Analyze This

A New Approach to Particle Morphology

The particle size of the API and excipients affects more than just the stability and appearance of the product.

While at IFPAC (N. Bethesda, MD) in March, I noted that particle size, morphology, and physical performance were being highlighted by both speakers and exhibitors. This makes sense for traditional cGMP production of products but becomes more than “nice to know” for PAT and QbD-based production paradigms and pretty much an absolute necessity when producing a solid dosage form via continuous manufacturing (CM). It makes sense, in that case, that we need to begin the characterizing of all materials used in a dosage form even before the formulation is finalized. Fortunately, I ran into a colleague whom I’ve known for over 30 years and grilled him about his new software suite for characterizing particle size and morphology. Since his work in near-infrared (NIR) was well-thought out and his familiarity with Chemometrics and statistics were first rate, I wanted to learn more about his software package.

When developing a new pharmaceutical product, particularly where the delivery mechanism involves a dry power-based active pharmaceutical ingredient (API), particle size is a very important property to understand and control. The particle size of the API and excipients affects more than just the stability and appearance of the product. Particle size can influence properties such as friability, dissolution, bioavailability, release rate, and can even influence manufacturing processes and parameters: in short, all critical to quality (CtQ) parameters.

As important as measuring particle size is, understanding and controlling the particle’s shape or morphology is every bit as critical. A recent example of this importance was seen at a commercial facility, where one batch of API was failing its bioequivalence test. Analysis of this API in comparison to a passing batch, using traditional methods including Laser Light Diffraction (LLD) proved inconclusive as the particle sizes were apparently (to the device) the same.

It wasn’t until the product was analyzed using Image Analysis (IA) that the solution of the situation was found. The morphology of the particles clearly showed a change in aspect ratio, intensity, and area, pointing to a change in the milling and crystallization processes used early in the manufacture of the API (see Figure 1).


Figure 1. Screenshot of particles.

Another important aspect of particle identification relates to quality control of pharmaceutical solutions. Visual inspection is covered by USP chapter , along with USP chapters , , and that regulate the number of visible and subvisible particles in ophthalmic and injectables. All of which require the observation and counting of particulate matter. In these cases, the presence, size, and morphology of particles can additionally be used for forensic determination of the particulate source, be it intrinsic, extrinsic, or inherent.

As pharmaceutical science moves towards more advanced manufacturing and delivery technologies, such as 3-D printing and continuous manufacturing, morphology of the constituents becomes ever more critical. Powder flow and shape factors, such as sphericity, will need to be precisely controlled to ensure final product quality, content, and performance. In fact, one of the exhibitors at IFPAC was showing an instrument that measures the increase in static electricity in an excipient as it is dispensed through a stainless-steel pipe. This is yet another data point that needs to be measured and controlled.

The answer to this challenge, however, is not that simple, or everyone would already be doing it. Current commercial technologies for measuring particle size and morphology such as laser diffraction (LLD), dynamic image analysis (DIA), scanning electron microscopy (SEM), static image analysis (SIA), and microflow imaging all report different modes of size and shape. For example, to name a few difference, laser diffraction reports volumetric size, dynamic imaging a cord length, static imaging a max length, and microflow imaging the Feret length—a measure of an object’s size along a specified direction, defined as the distance between the two parallel planes restricting the object perpendicular to that direction. It is therefore also called the caliper diameter, referring to the measurement of the object size with a caliper. Some techniques report statistical average data, others report number-based data, while others don’t report enough information for statistical relevance, at all.

The consequence of all this variation among technologies is that it is increasingly difficult for a particle scientist to compare results between techniques, especially as you increase the number and complexity of competing and complementary technologies into the manufacturing process. All measurements provide correct results, but those results can be biased by the way they were generated. This is also quite common in rheology measurements in liquids: no two methods generate the same number, so the instrument and spindle are “set in stone” for each material measured. It is up to the development team to ask, “Which result is the most relevant to our application?” Compounding these complex issues, only a subset of techniques provides morphological data along with size, and the number of parameters reported varies by method.

