Raw material variability of an active pharmaceutical ingredient and its relevance for processability in secondary continuous pharmaceutical manufacturing

Past, current, and future: Application of image analysis in small molecule pharmaceutical development

The often-perceived limitations of application of image analysis have for many years impeded the widespread application of such systems as first line characterisation tools. Image analysis has, however, undergone a notable resurgence in the pharmaceutical industry fuelled by developments system capabilities and the desire of scientists to characterize the morphological nature of their particles more adequately. The importance of particle shape as well as size is now widely acknowledged. With the increasing use of modelling and simulations, and ongoing developments though the integration of machine learning and artificial intelligence, the utility of image analysis is increasing significantly driven by the richness of the data obtained. Such datasets provide means to circumvent the requirement to rely on less informative descriptors and enable the move towards the use of whole distributions. Combining the improved particle size and shape measurement and description with advances in modelling and simulations is enabling improved means to elucidate the link between particle and bulk powder properties. In addition to improved capabilities to describe input materials, approaches to characterize single components within multicomponent systems are providing scientists means to understand how their material may change during manufacture thus providing a means to link the behaviour of final dosage forms with the particle properties at the point of action. The aim is to provide an overview of image analysis and update readers with innovations and capabilities to other methods in the small molecule arena. We will also describe the use of AI for the improved analysis using image analysis.

Ten years of the manufacturing classification system: a review of literature applications and an extension of the framework to continuous manufacture

The MCS initiative was first introduced in 2013. Since then, two MCS papers have been published: the first proposing a structured approach to consider the impact of drug substance physical properties on manufacturability and the second outlining real world examples of MCS principles. By 2023, both publications had been extensively cited by over 240 publications. This article firstly reviews this citing work and considers how the MCS concepts have been received and are being applied. Secondly, we will extend the MCS framework to continuous manufacture. The review structure follows the flow of drug product development focussing first on optimisation of API properties. The exploitation of links between API particle properties and manufacturability using large datasets seems particularly promising. Subsequently, applications of the MCS for formulation design include a detailed look at the impact of percolation threshold, the role of excipients and how other classification systems can be of assistance. The final review section focusses on manufacturing process development, covering the impact of strain rate sensitivity and modelling applications. The second part of the paper focuses on continuous processing proposing a parallel MCS framework alongside the existing batch manufacturing guidance. Specifically, we propose that continuous direct compression can accommodate a wider range of API properties compared to its batch equivalent.

UV-VIS imaging-based investigation of API concentration fluctuation caused by the sticking behaviour of pharmaceutical powder blends

Surface powder sticking in pharmaceutical mixing vessels poses a risk to the uniformity and quality of drug formulations. This study explores methods for evaluating the amount of pharmaceutical powder mixtures adhering to the metallic surfaces. Binary powder blends consisting of amlodipine and microcrystalline cellulose (MCC) were used to investigate the effect of the mixing order on the adherence to the vessel wall. Elevated API concentrations were measured on the wall and within the dislodged material from the surface, regardless of the mixing order of the components. UV imaging was used to determine the particle size and the distribution of the API on the metallic surface. The results were compared to chemical maps obtained by Raman chemical imaging. The combination of UV and VIS imaging enabled the rapid acquisition of chemical maps, covering a substantially large area representative of the analysed sample. UV imaging was also applied in tablet inspection to detect tablets that fail to meet the content uniformity criteria. The results present powder adherence as a possible source of poor content uniformity, highlighting the need for 100% inspection of pharmaceutical products to ensure product quality and safety.

A Rational Hierarchy to Capture Raw Material Attribute Variability in the Pharmaceutical Drug Product Development and Manufacturing Lifecycle

