What does this research mean for the field?

Statistical methods and Design of Experiments (DoE), supported by software tools, are essential in the pharmaceutical industry for ensuring drug safety, efficacy, and regulatory compliance throughout the drug development lifecycle. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To review the implementation, core methodologies, and practical challenges of statistical analysis and experimental design across the pharmaceutical drug development lifecycle.

August 29, 2026Open Access

Application of Statistical Analysis in Pharmaceutical Industry

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Authors

MTMohini R. Nayse, Rutika R. Perane,,Pranjal D. Kulkarni, Prajakta M. Buchude, Sandesh S. Sawant, Prof. K. N. TarkaseSavitribai Phule Pune University

Discussion

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Implication

Narrative review demonstrates the critical utility of statistical modeling in pharmaceutical manufacturing and trials, highlighting its necessity for safety, optimization, and regulatory compliance.

Key Points

To review the implementation, core methodologies, and practical challenges of statistical analysis and experimental design across the pharmaceutical drug development lifecycle.
Synthesized primary statistical approaches in drug research, including descriptive statistics, multivariate regression, and principal component analysis.
Assessed Design of Experiments (DoE) strategies, focusing on central composite designs and analytical computing software including SAS, Minitab, and SPSS.
Statistical modeling and experimental designs qualitatively enhance pharmaceutical formulation efficiency, trial evaluation, and regulatory compliance.
Application of dedicated statistical software streamlines complex data processing, though workflows remain vulnerable to systematic bias and data quality limitations.

Cite This Study

Mohini R. Nayse, Rutika R. Perane,,Pranjal D. Kulkarni, Prajakta M. Buchude, Sandesh S. Sawant, Prof. K. N. Tarkase (2026) studied this question.

synapsesocial.com/papers/6a9299bb8e5d7d1fc0c11d0d https://doi.org/10.5281/zenodo.22121470

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August 29, 2026Open Access

Application of Statistical Analysis in Pharmaceutical Industry

View Full Paper

Ask AI

Bookmark

Authors

MTMohini R. Nayse, Rutika R. Perane,,Pranjal D. Kulkarni, Prajakta M. Buchude, Sandesh S. Sawant, Prof. K. N. TarkaseSavitribai Phule Pune University

Discussion

Member takes

Implication

Narrative review demonstrates the critical utility of statistical modeling in pharmaceutical manufacturing and trials, highlighting its necessity for safety, optimization, and regulatory compliance.

Key Points

To review the implementation, core methodologies, and practical challenges of statistical analysis and experimental design across the pharmaceutical drug development lifecycle.
Synthesized primary statistical approaches in drug research, including descriptive statistics, multivariate regression, and principal component analysis.
Assessed Design of Experiments (DoE) strategies, focusing on central composite designs and analytical computing software including SAS, Minitab, and SPSS.
Statistical modeling and experimental designs qualitatively enhance pharmaceutical formulation efficiency, trial evaluation, and regulatory compliance.
Application of dedicated statistical software streamlines complex data processing, though workflows remain vulnerable to systematic bias and data quality limitations.

Cite This Study

Mohini R. Nayse, Rutika R. Perane,,Pranjal D. Kulkarni, Prajakta M. Buchude, Sandesh S. Sawant, Prof. K. N. Tarkase (2026) studied this question.

synapsesocial.com/papers/6a9299bb8e5d7d1fc0c11d0d https://doi.org/10.5281/zenodo.22121470

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