The ultimate outcome, putting this complex jigsaw puzzle of information together, can be a slow, tedious, and laborious process. This process requires a detailed knowledge of each technique’s capabilities, along with their strengths and weaknesses relative to the application. This paradigm requires scientists to become experts in the range of analytical techniques applicable, or companies to recruit expert consultants to help wade through the myriad of information. Particle Size and Material Science has now become a fundamental science within the pharmaceutical industry, requiring technologies that can meet the economies of scale needed by the industry, which a software program I observed at IFPAC can.

With the introduction of CLAIRITY, a software product from ImageProVision, Inc., there may be a simpler way to help solve this conundrum. This product is aimed to be a lower priced alternative to the traditional instrumentation in this field. Offering access to these essential measurements, with a smaller capital outlay, whilst improving the performance of the technology at the same time. The software provides a trove of information in the world of particle size and morphology for a relatively small investment.

This Particle Analysis Suite is a software package that offers an updated view on measuring particle size and morphology. Traditional instrumentation offers limited compatibility for comparison or interpretation of alternative measurement technologies. Not only does this new software package offer the ability to directly integrate with virtually any microscope, offering direct acquisition and analysis of particle size and morphology. This software also offers the unique ability to import and process images from virtually any source.

This ability facilitates the direct comparison of data in a single software platform, whilst utilizing a range of reportable parameters that allow direct comparison of data to other techniques. For example, results such as spherical equivalent volume (SEV) allows for the comparison of laser diffraction data, and the reporting of 5 different length measurements, means that previously incomparable image analytics data may now be directly compared.

Take, as an example, the data obtained from the traditional Static Image Analysis platforms in the market today. One manufacturer report’s size according to the USP chapter definition, which is the longest distance between two points on a particle’s axis. Another manufacturer reports size according to the Feret definition, which is a caliper base measurement of the maximum distance across the particle. For irregularly shaped objects these two measurements can result in very different outcomes, making the results incomparable.

Another example of the software’s capabilities is the comparison of Flow Imaging (FI) data to static image analysis. A typical FI analysis can result in tens of thousands of images being generated for a single sample, few of which actually contain particles. Comparison of these datasets between manufacturers can be quite challenging, and options for re-analysis of the data limited due to the number of images. CLAIRITY offers the ability to import, and re-analyze the entire image set, expanding the information available from the measurement, and providing directly comparable data to complimentary techniques.

What the software package brings to the table is the ability to process and interpret particle data within a single platform. It provides greater comparability, transparency, and repeatability between results than current approaches. It almost sits as the referee between techniques, offering unique insights and comparisons into data that were previously quite laborious to achieve.  Add to this capability to extend the software to incorporate Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) [currently AI, ML, and DL are not deployed at any location, but are slated as future applications] into the acquisition, image processing, data analysis, and data interpretation phases of the measurement this software package can provide analytical insights into the data, trends, and outliers that are currently not possible from traditional technologies.

The software is a high-performance, low-cost entry into an application space that has seen little improvement in technology and capability over the past ten years. While the functional limitations of image base analysis remain, integration of new technologies and capabilities for data interpretation and analysis brings greater insights into once incomparable data sets. It offers a unique, unified approach to data collection, analysis, and review for particle size and morphology measurement (see Figure 2). In turn this data can provide actionable insights and establish functional relationships between Critical Material Attributes (CMAs), and Critical Process Parameters (CPPs) to confirm Critical Quality Attributes (CQAs) or a pharmaceutical product.


Figure 2. Screenshot of capsule contents.

Acknowledgements: I want to thank Messers Jeffery Hall and Matt McGann from ImageProVision, Inc. for taking the time to enlighten me about this new product.


Emil W. Ciurczak, also known as the NIR Professor, has roughly 50 years of cGMP pharmaceutical experience and more than 35 years of Near-Infrared Spectroscopy (NIRS) experience with industries, universities, and instrument manufacturers. Emil teaches courses in NIRS, NIR/Raman, Design of Experiment, and PAT/QbD; has designed and patented hardware and software (including hardware and software related to anti-counterfeiting; written numerous technical texts and chapters; published extensively in journals; and presented hundreds of technical papers at many conferences, worldwide. He has worked in the pharmaceutical industry since 1970 for companies that include Ciba-Geigy, Sandoz, Berlex, Merck, and Purdue Pharma, where he specialized in performing method development on most types of analytical equipment. For more info: emil@ciurczak.com

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