Significance of Standardization process
The standardization process is a systematic approach essential for ensuring the quality and reliability of raw materials and Ayurvedic formulations. It sets guidelines for the authenticity and purity of raw drugs, evaluates the quality of medicinal products like Mandura Vajra Vataka and Butea monosperma flowers, and establishes consistent protocols for herbal medicines. This process includes morphological, chemical, and biological assessments to validate the quality, efficacy, and safety of products, crucial for their market acceptability and therapeutic effectiveness.
Synonyms: Standardization procedure, Normalization process, Regularization method, Normalization, Harmonization, Unification, Regularization, Integration
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
Hindu concept of 'Standardization process'
The Standardization process in Hinduism involves ensuring results are accurate and reliable, linked to established reference systems, while also maintaining quality and uniformity from raw material collection through manufacturing.
From: Journal of Ayurveda and Integrated Medical Sciences
(1) This is the process that aims to guarantee the quality, efficacy, and uniformity of the final product, starting from raw material collection and continuing through manufacturing.[1] (2) This process guarantees that results are linked to established reference systems, providing increased confidence in their accuracy and proximity to the true value, involving development and characterization of reference materials.[2]
The concept of Standardization process in scientific sources
The Standardization process involves systematically collecting raw materials and applying structured procedures to guarantee consistent quality and reliability in clinical applications, ensuring a uniform standard across practices and scales.
From: Sustainability Journal (MDPI)
(1) Through the standardization process, the proposed solution is assumed to be critically evaluated and improved, enhancing its reliability.[3] (2) A standardization process is applied for both datasets to rescale the features due to the differences among their value ranges, which allows the models to have better results.[4]