Pharmaceutical Excipient Characterization

The aim of formulation development is to design a product and its manufacturing process to consistently deliver the intended Quality Target Product Profile (QTPP). This involves determining the Critical Quality Attributes (CQAs) for the Active Pharmaceutical Ingredient (API) and excipients that define the performance of the product. These are generally identified through an assessment of the extent to which the variation in a specific attribute, for example particle size, can impact the drug product’s quality and performance.

Introduction

The aim of formulation development is to design a product and its manufacturing process to consistently deliver the intended Quality Target Product Profile (QTPP). This involves determining the Critical Quality Attributes (CQAs) for the Active Pharmaceutical Ingredient (API) and excipients that define the performance of the product. These are generally identified through an assessment of the extent to which the variation in a specific attribute, for example particle size, can impact the drug product’s quality and performance.

With reference to the excipient, guidance from the FDA and USP encourages identification of the CQAs for excipients and the setting of associated quality controls [1]. Changes in the physical characteristics of an excipient may impact its interaction with other formulation components and thereby have a major impact on the QTPP.

Analytical strategies

The analysis of formulation blends using microscope images is widely employed during the initial stages of product development in order to understand how the physical properties of the excipient correlate with product performance.

Once the CQAs associated with the excipient have been identified, a routine quality control strategy is developed and validated using techniques such as laser diffraction for particle size analysis.

In this application note, lactose is used as an example excipient in order to consider the available guidance in context. Lactose is commercially available in different grades. Selection of a specific grade, or mixing together different grades to obtain an appropriate Particle Size Distribution (PSD), will be guided by its functionality in a particular formulation and how it interacts with the API during processing and final product. [2]

The first case study presented in this application note showcases the use of Morphologically Directed Raman Spectroscopy (MDRS) for component specific morphological analysis of a blend of lactose and API. The second case study presents the use of laser diffraction bulk material characterization tool which can support excipient particle size measurement requirements from formulation development through to QC analysis.

Case Study: Understanding excipient functionality in a formulation

In order to establish the CQAs of an excipient, it is important to understand how the excipient particles interact with other components of the formulation.

Lactose is widely used as a bulking agent in pharmaceutical products. In some cases fine lactose particles bind with the API particles within the formulation to form weak Multi Component Agglomerates (MCA). The presence of MCAs may have an adverse effect on the bioavailability of the final product. Alternatively, this type of agglomeration may prevent the formation of strongly bound API-API particle agglomerates during processing, helping to improve the content uniformity and bioavailability of the final product [2]. Selection of the most appropriate lactose PSD is therefore important to control its interaction with the API and ultimately achieve the product’s QTPP.

One way to understand the interaction between an excipient and the API in a formulation is to use the technique of Morphologically Directed Raman Spectroscopy (MDRS). MDRS is a relatively new technique which combines automated image analysis with the chemical identification capabilities of Raman spectroscopy. MDRS systems (Morphologi-ID) enable the identification of the components present in a formulation blend and discrete determination of their individual morphological properties.

In this example, the preliminary analysis of a blend of lactose with an API using MDRS revealed the presence of API-lactose-MCAs. Figure 1 shows an overlay of the spectrum of the agglomerate with the spectra of pure lactose and pure API, and confirms that the agglomerate spectrum has features which resemble both pure substances, which help confirm that it is an MCA.

Figure 1: Raman spectrum (black) for a particle recorded using the MDRS (Morphologi-ID) system. The spectrum contains features which resemble both lactose and the API particle, which reveals agglomeration between these two particles to produce MCAs
MRK2093_fig01

In order to engineer or control the extent of agglomeration between these two particle types, it is first important to fully understand the nature of this interaction. In this case all the particles targeted for Raman spectroscopy were chemically classified according to the correlation scores of their spectra with the spectrum of pure particles. The system then produced a component specific particle size distribution as shown in figure 2.

