Chapter 59: Raw Materials, Packaging, and Infrastructure for Product Development

The United States Food and Drug Administration (FDA) provides guidance for raw materials, packaging, and infrastructure for product development within the guidance for industry Process Analytical Technology—A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance. The premise of this document is to ensure that the current concepts of risk management and quality systems approaches are incorporated into the design, development, and manufacture of pharmaceuticals while maintaining product quality.

Effective innovation in development, manufacturing, and quality assurance would be aided by answering several questions:

• What are the mechanisms of degradation, drug release, and absorption?

• What are the effects of product components on quality?

• What sources of variability are critical?

• How does the process manage variability?

• What are the packaging considerations?

The goal of process analytical technology (PAT) is to enhance understanding and control the manufacturing process, which is consistent with current drug quality system thought: quality can not be tested into products—it should be built in or should be by design.

Quality is built into pharmaceutical products through a comprehensive understanding of:

• The intended therapeutic objectives, patient population, route of administration, and pharmacological, toxicological, and pharmacokinetic characteristics of a drug

• The chemical, physical, and biopharmaceutic characteristics of a drug

• Design of a product and selection of product components and packaging based on drug attributes

• The design of manufacturing processes using principles of engineering, material science, and quality assurance (QA) to ensure acceptable and reproducible product quality and performance throughout a product’s shelf life

Many tools are available that enable process understanding for scientific, risk-managed pharmaceutical development, manufacture, and QA. These tools, when used within a system, can provide effective and efficient means for acquiring information to facilitate process understanding, continuous improvement, and development of risk mitigation strategies. In the PAT framework, these tools can be categorized as:

• Multivariate tools for design, data acquisition, and analysis

• Process analyzers

• Process control

• Continuous improvement and knowledge management

Multivariate tools for design, data acquisition, and analysis from a physical, chemical, or biological perspective, and pharmaceutical products and processes, are complex multifactorial systems. Many development strategies can be used to identify optimal formulations and processes. The knowledge acquired in these development programs is the foundation for product and process design. Methodological experiments based on statistical principles of orthogonality, reference distribution, and randomization provide effective means for identifying and studying the effect and interaction of product and process variables. Traditional one-factor-at-a-time experiments do not address interactions between product and process variables. When used appropriately, these tools enable the identification and evaluation of product and process variables that may be critical to product quality and performance. The tools may identify potential failure modes and mechanisms and quantify their effects on product quality.

Some process analyzers provide nondestructive measurements that contain information related to biologic, physical, and chemical attributes of the materials being processed. These measurements can be:

• At-line, where the sample is removed and analyzed close to the process stream

• Online, where the sample is diverted from the manufacturing process to an analyzer, and possibly returned to the stream

• In-line, which may be an invasive or noninvasive process that analyzes the sample while it is part of the process stream

Process control tools used for the design and optimization of drug formulations and manufacturing processes within the PAT framework can include the following steps, although the sequence of steps can vary:

• Identify and measure critical material and process attributes relating to product quality.

• Design a process measurement system to allow real-time or near real-time (for example, on-, in-, or at-line) monitoring of all critical attributes.

• Design process controls that provide adjustments to ensure control of all critical attributes.

• Develop mathematical relationships between product quality attributes and measurements of critical material and process attributes.

Continuous improvement and knowledge management through data collection and analysis over the life cycle of a product are important. These data can contribute to justifying proposals for post-approval changes. Approaches and information technology systems that support knowledge acquisition from such databases are valuable for the manufacturers and can facilitate scientific communication.