Assessing the robustness of a drug product formulation and manufacturing process to variations in raw material (RM) properties is an essential aspect of pharmaceutical product development. Motivated by the need to demonstrate understanding of attribute-performance relationships at the time of new product registration and for subsequent process maintenance, we review practices to explore RM variations. We describe limitations that can arise when active ingredients and excipients invariably undergo changes during a drug product lifecycle. Historical approaches, such as Quality-by-Design (QbD) experiments, are useful for initial evaluations but can be inefficient and cumbersome to maintain once commercial manufacturing commences. The relatively miniscule data sets accessible in product development - used to predict response to a hypothetical risk of variation - become less relevant as real-world experience of actual variability in the commercial landscape grows. Based on our observations of development and manufacturing, we instead propose a holistic framework exploiting a hierarchy of RM variability, and challenge this with common failure modes. By explicitly incorporating higher ranking RM variations as perturbations, material-conserving experiments are shown to provide powerful and enduring robustness data. Case studies illustrate how correctly contextualizing such data in formulation and process development can avoid the traps of historical QbD approaches and become valuable for evaluating changes occurring later in the drug product lifecycle.

Design space determination of pharmaceutical processes: Effects of control strategies and uncertainty

The identification of process Design Space (DS) is of high interest in highly regulated industrial sectors, such as pharmaceutical industry, where assurance of manufacturability and product quality is key for process development and decision-making. If the process can be controlled by a set of manipulated variables, the DS can be expanded in comparison to an open-loop scenario, where there are no controls in place. Determining the benefits of control strategies may be challenging, particularly when the available model is complex and computationally expensive - which is typically the case of pharmaceutical manufacturing. In this study, we exploit surrogate-based feasibility analysis to determine whether the process satisfies all process constraints by manipulating the process inputs and reduce the effect of uncertainty. The proposed approach is successfully tested on two simulated pharmaceutical case studies of increasing complexity, i.e., considering (i) a single pharmaceutical unit operation, and (ii) a pharmaceutical manufacturing line comprised of a sequence of connected unit operations. Results demonstrate that different control actions can be effectively exploited to operate the process in a wider range of inputs and mitigate uncertainty.

Morphological distribution mapping: Utilisation of modelling to integrate particle size and shape distributions

The aim of this work was to develop approaches to utilize whole particle distributions for both particle size and particle shape parameters to map the full range of particle properties in a curated dataset. It is hoped that such an approach may enable a more complete understanding of the particle landscape as a step towards improving the link between particle properties and processing behaviour. A 1-dimensional principal component analysis (PCA) approach was applied to create a 'morphological distribution landscape'. A dataset of imaged APIs, intermediates and excipients encompassing particle size, particle shape (elongation, length and width) and distribution shape was curated between 2008 and 2022. The curated dataset encompassed over 200 different materials, which included over 150 different APIs, and approximately 3500 unique samples. For the purposes of the current work, only API samples were included. The morphological landscape enables differentiation of materials of equivalent size but varying shape and vice versa. It is hoped that this type of approach can be utilised to better understand the influence of particle properties on pharmaceutical processing behaviour and thereby enable scientists to leverage historical knowledge to highlight and mitigate risks associated to materials of similar morphological nature.

Smart Specification Setting for Dry Powder Inhalation Carriers

The specifications of excipients are important to pharmaceutical manufacturers to ensure that the final product can be manufactured robustly over the entire lifecycle of a drug product. Particle size specifications are key for dry powder inhalation excipients and they should be agreed between users and suppliers. The current paper evaluates two development strategies to set particle size specifications. It is shown that the application of quality-by-design principles to specification setting could result in broader specifications, while it guarantees that efficacy, safety and manufacturing of the medication is not affected. A multitude of reasons exist to keep specifications broader than the production capability range, including improved risk-mitigation and potentially reduced regulatory challenges during and after registration.

Development and Validation for Quantitative Determination of Genotoxic Impurity in Gemfibrozil by Gas Chromatography with Mass Spectrometry

