Contamination Control | Make Contamination Detection Automatic

This new department, which will appear in every issue, will bring you the key information you need to prevent contamination incidents in your facility.

A few tools can help automate the search for foreign particulates

Foreign particles or foreign particulate matter in parenteral and drug powder products is a big area of concern in pharmaceutical manufacturing settings. Contamination due to excessive particulate matter in drugs can lead to quality, safety, and efficacy problems in products that interact directly with diseased organs or require specific regional deposition. Particle contamination in manufacturing sites results in the suspension of drug production. In addition, investigating the source of the contaminants and developing a suitable cleaning process increase costs.

Foreign particles consist of two main types: intrinsic and extrinsic. Intrinsic particulate matter is either part of the original product that was not removed by filtration prior to filling or is made up of particles that resulted from a precipitation in the solution. Extrinsic or extraneous particles are those that are introduced into the process due to insufficient cleaning of the production environment, product assembly protocols, or standard manufacturing processes such as milling, filling, and lyophilization. Automated particle analysis using scanning electron microscopy, energy dispersive spectrometry, and micro-Raman spectroscopy can be used to detect these particles.

Regulatory agencies like the Food and Drug Administration (FDA) and the United States Pharmacopeia (USP) provide continually evolving guidelines to evaluate contamination in pharmaceutical products. For parenteral products, the USP established chapter <788>, which requires the inspection and evaluation of particulate matter through either microscopic or light obscuration particle count testing.

Initiatives such as quality by design (QbD) and process analytical technology (PAT) are at the forefront of efforts to obtain better and cleaner manufacturing environments and products. QbD is based on the idea that manufacturers should proactively design quality into their products, as opposed to spending time and money to solve post-production errors and defects. Along the same lines, companies using PAT are conducting real-time, on-location testing of quality factors with the goal of detecting and fixing problems during the process, rather than waiting until after a batch is produced.

Both approaches have similar goals that can be incorporated into the drug development and manufacturing process. For particulate matter, full characterization studies—including chemical identification, sizing, and enumeration—are essential to understanding the process, identifying the sources of contamination, and establishing acceptance criteria for product approval and release.

Typical Contamination Sources

Most pharmaceuticals must be essentially free of visible particulate contaminants; in most cases, particle size distribution, enumeration, and chemical identification are required. Particulate matter can range in size from sub-microns to several hundreds of microns, and shape and density may vary widely.

The most common materials identified in pharmaceutical environments are stainless steel, silica, aluminum, salts, minerals, organic fluorinated compounds, and carbonaceous materials in varying sizes and shapes.

Contamination sources vary depending on the drug product manufacturing process, equipment, location, and overall cleanliness. Cleanrooms can be exposed to particulate matter shed by gowns, gloves, skin flakes, sample preparation equipment, and glassware. Manufacturing facilities are a high-risk source for contamination from metal, metal oxides, building materials, ceramics, dust, personnel, process air, air filtration systems, and machines.

Containers and their closures, specifically rubber closures, contribute particulate matter due to leaching, chemical reactions, friction, and changes in physical properties. Packaging materials, blisters, solutions, vials, formulation components, and product-package interactions also generate particulate matter. The most common materials identified in pharmaceutical environments are stainless steel, silica, aluminum, salts, minerals, organic fluorinated compounds, and carbonaceous materials in varying sizes and shapes (see Figure 1, p. 40).

Automated Particle Analysis

In the QbD and PAT approaches, pharmaceutical companies are encouraged to create a detailed database containing information about the types and sources of particulate material. This database serves as a reference when conducting investigations or establishing manufacturing controls. Today, many analytical techniques are available for particle characterization, and every laboratory has its own criteria for selecting the technique that best suits its needs and budget. Some key questions to ask when selecting a particle characterization technique:

• What is the particle size range of interest?
• Is chemical composition data required?
• What is the chemical nature of the particles (organic, inorganic, metallic)?
• What is the sampling method?
• If the drug is a powder, is it soluble?
• Does it tend to aggregate?

One additional point to consider in the selection of the appropriate testing technique is whether or not the analysis process can be automated. Inspection and testing for particulate matter can be performed either manually or automatically. Manual inspection depends on a variety of factors, including the nature of the particles, type and intensity of lighting, visual acuity of the inspector, container clarity, container volume, interval of inspection, and analyst fatigue. To take into account the physical limitations of manual inspection processes, guidelines are often composed with imprecise statements, such as "practically free."

Today, technological advances allow the automation of many particle-testing techniques. Automation eliminates the physical limitations of visual inspection, like subjective analysis. In addition to improving throughput by reducing the analysis time, process automation provides an impressive amount of meaningful statistical metrics.

