Product-Packaging Stability Modeling

Are you determining the shelf life of a product or designing a container closure system (CCS) to ensure the product achieves its desired shelf life? Traditionally, shelf life determination involves placing the product in various CCS configurations, periodically testing its stability, and recording the duration for which it meets the required criteria. This classical approach is both time-consuming and costly. If the product fails, the stability study must be repeated, further extending timelines and increasing expenses. Although this traditional method is no longer the industry standard, many companies still rely on it. Why is that? Often, senior management still insists on the outdated mentality of “Just put the product in a package!”

In contrast, designing a CCS requires a thorough understanding of product kinetics, packaging barrier properties, and environmental conditions. This allows for an estimation of product stability using fundamental principles. Implementing a computer-programmed model for numerical analysis can streamline this process. In this post, I will introduce a Product-Packaging Stability Modeling method, applicable to both food and pharmaceutical products, which can significantly enhance efficiency and accuracy in stability predictions.

First Principles used to develop the Product-Packaging Stability Model

Product​

  •  Moisture sorption isotherm (GAB, Langmuir models)​
  •  Product degradation kinetics (accelerated stability, Arrhenius relationship)

Package​

  •  Permeability (Fick’s laws of diffusion)

Environment​

  •  Partial pressure for moisture, oxygen, etc.

Figure 1 shows a graphical representation of this model.

Figure 1.

Moisture and oxygen permeate through plastic container-closure systems, and the permeated moisture can be distributed between the desiccant and the product based on their respective sorption isotherms and weights. Permeated oxygen is consumed during the product degradation process. At any given moment, the vapor pressure in the headspace, desiccant, and product reach an equilibrium within the container. This dynamic equilibrium allows for the calculation of product stability changes. Using a product kinetic model, which describes the relationship between degradation rate, moisture (and oxygen), and temperature, these stability changes can be accurately predicted. This approach provides a robust method for assessing the impact of environmental factors on product shelf life and helps in designing more effective packaging solutions.

By understanding and modeling these interactions, one can significantly enhance the predictive accuracy of product stability, leading to better-informed decisions in the packaging design process and ultimately ensuring the quality and efficacy of the product throughout its shelf life.

Critical Modeling inputs and outputs

Modeling utilizes experimentally determined inputs (material properties)​

  •   Packaging – moisture (and oxygen) permeability​
  •   Product – initial moisture content and moisture sorption isotherm for solids, product degradation rate constants​
  •   Environment – any desired conditions​

To provide: ​

  • Theoretically estimated outputs: Aw (water activity) and moisture contents of solids, impurity, etc. ​

The Product-Packaging model provides scientific estimates based upon material properties and first principles.

The model has been verified with experimentally determined results. See Figure 2 for water activity results and Figure 3 for product impurity results.

Figure 2. Comparison between estimated and experimentally determined water activity
Figure 3. Comparison between estimated and experimentally determined impurity

Applications

  • Packaging design for new products​: packaging material selection, determine the amount of desiccant and type of desiccants​, Justification of initial aw, oxygen concentration, etc.​
  • Support for manufacturing deviations​
  • Post approval changes​: packaging material changes​, bottle count change​, sealing method change (e.g., heat seal vs. cable tie)

        Conclusions

        1. Product-packaging stability modeling is a good example of QbD paradigm.​
        2. Minimize trial and error approach – package screening study should not be a tool to select packages but to confirm QbD approach.​
        3. This modeling can minimize unnecessary work but maximize necessary work.  Overall, reduce cycle time for package design and ensure cost effective packages.​
        4. Powerful QbD tool to explain product stability in a variety of situations.​
        5. High confidence in new packaging design and acceptable product stability.