Figure 2: Overlay of number based particle size distribution; API particles (red), Lactose (green) and MCAs (Blue)
MRK2093_fig02

These data show that the lactose particles are considerably larger in size than the API particles and the MCAs are slightly smaller in size than the API particles on their own. This suggests that fine API particles are interacting with fine lactose particles to form MCAs.

The link between product performance and ratio of each of the three particles types present at the blending stage (figure 3) can be further studied to provide insights to engineer the best combination for maximum bioavailability, API stability or processability of the blend.

Figure 3: Relative composition of each individual class of particles analyzed in the blend using the MDRS (Morphologi-ID) system
MRK2093_fig03

Case Study: Monitoring Excipient Blending

The use of MDRS can help formulation scientists to identify the optimum particle size distribution for an excipient. However, the link between the excipient particle size and product performance can only be established if the particle size of the excipient is controlled.

One technique which can be used for excipient characterization is laser diffraction. Its wide dynamic range and submicron performance enables it to characterize many different excipient grades and blends. Relatively large sample sizes can be characterized using laser diffraction, ensuring that the results obtained are reproducible and represent the properties of the bulk material. Rapid measurements and a simple set up make it an ideal technique for routine Quality Control (QC) as well as Research and Development (R&D).

In this case study, a series of blends were prepared from two different grades of commercially available lactose (table 1). These were individually analyzed using laser diffraction (Mastersizer 3000).

Table1: Ratio of blends of Lactose with 10 µm to 100 µm particle size
Blend numberLH300 (Dv50 10 mm )LH100 (Dv50 100 mm )
11%99%
25%95%
310%90%
420%80%
530%70%
650%50%

The undersize distribution plots shown in Figure 4 highlight the sensitivity of laser diffraction in accurately determining variations in particle size distribution across all of the blends detailed in table 1. The system correctly detects the increase in the fines content as the blend is changed. This suggested that laser diffraction can be realistically applied to supporting excipient selection during formulation development.

Figure 4: Undersize particle size distribution data for the lactose blends described in table 1.
MRK2093_fig04

Once the optimum lactose PSD has been established, a validated method is required to support QC during routine manufacturing. According to USP guidance for the validation of physical property methods, the linearity of response of a technique should be gauged [3]. In this case, the requirement would be for the response of the particle size distribution measurement system to be linear to changes in the fine particle fraction within the blend.

Considering the lactose example above, the trend plot in Figure 5 shows how the percentage volume of particles less than 30 µm in size changes with respect to the proportion of the fine lactose component in the blends which were analyzed. A linear regression coefficient suggests that the laser diffraction system responds correctly to changes in the blend composition.

Figure 5: Plot showing how the volume percent below 30 µm in size changes with the percentage of the fine grade lactose (LH300) within the blends.
MRK2093_fig05

These data signify that laser diffraction is an effective tool not only for supporting R&D, but also during routine QC testing required further ahead in the manufacturing of pharmaceutical formulations.

Conclusion

Formulation development involves identifying the CQAs, such as particle size distribution, of the API and excipients that define the performance of a product. The application note considers the use of MDRS alongside laser diffraction at this critical stage of development.

MDRS not only allows component specific particle size distributions to be measured for a formulation blend, but also enables the formulation scientist to understand the nature of interaction between an excipient and API. The data produced can be used to understand the effect of variations in the excipient PSD have on this interaction.

In order to control the particle size distribution of the excipient, an accurate and reproducible bulk material characterization tool, such as laser diffraction, is required. Due to its wide dynamic range, rapid results and simple set up, laser diffraction supports product development from the formulation development stage right through to routine QC at the manufacturing stage.

References

  1. USP Guideline for Submitting Requests for Revision to USP-NF V3.1 April 2007
  2. Matthew D. Jones and Robert Price, “The Influence of Fine Excipient Particles on the Performance of Carrier-Based Dry Powder Inhalation Formulations”, Pharmaceutical Research, Vol. 23, No8, August 2006
  3. USP <1225> Validation of Compendial Procedures / General Information

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