All regulatory organizations are paying close attention to the identification and measurement of genotoxic contaminants. Using conventional analytical techniques like high-performance liquid chromatography (HPLC) and gas chromatography to quantify probable genotoxic substances (PGIs) at the trace level is difficult (GC). Therefore, there is a necessity for advanced analytical techniques for the development of highly sensitive analytical procedures for the determination of trace-level PGIs in drug products and drug substances. This study’s goal is to develop and evaluate an analytical technique for measuring allyl chloride, a possible genotoxic contaminant in gemfibrozil. For the detection of very low and trace levels of impurities, a gas chromatography with a triple quadrupole mass spectrometry detector (GC-MS/MS) approach was developed and validated. Using a column USP phase G27, a nonpolar and low bleed 5% diphenyl, 95% dimethylpolysiloxane, with dimensions of 30 m in length, 0.32 mm internal diameters, and 1.5 m film thickness, along with a flow rate of 2.0 mL/min and Helium (He) as a carrier gas, this method uses a thermal gradient elution program. The method was calibrated with a linearity range from 30% to 150% concentration with respect to the specification level and achieved a limit of detection (LOD) and limit of quantification (LOQ) were 0.005 ppm and 0.01 ppm, respectively, for allyl chloride. According to current ICH requirements, the method was validated, and it was discovered to be specific, exact, accurate, linear, sensitive, tough, robust, and stable. This method is suitable for determining allyl chloride in the regular analysis of Gemfibrozil.

Direct Tableting on a Continuous Manufacturing Line-Impact of Mixing Parameters, Material Densities, and Drug Load on Subsequent Process Parameters and Tablet Quality

The continuous manufacturing (CM) of solid oral dosage forms has received increased attention in recent years and has become a leading technology in the pharmaceutical industry. A model has been developed based on process data from two design of experiments (DoEs), where the impact of the mixer process parameters, throughput (THR), hold up mass (HUM), impeller speed (IMP), and the input raw material bulk density (BD_i), on the continuous process and the resulting drug product has been investigated. These statistical models revealed equations, describing process parameter interactions for optimization purposes. For the exit valve opening width (EV) at the bottom of the continuous mixer (CMT), the combination of high throughput (30 kg/h) and low impeller speed (300 rpm) resulted in optimal process conditions. Apparent bulk density of the blend (BD) within the process, fill depth (FD), and tensile strength (TS) were mainly impacted by input bulk density (BD_i) of the tableting mixture, emphasizing the role of material attributes on the continuous manufacturing process. The apparent bulk density itself was, other than from the input bulk density, equally dependent from THR and IMP in opposite deflections. However, process parameters (THR and IMP) revealed a minor impact on the apparent BD compared to the input bulk density. FD was impacted mainly by THR ahead of IMP and the TS by IMP and THR to a similar extend, in opposite deflections. A simplified linear model to estimate the input bulk density revealed satisfactory prediction quality when included in the derived statistical model equations.

Control Strategy for Excipient Variability in the Quality by Design Approach Using Statistical Analysis and Predictive Model: Effect of Microcrystalline Cellulose Variability on Design Space

Although various quality by design (QbD) approaches have been used to establish a design space to obtain robust drug formulation and process parameters, the effect of excipient variability on the design space and drug product quality is unclear. In this study, the effect of microcrystalline cellulose (MCC) variability on drug product quality was examined using a design space for immediate-release tablets of amlodipine besylate. MCC variability was assessed by altering the manufacturer and grade. The formulation was developed by employing the QbD approach, which was optimized using a D-optimal mixture design. Using 36 different MCCs, the effect of MCC variability on the design space was assessed. The design space was shifted by different manufacturers and grades of MCC, which resulted in associations between the physicochemical properties of MCC and critical quality attributes (CQAs). The correlation between the physicochemical properties of MCCs and CQAs was assessed through a statistical analysis. A predictive model correlating the physicochemical properties of MCCs with dissolution was established using an artificial neural network (ANN). The ANN model accurately predicted dissolution with low absolute and relative errors. The present study described a comprehensive QbD approach, statistical analysis, and ANN to comprehend and manage the effect of excipient variability on the design space.

In-Depth Understanding of Granule Compression Behavior under Variable Raw Material and Processing Conditions

Tablet manufacturing involves the processing of raw materials through several unit operations. Thus, the mitigation of input-induced variability should also consider the downstream processability of intermediary products. The objective of the present work was to study the effect of variable raw materials and processing conditions on the compression properties of granules containing two active pharmaceutical ingredients (APIs) and microcrystalline cellulose. Differences in compressibility and tabletability of granules were highlighted in function of the initial particle size of the first API, granule polydispersity and fragmentation. Moreover, interactions were underlined with the atomizing pressure. Changing the supplier of the second API was efficiently controlled by adapting the binder addition rate and atomizing pressure during granulation, considering the starting crystal size. By fitting mathematical models on the available compression data, the influence of diluent source on granule compactibility and tabletability was identified. These differences resumed to the ease of compaction, tableting capacity and pressure sensitivity index due to variable water binding capacity of microcrystalline cellulose. Building the design space enabled the identification of suitable API types and the appropriate processing conditions (spray rate, atomizing pressure, compression force) required to ensure the desired tableting performance.

