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February / March 2012


The Value of Lean Sigma: Improving GC Processes in Pharmaceutical R&D


by Karen Rome, Analytical Sciences, AstraZeneca, Macclesfield, SK10 2NA, UK


In an increasingly competitive market, today’s science and technology strategies must deliver a superior product to the market in less time and for less cost. Efficient product and process delivery are optimised by encouraging real time analysis; putting the technique into the hands of the customer is essential to this.


Gas Chromatography-Flame Ionisation Detection (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS) are techniques fundamental to the pharmaceutical R&D industry. These techniques measure the quality of raw materials and intermediates used in the manufacture of active pharmaceutical ingredient (API) and deliver knowledge into the synthetic organic process for effective learning. Raw materials, intermediates and impurities seen in the manufacturing process typically cover a wide range of polarities and are often highly structurally related, (e.g positional isomers). The supporting analytical methods must therefore be highly efficient and selective. As a consequence, compound specific methods are typically developed.


Internal data show compound specific methods are struggling to support increased project demand. This article discusses the combination of new lean methodologies with advances in column technologies in order to improve efficiency of the GC process from method development to commercial technology transfer. These improvements have successfully responded to increased project demands in our organisation without requirement for large-scale financial investment.


Introduction


During development each pharmaceutical candidate is assigned its own cross- functional team including synthetic organic and analytical chemists. The level of GC support to a project is dependant on the properties of the process and the impurities generated. As a result an analyst’s use of GC can vary from providing daily support to not using the technique for several months.


Historically the primary focus of GC method development has been for a sub- 30 minute method that is selective for the compound of interest and its related impurities. This approach has lead to a broad-spectrum of column chemistries and dimensions being used (our lab has over 185 different columns).


Increased data requirements and associated analytical support means instrument availability has reduced, and without financial investment or a change to the methodology, the current instruments will be unable to meet the project demands. In addition, a desire for increased product and process understanding from both analysts and synthetic chemists has resulted in an increase in the amount of data requested, and without increasing human resource the current way of working cannot fulfil project requirements. As a consequence,


Define ↓


Measure ↓


Analyse ↓


Improve ↓


Control ↓


The business opportunity, voice of the customer and visualise a primary process map


Time spent on value-added, business value and wasteful activities The root causes of wasteful activities Develop and implement improvement solutions


Continually monitor improvement solutions to sustain long-term impact


Table 1: The DMAIC approach uses five phases designed to reduce waste of an existing process


instruments are continually re-configured to meet project demands, resulting in high base level of training requirements. To successfully deliver projects, the GC process needs to reduce the turn around time for results and improve user familiarity.


Application of Lean Sigma To improve the GC process we have adapted the principles of Lean Sigma, a well- established methodology within the service and manufacturing industries.1,2


Lean Sigma


principles are applied to improve speed, quality and reduce cost by removing time spent on wasteful activities and to reduce defects by reducing process variation. The key principles of a Lean Sigma process are:


• Goal: Remove waste from the process


• Benefits: Improved capacity, reduced lead times, increased quality and increased customer focus


• Outcome: Increased productivity and efficiency of processes


We focused on reducing waste by removing the non-value adding activities. We used the Define; Measure; Analyse; Improve; Control (DMAIC) roadmap as detailed in Table 1. Each of these areas are discussed below.


Define Gas Chromatography is a powerful technique that is being underutilised in our department. The reasons for this are (i) the instrument availability is low, (ii) the process


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