Bernhard Wagner, Olaf Haeusler, Thomas Brinz, Presented at the 12th World Meeting on Pharmaceutics, Biopharmaceutics and Pharmaceutical Technology, 2021
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