Principles of Parametric Release: Emphasis on Data Collection and Interpretation.

Area of Science:

• Sterilization technologies
• Industrial microbiology
• Process validation

Background:

• Parametric release, utilizing process data for product release, offers significant advantages but adoption in the sterilization industry remains limited.
• Current sterilization release practices often rely on biological indicator (BI) growth responses or dosimetry readings, rather than comprehensive process data.
• Variability in product loads can impact the reliability of traditional release methods when not adequately addressed during performance qualification.

Purpose of the Study:

• To highlight the potential of using process-generated data for enhanced parametric release implementation in sterilization.
• To demonstrate how data from ethylene oxide (EO), vaporized hydrogen peroxide (VHP), and radiation sterilization processes can inform parametric release strategies.
• To address the limitations of current methods in accounting for load variability during sterilization validation.

Main Methods:

• Analysis of process data from ethylene oxide (EO) and vaporized hydrogen peroxide (VHP) sterilization cycles.
• Evaluation of the repeatability of validated parameters delivered by sterilization equipment under varying load conditions.
• Comparison of direct concentration measurement probes versus calculated methods for EO and VHP concentrations.
• Review of regulatory requirements for parametric release, including European Union good manufacturing practice Annex 17.

Main Results:

• Sterilization equipment demonstrated consistent delivery of validated parameters for EO and VHP processes after successful load validation.
• Biological indicator testing and direct EO concentration measurement may not fully capture the impact of load variability on the validated process.
• Calculated methods can accurately determine EO and VHP concentrations, potentially making direct measurement probes redundant.
• Radiation processing faces challenges in parametric release due to limitations in measuring critical parameters like photon delivery.

Conclusions:

• Process data offers a more robust basis for parametric release than traditional BI testing, especially when load variability is a concern.
• Calculated methods for determining EO and VHP concentrations provide a reliable alternative to direct measurement probes.
• Achieving parametric release requires sufficient data to demonstrate process repeatability, aligning with regulatory expectations.
• Further development is needed to overcome measurement challenges in radiation processing for broader parametric release adoption.