Functional design of experiment for potency assay optimization and in-silico simulation

Area of Science:

• Biopharmaceutical Analysis
• Assay Development
• Statistical Modeling

Background:

• Robust potency assays are crucial for biotherapeutic analytics.
• Current design of experiment (DoE) approaches model assay features independently, hindering joint interpretation.
• Existing methods limit the comprehensive understanding of assay parameter influence.

Purpose of the Study:

• To develop a functional DoE approach for modeling multiple assay features simultaneously.
• To investigate the direct impact of assay parameters on dose-response curve shape.
• To optimize biotherapeutic potency assays using a multivariate desirability function.

Main Methods:

• Utilized a functional DoE approach to model the sigmoidal dose-response curve.
• Employed the functional relationship between assay features for curve description.
• Defined and applied a multivariate desirability function for assay optimization.

Main Results:

• Successfully modeled the direct impact of assay parameters on the dose-response curve shape.
• Demonstrated the utility of functional modeling for joint interpretation of assay features.
• Achieved assay optimization through the multivariate desirability approach.

Conclusions:

• Functional modeling enhances the understanding of joint assay parameter influence in biotherapeutic analytics.
• This approach contributes to the design of more robust and reliable potency assays.
• The proposed method offers a significant advancement in biopharmaceutical assay development and optimization.