Six Sigma in the Pharmaceutical Industry

Nunnally, Brian K.; McConnell, John

doi:10.1201/9781420054408

Cited by 15 publications

(6 citation statements)

References 6 publications

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“…It is a probability that the modification of the fermentation unit of the bioprocess or improvement of operations in downstream processing may result in the design and optimization advancement of the pharmaceutical production process [ 48 ]. It is found that quality control strategies (including Six Sigma) as a means to either improve production or to enhance product quality in the pharmaceutical industries have been proposed or predicted through simulations by diverse groups [ 49 – 53 ]. An early study forecasted a theoretical model for penicillin synthesis, with qualitative prediction of different developments that are generally countered in experiments and also reviewed various models for secondary metabolite manufacturing [ 49 ].…”

Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

“…Case studies that involve integration of Six Sigma methodology in pharmaceutical production unit have been conducted in related areas such as biological, parenteral operations, safety, and improved control of potency [ 53 ]. Six Sigma can serve as the driving force for continuous improvement by identifying the root cause or causes of low process yield, due to excessive variance in the desired specifications [ 52 ].…”

Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

“…It has been proposed that the Six Sigma methodology may decrease discrepancy and focus on significant elements to attain continuous improvement by identifying and analyzing all of the constituent steps of prophylactic antibiotic administration and then observing them for improvement [ 55 ]. According to Nunnally and McConnell [ 53 ], the application of Six Sigma has helped in minimizing deviations in two of the key variables, pH and specific potency, in a fermentation set-up. Recently, a very interesting work has focused on an amalgamation of Six Sigma methodology with incorporated design and control and has predicted superior yield of archetypal penicillin [ 52 ].…”

Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

See 2 more Smart Citations

A Proposal for Six Sigma Integration for Large-Scale Production of Penicillin G and Subsequent Conversion to 6-APA

Nandi

Pan

Potumarthi

et al. 2014

Journal of Analytical Methods in Chemistry

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Six Sigma methodology has been successfully applied to daily operations by several leading global private firms including GE and Motorola, to leverage their net profits. Comparatively, limited studies have been conducted to find out whether this highly successful methodology can be applied to research and development (R&D). In the current study, we have reviewed and proposed a process for a probable integration of Six Sigma methodology to large-scale production of Penicillin G and its subsequent conversion to 6-aminopenicillanic acid (6-APA). It is anticipated that the important aspects of quality control and quality assurance will highly benefit from the integration of Six Sigma methodology in mass production of Penicillin G and/or its conversion to 6-APA.

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Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

Section: Six Sigma Methodology: An Overviewmentioning

confidence: 99%

See 1 more Smart Citation

A Proposal for Six Sigma Integration for Large-Scale Production of Penicillin G and Subsequent Conversion to 6-APA

Nandi

Pan

Potumarthi

et al. 2014

Journal of Analytical Methods in Chemistry

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show abstract

“…In addition, the larger the process variation, the more likely it is for a process to fail to meet manufacturing specifications. In fact, reduced process variation can even lower cycle time in manufacturing . As such, the ability to quantify and model variation is a key element in QbD.…”

Section: Role Of Batch-to-batch Variation In Qbdmentioning

confidence: 99%

Batch-to-Batch Variation: A Key Component for Modeling Chemical Manufacturing Processes

Mockus

Peterson

Laínez

et al. 2014

Org. Process Res. Dev.

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For chemical manufacturing processes, the chemical kinetics literature contains virtually no mention of quantitative models that involve batch-to-batch variation. Models for chemical process manufacturing quality improvement are being more carefully considered, particularly by the pharmaceutical industry and its regulators. This is evidenced in part by the recent ICH Q11 regulatory guidance on drug substance manufacture and quality. Quality improvement has been defined as a reduction in variation about a target. Hence the modeling of process variation plays an important role in quantifying quality improvement. Given that batch-to-batch variation is often a dominant source of process variation (usually exceeding measurement error variation), it is important for process models to incorporate such variance components. In this paper, we show how chemical kinetic models can incorporate batch-to-batch variation as well as measurement error. In addition, we show that these models can be used to quantify the reliability of meeting process specifications using Bayesian statistical methods. We also compare some different Bayesian computational approaches and recommend some software packages to aid with the computations.

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“…In an attempt to explore a most probably strong causal relationship between the symptoms and their reasoning, it is becoming quite obvious that the major root cause might be found lying deep within the management culture of the pharmaceutical industry, the values of which reflect much more the world of business rather than the rational world of statistical thinking and knowledge management (11,16).…”

mentioning

confidence: 99%