Setting Effective Product Specifications in Pharmaceutical Manufacturing

An important aspect of Quality by Design (QbD) is to establish meaningful and realistic specifications. Well-defined specifications control the performance of products, as they derive from associations between clinical behaviour and the variables determined routinely during processing for quality control. This article investigates the process of setting specifications, taking particle size as an example which is a major parameter for a variety of pharmaceutical formulations.  

The pharmaceutical industry faces many pressures and the regulatory bodies that control this industry are encouraging the shift towards a risk-based approach to production. QbD is an important part of this change in emphasis, promoting knowledge development through which manufacturers can prove their capability.

Setting Meaningful Specifications

According to the FDA guidance specified in ICH topic Q6A, specifications are important standards that are proposed and justified by manufacturers and sanctioned by regulatory authorities as conditions of approval. Since specifications define the acceptability of a product, the requirement for one is based on the existence of a correlation between a variable and some aspect of performance. Within the structure of QbD, such links establish a parameter as a Critical Quality Attribute (CQA), the control of which ensures product quality. These parameters include the following:

  • Particle size
  • Physicochemical properties such as refractive index, pH, melting point
  • Chiral identity
  • Polymorphic form/amorphous content
  • Water content
  • Microbial content
  • Inorganic impurity levels

Evidently, when a variable does not impact on product quality, it is not necessary to specify values for it, but where there is a correlation any associated specification must provide sufficient control.

Particle Size Specification

A decision tree in the ICH topic Q6A ascertains the need for a particle size specification, recommending them for both solid and liquid dosage forms as particle size can be important to any of the following attributes:

  • Dissolution
  • Processability
  • Stability
  • Product content uniformity

It is a well-known fact that dissolution behavior depends on particle size, or more precisely on surface area. Finer powders dissolve more quickly, and powders with a narrow size distribution dissolve at a similar rate. For orally administered and nasal drug products, the correlation with bioavailability is more direct, because wrong-sized particles will not deposit within the preferred part of the respiratory system, and thereby fail to enter the body by the prescribed route.

Processability is critical as it correlates with the consistency and quality of products, with poorly controlled processes creating a low quality output. Particle size relates to parameters such as segregation behaviour, powder flowability, and compressibility. Hence, defined size specifications for intermediates or in-process material may provide a way of reducing process variability.

Stability issues usually occur because the forces acting on particles are related to their size. Smaller particles are more likely to agglomerate because inter-particle forces are comparatively high. When looking at suspensions, the tendency to settle increases with size due to the effects of gravitational forces. Stability is an important parameter during the development of particle size measurement methods.

Lastly, the size of the particle can affect blend uniformity, and consequently the dose content uniformity related to a product. For instance, Figure 1 depicts a NIR chemical image of a recalled tablet with the active ingredient-rich domains highlighted in red. The right side of the tablet has larger areas when compared to the left, indicating that composition is not even.

NIR image of a tablet showing heterogeneous distribution of the active ingredient.

Figure 1. NIR image of a tablet showing heterogeneous distribution of the active ingredient.

To sum up, particle size specifications are usually required for suspensions or solid dosage forms, as particle size affects many aspects of product performance.

Measurement of Particle Size Distributions using Laser Diffraction

A wide range of particle size analysis tools are available to support pharmaceutical development. One of the most popular methods used for particle size analysis is laser diffraction. This particle size measurement method has broad applicability and is ideal for both wet and dry systems with particle size ranging from 0.1 to 3500µm. An attractive feature of this technique is that it is a suitable Process Analytical Technology, therefore specifications formulated in the laboratory can be transferred into production.

Particle Size Distribution

Comparing volume and number based distribution.

Figure 2. Comparing volume and number based distribution.

Laser diffraction creates volume based distributions, meaning that data is produced concurrently for the entire sample (ensemble), rather than for separate particles, and is represented with respect to the volume of material in a given size fraction. An alternative, utilized by microscopy and imaging techniques, is to show data on a number basis - that is, display the number of particles in each size fraction. Both techniques are equally suitable, but the results obtained are quite different (Figure 2).

Selecting a Suitable Parameter

Assessing the ability of a laser diffraction analyzer (Mastersizer 3000) to identify coarse and fine particles in a pharmaceutical blend.

Figure 3. Assessing the ability of a laser diffraction analyzer (Mastersizer 3000) to identify coarse and fine particles in a pharmaceutical blend.

One way to determine the best basis for a specification is to measure the sensitivity of different particle size parameters to changes in a sample. Figure 3 shows an example size distribution, in this case a mixture of two components, which has been measured using laser diffraction. Using this, we can consider which statistics relate to different regions of the distribution.

Setting Appropriate Tolerances  

Laser diffraction provides unprecedented robustness, repeatability and reproducibility, creating good quality data with little manual input needed. Setting suitable tolerances for a specification needs an appreciation of measurement errors together with an understanding of the association between the variable and product performance. Figure 4 illustrates some particle size distribution data, with the orange and yellow lines measuring reproducibility and the red line being a typical reading. If the specification for this product is a Dv50 of 10µm, the plot shows that the measurement variability will be +/- 5%. But, it would be incorrect to assume that the same tolerance can also be employed for the percentage below 10µm.

Highlighting how accuracy is affected by the basis or wording of a specification.

Figure 4. Highlighting how accuracy is affected by the basis or wording of a specification.

Owing to the slope of the undersize distribution curve, a specification demanding that 50% of the volume of material must be 10µm size or less would be subject to +/-14% measurement variability. This study clearly underlines a point that as measurement variability increases, assurance in the reported result should reduce.


Establishing specifications on the basis of product understanding is a major aspect of QbD and important for successful quality control. To this end, particle size in many pharmaceuticals is a Critical Quality Attribute, a variable that must be strongly controlled as it directly affects performance.

Laser diffraction is ideal for a variety of applications within the pharmaceutical industry and is specifically sensitive to over-sized material. The Mastersizer laser diffraction analyzer offers highly repeatable results (+/-1%) and reduces the need to tighten tolerances to account for measurement errors.

About Malvern Panalytical

Malvern Panalytical provides the materials and biophysical characterization technology and expertise that enable scientists and engineers to understand and control the properties of dispersed systems.

These systems range from proteins and polymers in solution, particle and nanoparticle suspensions and emulsions, through to sprays and aerosols, industrial bulk powders and high concentration slurries.

Used at all stages of research, development and manufacturing, Malvern Panalytical’s materials characterization instruments provide critical information that helps accelerate research and product development, enhance and maintain product quality and optimize process efficiency.

Sponsored Content Policy: publishes articles and related content that may be derived from sources where we have existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.Net which is to educate and inform site visitors interested in medical research, science, medical devices and treatments.

Last updated: May 31, 2023 at 9:51 AM


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Malvern Panalytical. (2023, May 31). Setting Effective Product Specifications in Pharmaceutical Manufacturing. News-Medical. Retrieved on April 23, 2024 from

  • MLA

    Malvern Panalytical. "Setting Effective Product Specifications in Pharmaceutical Manufacturing". News-Medical. 23 April 2024. <>.

  • Chicago

    Malvern Panalytical. "Setting Effective Product Specifications in Pharmaceutical Manufacturing". News-Medical. (accessed April 23, 2024).

  • Harvard

    Malvern Panalytical. 2023. Setting Effective Product Specifications in Pharmaceutical Manufacturing. News-Medical, viewed 23 April 2024,

Other White Papers by this Supplier

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.