For disperse system drug formulations, meaningful particle size distribution (PSD) comparators are essential in determining pharmaceutical equivalency and predicting biopharmaceutical equivalence in terms of the effect of particle size on the rate and extent of drug input. In formulation development and licensure, particle size characterization has been applied to establish relationships for bioequivalence of generic pharmaceutical drug products. The current approaches recommended by the US-FDA using median and span are not adequate to predict drug product performances or account for multi-modal PSD performance properties. The use of PSD similarity metric and the development and incorporation of drug release predictions based on PSD properties into PBPK models for various drug administration routes may provide a holistic approach for evaluating the effect of PSD differences on in vitro release of disperse systems and the resulting pharmacokinetic impact on drug product performance. The objectives of this study are to provide a rational approach for PSD comparisons by 1) developing similarity computations for PSD comparisons and 2) using PBPK-models to specifically account for PSD effects on drug input rates via a subcutaneous (SQ) administration route.
Two techniques for measuring PSDs of reference (reference-listed drug product) and test (generic) drug products were investigated: OVL and PROB, as well as the current standard measurements of median and span. In addition, release rate profiles of each product pair simulated from modified Bikhazi and Higuchi’s model were used to compute release rate comparators such as similarity factor (f2) and fractional time ratios. A subcutaneous input PBPK model was developed and used to simulate blood concentration-time profiles of reference and test drug products. Pharmacokinetic responses such as AUC, Cmax, and Tmax were compared using standard bioequivalence criteria. PSD comparators, release rate comparators, and bioequivalence metrics were related to determine their relationships and identify the appropriate approach for bioequivalence waiver.
OVL showed better predictions for bioequivalence compared to PROB, median, and span. For release profile comparisons, the f2 method was the best for bioequivalence prediction. The use of both release rate (e.g., f2) and PSD (e.g., OVL) comparison metrics significantly improved bioequivalence prediction to about 90%.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7454 |
| Date | 01 December 2017 |
| Creators | Ngeacharernkul, Pratak |
| Contributors | Kirsch, Lee E. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2017 Pratak Ngeacharernkul |
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