Table 1. Instrument requirements and settings for automated scanning electron microscopy with energy dispersive spectrometry characterization of particles. Particles with a high atomic number are considered bright (high backscatter electron signal). Dark particles have a low atomic number (low backscatter signal).

One example of successful process automation for foreign particulate testing is the Personal Scanning Electron Microscope (PSEM; ASPEX Corp., Delmont, Pa.). The PSEM integrates scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) for a multi- disciplinary approach that provides not only visual information about the organic and inorganic submicron particles (size, shape, and morphology) but also chemical identification based on the X-ray energy lines.

Although SEM and EDS equipment can be used independently for analytical testing of pharmaceutical products, the integration and automation of these techniques provides additional benefits, such as the recognition of groupings within a population of particulate material, location of low-probability features (the needle in the haystack), elimination of human subjectivity, and reduced cost and analysis time.

Due to the great diversity of data (morphology, size, shape, and elemental composition) and statistical information, automated SEM-EDS testing is used in pharmaceutical laboratories across the nation; it provides complete understanding of the sources of foreign particles. There are several important criteria for the optimization of this microscopic method (see Table 1).

Automated Raman Spec

Automated micro-Raman spectroscopy combined with image analysis is another technique used for the collection of microscopic data on non-metallic organic and inorganic matter. Automated Raman spectroscopy with image analysis works by collecting an image of the entire filter membrane surface covered with particles, then following with Raman analysis. Data collected include size, count, imaging, and chemical structure of non-metallic particles larger than two microns and agglomerates of the drug substance.

Figure 1. Scanning electron microscopy images and energy dispersive spectrometry spectra of typical pharmaceutical contaminants. Top to bottom: aluminum, iron, synthetic fiber, talc, and stainless steel.

Automated optical microscopy is used for size information only. The automation of optical microscopy can be achieved by using software for image analysis, measurement, and characterization of particles in terms of size and shape. Solid samples and ointments can be placed on a microscopic slide for analysis of particles larger than 50 microns. Sample preparation for the aforementioned techniques—automated SEM-EDS, micro-Raman spectro-scopy, and optical microscopy—is based on standard filtration techniques. Drug powder suspensions or the parenteral solution are passed through a filter membrane that is automatically scanned for particle content.

Other automated techniques, including light obscuration and laser diffraction, are typically used when only particle enumeration is required. Light obscuration testing requires a sample dose suspended in a liquid and exposed to a laser. When particles pass through the laser, they either absorb or scatter, resulting in a measurable voltage change proportional to the particle size. In laser diffraction, measurements provide size data for particles as small as tens of nanometers through measurements of scattering intensity as a function of the scattering angle and the wavelength and polarization of light based on applicable scattering models. This technique can be used to evaluate the particle size distribution and shape of particulate matter in dry powders and solutions. Both particle counters are a staple in pharmaceutical environments for particle size distribution testing.

Once the appropriate technique is selected, a standard operating procedure (SOP) must be developed and validated to assure that all variables and instrumental parameters are identical for every measurement, eliminating user or site variations. Reproducibility and reliability studies are also recommended prior to installation and data acquisition. These are just a handful of suggestions for the selection and implementation of the appropriate analytical testing technique for particulate matter. As regulatory perspectives change, pharmaceutical companies need to monitor and adhere to the latest regulations.

Because undetected particulate matter that contaminates products might cause adverse health effects, excessive particulate matter in pharmaceutical environments can delay the development and manufacturing of a drug product. As a result, regulatory agencies like the FDA and the USP have established guidelines and standards for testing of particulate matter in parenterals and drug products.

Although particulate matter is often a result of the manufacturing environment, in the case of injectable products, it may result from a chemical interaction between a reconstituted product and its container. Conducting appropriate testing will identify the source of contamination, allowing for the implementation of procedures that eliminate excessive particulate matter to the FDA's satisfaction.

Depending on the nature of the sample (organic, inorganic, or metallic) and the type of information desired, pharmaceutical companies have a large pool of adequate technologies to acquire data quickly and accurately. Automated technologies, such as SEM-EDS, are used in pharmaceutical laboratories to obtain data on the morphology, size, shape, and elemental composition data of metallic and organic particles as small as 0.1 microns. Lack of testing for particulate contamination can result in product recalls and patient complications that can cost pharmaceutical companies millions of dollars. Implementation of technologies for particulate matter testing is a key step toward eliminating potential quality problems and contamination issues in a timely fashion, just as QbD and PAT approaches suggest.

Dr. Vicéns is an application specialist at ASPEX Corporation. For more information, e-mail her at mvicens@aspexcorp.com or visit www.aspexcorp.com.

Resources

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5. Blanchard J, Coleman J, Crim C, et al. Best practices for managing quality and safety of foreign particles in orally inhaled and nasal drug products, and an evaluation of clinical relevance. Pharm Res. 2007;24(3):471-479.