Engineering automated systems for pharmaceutical manufacturing: quality, regulations and business performance

The pharmaceutical sector is very heavily regulated Drug safety regulations form one of the pillars of this regulation. The manufacture of pharmaceuticals is carried out in an environment of onerous regulatory requirements, often from several national and international regulatory bodies. The quality systems operated by drug manufacturers and their regulatory practices have an important impact on product quality. The quality and regulatory requirements apply not only to handling of the medicinal products, but also to the physical and electronic systems used in the manufacture of those products, and extend to automated systems used to support quality assurance operations. Design, development, building and support of such systems are ultimately the responsibility of the drug manufacturer. The quality and regulatory requirements for automated systems are passed down the supply chain to suppliers. In the last two decades of the 20th century there has been a proliferation in the use of computerised and automated systems for use in, or to support manufacturing. Correspondingly, regulatory requirements have been imposed on the manufacturing industry. This work used survey research and factor analysis to establish relationships between quality and regulatory practices, and between both quality and regulatory practices and business performance for suppliers of automated systems into the pharmaceutical market. A survey instrument and an administration strategy were developed from a review of the literature. It was established empirically that quality practices and regulatory practices were strongly related. Specific facets of quality practices and regulatory practices were found to have had a significant impact on both market share and competitiveness expectations and also profit and sales expectations. Differences in practices and performance were established for various levels of automation complexity and criticality, where criticality was a function of the risk the respondent’s system posed to the manufacture of their customer’s products.