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Systematic Selection of Impurities, Development, and Validation of Related Substance Methods for Estradiol and
Naga Venkata Durga Prasad Ketha1, Deepti Kolli1, Praveen Kumar Subbappa2
1Koneru Lakshmaiah Education Foundation, Department of Chemistry, Green Fields, Vaddeswaram, Guntur, Andhra Pradesh 522502, India.
Background:
A kind of estrogen called estradiol is a female sex hormone that regulates several body processes. In hormone replacement therapy for women, the endogenous steroid progesterone is employed. The soft gel capsule medication, which contains a mix of 1 mg estradiol and 100 mg progesterone, is used to treat moderate to severe menopause symptoms, such as hot flashes, in women who have uteruses, as well as feelings of warmth in the face, neck, and chest.
Objective:
To establish the stability of drug products in accordance with the ICH Harmonized Tripartite Guideline, Stability Testing of New Drug Substances and Products (Q1A), this study aims to develop a reverse-phase chromatographic method, the necessary analytical methodology for identifying the drug degradation profiles.
Method:
The procedures were optimized using a C18 column (250 × 4.6 mm, 5 µ) as the stationary phase and conventional solvents such as water-acetonitrile mixtures as the mobile phase. A quantification technique had been an HPLC combined with a UV/PDA and fluorescence detector.
Results:
The developed methods for both estradiol and progesterone were capable of all components of each active individually by overcoming the extremely difficult challenges of a combination product with similar structural compounds, having 24 impurities in all, and having complex excipients used for soft gel formulation.
Conclusions:
The method has been successfully created, validated for use in compliance with regulatory specifications, and determined to be accurate, linear, specific, and stability-indicating in nature.
Highlights:
To quantify the associated impurities of both actives in the presence of a highly complex matrix, the performance of the HPLC approach considerably possesses a higher degree of selectivity.
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