J 2021

A Critical Overview of FDA and EMA Statistical Methods to Compare In Vitro Drug Dissolution Profiles of Pharmaceutical Products

MUSELÍK, Jan, A. KOMERSOVA, Kateřina KUBOVÁ, K. MATZICK, B. SKALICKA et. al.

Basic information

Original name

A Critical Overview of FDA and EMA Statistical Methods to Compare In Vitro Drug Dissolution Profiles of Pharmaceutical Products

Authors

MUSELÍK, Jan (203 Czech Republic, belonging to the institution), A. KOMERSOVA (guarantor), Kateřina KUBOVÁ (203 Czech Republic, belonging to the institution), K. MATZICK and B. SKALICKA

Edition

Pharmaceutics, BASEL, MDPI, 2021, 1999-4923

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30104 Pharmacology and pharmacy

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 6.525

RIV identification code

RIV/00216224:14160/21:00119760

Organization unit

Faculty of Pharmacy

UT WoS

000714524900001

Keywords in English

drug dissolution; dissolution profile comparison; EMA and FDA strategy

Tags

Tags

International impact, Reviewed
Změněno: 14/4/2022 15:25, JUDr. Sabina Krejčiříková

Abstract

V originále

A drug dissolution profile is one of the most critical dosage form characteristics with immediate and controlled drug release. Comparing the dissolution profiles of different pharmaceutical products plays a key role before starting the bioequivalence or stability studies. General recommendations for dissolution profile comparison are mentioned by the EMA and FDA guidelines. However, neither the EMA nor the FDA provides unambiguous instructions for comparing the dissolution curves, except for calculating the similarity factor f(2). In agreement with the EMA and FDA strategy for comparing the dissolution profiles, this manuscript provides an overview of suitable statistical methods (CI derivation for f(2) based on bootstrap, CI derivation for the difference between reference and test samples, Mahalanobis distance, model-dependent approach and maximum deviation method), their procedures and limitations. However, usage of statistical approaches for the above-described methods can be met with difficulties, especially when combined with the requirement of practice for robust and straightforward techniques for data evaluation. Therefore, the bootstrap to derive the CI for f(2) or CI derivation for the difference between reference and test samples was selected as the method of choice.


Links

MUNI/A/1574/2020, interní kód MU
Name: Pokročilé technologie pro přípravu a hodnocení částicových systémů
Investor: Masaryk University
QK1810221, research and development project
Name: Využití mikročástic jako nosičů hormonálně aktivních látek v řízené reprodukci ryb.
Investor: Ministry of Agriculture of the CR