Designing of industry friendly pastilles of Rosuvastatin and Piperine integrating green chemistry and advanced statistical approach

Biliary excretion and poor aqueous solubility are significant concerns about Rosuvastatin's (RSV) low oral bioavailability. Incorporating the green chemistry concept into the formulation at an industrial scale is another major concern nowadays. The present study aimed to develop immediate-release (IR) pastilles of RSV and Piperine (PIP) using advanced data mining tools and exploring the concept of green chemistry. The secondary objective was to develop and validate the analytical method for estimating RSV and PIP. The Q-absorbance ratio method was developed and validated to estimate both drugs in formulation. The IR pastilles were formulated using a modified method incorporating a laboratory-scale pastillator. The pastilles were formulated by mixing, melting and solidifying the mixture in a single-step process. The concept of green chemistry, i.e., no use of organic solvent and no dust generation, was accomplished. The PIP was used as a bioenhancer, preventing RSV from entering the bile and increasing bioavailability and systemic exposure in the body. The RSV and PIP solubility were improved by formulating the pastilles using the hydrophilic carrier. The Box Behnken design (BBD) was applied to optimize pastilles. The amount of Soluplus, Primellose, and PEG 6000: HPMC E5 ratio were taken as critical material attributes (CMAs), and disintegration time, % CDR of RSV, and PIP were taken as critical quality attributes (CQAs). Various physical and drug-related evaluation parameters characterized the pastilles. The developed Q absorbance method for estimating RSV and PIP was accurate, precise, and robust. The observed isobestic point was 283 nm. QbD was implemented to develop a quality product and to find design space. BBD revealed a significant relationship between the chosen CQAs and CMAs. The optimal pastilles were composed of 42.33 mg Soluplus, 5.9% Primellose, 63.84 mg PEG-6000 and 27.36 mg HPMC E5. The designed pastilles were of uniform size and shape and had the desired characteristics. The formulation released a drug > 85% in an hour using Soluplus as a solubility enhancer and Primellose as a super disintegrant. The unexplored formulation, pastilles of RSV and PIP, was successfully developed in a single step, which has a faster dissolution rate, accomplishing a systematic approach. Green chemistry was explored using no organic solvent with no dust generation, leading to less pollution. The newer approach of formulating pastilles might apply to the industry as it is environment-friendly, single-step, and uses fewer excipients.

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Publication Details

Journal
Discover Chemistry.
Published
2025-04-21
DOI
https://doi.org/10.1007/s44371-025-00172-5
Citations
4
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
6.02
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article

Designing of industry friendly pastilles of Rosuvastatin and Piperine integrating green chemistry and advanced statistical approach

Hardik Rana, Vaishali Thakkar, Chetna Modi, Grishma Patel
4 citations
Discover Chemistry.
Computational Drug Discovery Methods
6.02
article

Designing of industry friendly pastilles of Rosuvastatin and Piperine integrating green chemistry and advanced statistical approach

Hardik Rana, Vaishali Thakkar, Chetna Modi, Grishma Patel
article en
4 citations

Abstract

Biliary excretion and poor aqueous solubility are significant concerns about Rosuvastatin's (RSV) low oral bioavailability. Incorporating the green chemistry concept into the formulation at an industrial scale is another major concern nowadays. The present study aimed to develop immediate-release (IR) pastilles of RSV and Piperine (PIP) using advanced data mining tools and exploring the concept of green chemistry. The secondary objective was to develop and validate the analytical method for estimating RSV and PIP. The Q-absorbance ratio method was developed and validated to estimate both drugs in formulation. The IR pastilles were formulated using a modified method incorporating a laboratory-scale pastillator. The pastilles were formulated by mixing, melting and solidifying the mixture in a single-step process. The concept of green chemistry, i.e., no use of organic solvent and no dust generation, was accomplished. The PIP was used as a bioenhancer, preventing RSV from entering the bile and increasing bioavailability and systemic exposure in the body. The RSV and PIP solubility were improved by formulating the pastilles using the hydrophilic carrier. The Box Behnken design (BBD) was applied to optimize pastilles. The amount of Soluplus, Primellose, and PEG 6000: HPMC E5 ratio were taken as critical material attributes (CMAs), and disintegration time, % CDR of RSV, and PIP were taken as critical quality attributes (CQAs). Various physical and drug-related evaluation parameters characterized the pastilles. The developed Q absorbance method for estimating RSV and PIP was accurate, precise, and robust. The observed isobestic point was 283 nm. QbD was implemented to develop a quality product and to find design space. BBD revealed a significant relationship between the chosen CQAs and CMAs. The optimal pastilles were composed of 42.33 mg Soluplus, 5.9% Primellose, 63.84 mg PEG-6000 and 27.36 mg HPMC E5. The designed pastilles were of uniform size and shape and had the desired characteristics. The formulation released a drug > 85% in an hour using Soluplus as a solubility enhancer and Primellose as a super disintegrant. The unexplored formulation, pastilles of RSV and PIP, was successfully developed in a single step, which has a faster dissolution rate, accomplishing a systematic approach. Green chemistry was explored using no organic solvent with no dust generation, leading to less pollution. The newer approach of formulating pastilles might apply to the industry as it is environment-friendly, single-step, and uses fewer excipients.

Discover Chemistry.Vol. 2(1)
Directorate of Medicinal and Aromatic Plants Research (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Computational Drug Discovery Methods
6.02
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