The Effect of Binder Types on the Breakage and Drying Behavior of Granules in a Semi-Continuous Fluid Bed Dryer after Twin Screw Wet Granulation

Current study investigated the effect of different binder types on the granule drying process and the granule breakage behavior in a semi-continuous fluid bed dryer integrated in the C25 ConsiGma-system. The studied binders (i.e. hydroxypropyl pea starch, hydroxypropyl methylcellulose E15, polyvinylpyrrolidone K12, and starch octenyl succinate CO 01) required different liquid amounts to produce similar granule quality. These different liquid requirements were translated into different drying conditions for each binder to result in sufficiently dry granules at the end of a drying cycle. By comparing the size distribution of the granules before entering and after exiting the fluid bed dryer, granule breakage could be evaluated. No effect of the binder type on the granule breakage during drying was observed. However, differences in granule breakage were observed for the binders when processed with the horizontal set-up of the C25 system, as granule breakage during pneumatic transport depended on the binder type. Only one binder (hydroxypropyl pea starch) allowed to avoid granule breakage during the entire process. Furthermore, this research showed that the drying process was mainly steered by the liquid requirements for granulation, and that these liquid requirements depended on the binder used.

Continuous Twin Screw Granulation: A Review of Recent Progress and Opportunities in Formulation and Equipment Design

Continuous twin screw wet granulation is one of the key continuous manufacturing technologies that have gained significant interest in the pharmaceutical industry as well as in academia over the last ten years. Given its considerable advantages compared to wet granulation techniques operated in batch mode such as high shear granulation and fluid bed granulation, several equipment manufacturers have designed their own manufacturing setup. This has led to a steep increase in the research output in this field. However, most studies still focused on a single (often placebo) formulation, hence making it difficult to assess the general validity of the obtained results. Therefore, current review provides an overview of recent progress in the field of continuous twin screw wet granulation, with special focus on the importance of the formulation aspect and raw material properties. It gives practical guidance for novel and more experienced users of this technique and highlights some of the unmet needs that require further research.

Effect of Spray Drying Conditions on Physical Properties of Panax notoginseng Saponin (PNS) Powder and the Intra-Batch Dissolution Variability of PNS Hydrophilic Matrix Tablet

Purpose

Understanding raw material variability and its impact on product quality are crucial for developing robust pharmaceutical processes. This work aimed to study the effects of spray drying conditions on properties of the spray dried Panax notoginseng saponin (PNS) powders as well as the subsequent intra-batch dissolution variability of PNS hydrophilic matrix tablets.

Methods

The Plackett-Burman design was applied to screen the critical process parameters (CPPs). Then, the Box-Behnken design was used to investigate the relationship between the CPPs and the physiochemical properties of spray dried PNS powders. The PNS hydrophilic matrix tablets containing 57% spray dried PNS powders were directly compressed. The partial least squares (PLS) regression was used to uncover the hidden multivariate relationships among the CPPs, intermediate powder properties, and tablet quality attributes.

Results

The identified CPPs were the feed concentration, the inlet air temperature, and the atomization pressure. It was found that the CPPs exerted little impact on chemical properties of spray dried PNS powders, but had significant impact on physical properties, such as particle size, specific surface area, bulk density, hygroscopicity, and inter-particle porosity, etc. Latent variable modeling results revealed that the high inlet air temperature of spray drying process could produce PNS powders with low moisture content and high hygroscopicity, which were beneficial to reduce the intra-batch dissolution variability of PNS hydrophilic matrix tablets. Finally, a design space of the spray drying process was built in order to ensure the dissolution consistency.

Conclusion

Our research provided a reference for improving the spray drying conditions in order to ensure the dissolution consistency of the PNS hydrophilic matrix tablet.

