01 : Vol. 01, No. 09-September.2026 - BTS INTERNATIONAL ADVANCED PHARMACEUTICAL SCIENCES JOURNAL
Statistical Quality Control Tools for Total Quality Management in Pharma ceutical Product Development
Abstract
The pharmaceutical sector is known for being highly regulated, meaning the goods produced must adhere to strict industry standards. The development of pharmaceuticals incorporates total quality management (TQM) to ensure that patients receive products of the highest quality. TQM fosters an efficient approach for maintaining and improving product quality and customer
satisfaction through systematic processes. Achieving TQM requires the critical implementation of statistical quality control (SQC) tools. The execution of TQM is based on data evaluation, reduced process variability, enhanced dependability, and improved decision-making due to the
application of SQC tools. This review has a particular focus on the use of SQC tools in the development of pharmaceutical products with an emphasis on enhancing quality metrics, determining critical process variables, meeting regulatory requirements, applicability, benefits,
and limitations. These tools enable organizations to exercise control over their processes, maintain compliance with regulations, decrease variability, and manage product quality. Through these approaches, pharmaceutical companies will exceed the compliance requirements set forth by the governing bodies and will be able to deliver quality products. The use of SQC tools demonstrates clear improvements in product quality, cost efficiencies, accelerated time-to-market, and reduced risks. Incorporation of SQC tools into the TQM framework greatly enhances operational efficiency, competitiveness in the market, and most importantly, patient and customer safety and satisfaction. The strategic use of these tools enables pharmaceutical companies to maintain an industry-leading position with high quality, long-term success, and sustainable growth.
Keywords: Control Charts, Pharmaceutical Development, Process Control, Root cause analysis, Statistical Quality Control, Total Quality Management.