Recent progress in continuous manufacturing of oral solid dosage forms

Continuous drug product manufacturing is slowly being implemented in the pharmaceutical industry. Although the benefits related to the quality and cost of continuous manufacturing are widely recognized, several challenges hampered the widespread introduction of continuous manufacturing of drug products. Current review presents an overview of state-of-the art research, equipment, process analytical technology implementations and advanced control strategies. Additionally, guidelines and regulatory viewpoints on implementation of continuous manufacturing in the pharmaceutical industry are discussed.

Effect of raw material variability of glipizide on the in vitro dissolution rate and in vivo bioavailability performance: The importance of particle size

The objective of this study was to understand the impact of active pharmaceutical ingredients (API) particle size on a re-developed generic product of glipizide and to improve its formulation so that it exhibits bioequivalent to that of the reference listed drug (RLD). Two commercial batches of APIs (API-1 and API-2) with the same polymorphism and one batch of home-made APIs (API-3) with super-small particle size were used in the present study. The in vitro dissolution profiles of the tested formulations were compared with the RLD in a series of dissolution media. Then, the impact of particle size on in vivo absorption was evaluated in Beagle dogs. Compared with the RLD, formulation A with larger API size showed slower dissolution in pH 6.0 and 7.4 medium, resulting bioinequivalent with the RLD. Conversely, formulation B with smaller API size demonstrated similar in vitro dissolution profiles with the RLD and thus exhibited bioequivalent in the present study. Furthermore, formulation C with super small particle size still exhibited identical oral absorption although rapid dissolution was observed in the tested condition. Herein, it indicated that 2-5 µm might be defined as the "inert size range" of glipizide for ensuring the bioequivalence with the RLD. The results in the present study might help to obtain a better understanding of the variability in raw materials for oral absorption, develop a bioequivalent product and thus post-market quality control.

Managing API raw material variability in a continuous manufacturing line - Prediction of process robustness

Many studies on continuous twin-screw granulation only focus on the granulator without linking this process step to the upstream and downstream unit operations. Product critical quality attributes (CQAs) are however not only determined by the granulation step. In this study, the possibility to manage the batch-to-batch variability of an active pharmaceutical ingredient (API) in a high drug loaded formulation on a continuous line was investigated to obtain consistent tablet CQAs. As the ultimate goal of continuous manufacturing is to produce 24/7, current study also aimed at guaranteeing long term stability of the process. To do so, previously identified API critical material attributes (CMAs) were varied together with granulation, drying and milling critical process parameters (CPPs) in a screening design of experiments to understand the influence of these factors upon product CQAs and process stability. To evaluate the factors affecting the process stability with a reduced amount of materials, process deviations recorded by process sensors were used. While product CQAs only depended on process CPPs, process stability was strongly affected by API CMAs. The effect of API batch-to-batch variability on process stability could nonetheless be managed by applying suitable granulation conditions. Therefore, appropriate ranges of CPPs were defined to ensure both product CQAs and process stability. By studying the fully integrated continuous manufacturing line, it was possible to highlight the interactions between the different unit operations and the API CMAs and to design a robust process.

Deriving control parameter settings from process models to control capsule fillers integrated into continuous manufacturing

The aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.

Data analytics on raw material properties to accelerate pharmaceutical drug development

Manufacturability of active pharmaceutical ingredients (APIs) is often evaluated by an empirical approach during development due to limited material availability. This brings challenges in designing flexible yet robust manufacturing processes under highly accelerated timelines. Hence, good utilisation of a limited material dataset is key to accelerate the delivery of high quality final drug product into the market at minimum cost and maximum process capacity. In this study, we present a data-driven method to investigate a raw materials database where the integration of multivariate analysis and machine learning modelling aids the selection of new incoming materials based on their manufacturability. The procedure was applied to an industrial representative database of thirty-four APIs and seven excipients where eight measurements relevant to flow properties for each of those forty-one materials were collected. The models identified four clusters of materials with different flow properties. These models can serve as a risk assessment tool for new API in early product development phases based on the nearest surrogate material which behave similarly, as well as to identify targeted and material sparring experiments to address key risks during secondary process selection.

The coupling of in-flow reaction with continuous flow seedless tubular crystallization

The direct coupling between a continuous flow-assisted acetylation reaction of salicylic acid and the subsequent crystallisation of aspirin in a continuous flow tubular reactor or nucleator is investigated. A mean crystal size between 3 and 300 μm is obtained upon changing the nucleation temperature.

Managing active pharmaceutical ingredient raw material variability during twin-screw blend feeding

Continuous powder feeding is a critical step in continuous manufacturing of solid dosage forms, as this unit operation should ensure the mass flow consistency at the desired powder feed rate to guarantee the process throughput and final product consistency. In this study, twin-screw feeding of a pharmaceutical formulation (i.e., blend) existing of a highly dosed very poorly flowing active pharmaceutical ingredient (API) leading to insufficient feeding capacity was investigated. Furthermore, the API showed very high batch-to-batch variability in raw material properties dominating the formulation blend properties. Formulation changes were evaluated to improve the flowability of the blends and to mitigate the impact of API batch-to-batch variability on the twin-screw feeding. Herewith, feeding evaluation tests and an extensive material characterization of the reformulated blends were performed to assess the impact of the formulation changes upon continuous twin-screw feeding. The transfer of the glidant from extra-granular to intra-granular phase allowed to improve the flowability of the blends. A sufficient feeding capacity for the downstream process and a mitigation of the impact of batch-to-batch variability of the API upon twin-screw feeding of the blends could be achieved. No effect of the formulation or of the API properties on the feeding stability was observed. The material characterization of the blends allowed identifying the material attributes which were critical for continuous twin-screw feeding (i.e., bulk density, mass charge and powder cohesiveness).

Manufacturing classification system in the real world: factors influencing manufacturing process choices for filed commercial oral solid dosage formulations, case studies from industry and considerations for continuous processing

Following the first Manufacturing Classification System (MCS) paper, the team conducted surveys to establish which active pharmaceutical ingredient (API) properties were important when selecting or modifying materials to enable an efficient and robust pharmaceutical manufacturing process. The most commonly identified factors were (1) API particle size: small particle sizes are known to increase risk of processing issues; (2) Drug loading in the formulation: high drug loadings allow less opportunity to mitigate poor API properties through the use of excipients. The next step was to establish linkages with process decisions by identifying publicly-available proxies for these important parameters: dose (in place of drug loading) and BCS class (in place of particle size). Poorly-soluble API were seen as more likely to have controlled (smaller) particle size than more highly soluble API. Analysis of 435 regulatory filings revealed that higher doses and more poorly-soluble API was associated with more complex processing routes. Replacing the proxy factors with the original parameters should give the opportunity to demonstrate stronger trends. This assumption was tested by accessing a dataset relating to commercial tablet products. This showed that, for dry processes, a larger particle size was associated with higher achievable drug loading as determined by percolation threshold.

Enhanced Understanding of Pharmaceutical Materials Through Advanced Characterisation and Analysis

The impact of pharmaceutical materials properties on drug product quality and manufacturability is well recognised by the industry. An ongoing effort across industry and academia, the Manufacturing Classification System consortium, aims to gather the existing body of knowledge in a common framework to provide guidance on selection of appropriate manufacturing technologies for a given drug and/or guide optimization of the physical properties of the drug to facilitate manufacturing requirements for a given processing route. Simultaneously, material scientists endeavour to develop characterisation methods such as size, shape, surface area, density, flow and compactibility that enable a stronger understanding of materials powder properties. These properties are routinely tested drug product development and advances in instrumentation and computing power have enabled novel characterisation methods which generate larger, more complex data sets leading to a better understanding of the materials. These methods have specific requirements in terms of data management and analysis. An appropriate data management strategy eliminates time-consuming data collation steps and enables access to data collected for multiple methods and materials simultaneously. Methods ideally suited to extract information from large, complex data sets such as multivariate projection methods allow simpler representation of the variability contained within the data and easier interpretation of the key information it contains. In this review, an overview of the current knowledge and challenges introduced by modern pharmaceutical material characterisation methods is provided. Two case studies illustrate how the incorporation of multivariate analysis into the material sciences workflow facilitates a better understanding of materials.