Authors
Dr. Frank Deruyck
University College Ghent
Dr. Volker Kraft
JMP
Muralidhara A
JMP
Objective
Use control charts to understand process stability and analyze the patterns of process variation.
Background
FVM Pharmaceuticals is an international drug manufacturer, specialized in manufacturing finished formulations that cater to the most demanding global needs. FVM delivers contract manufacturing of tablets, capsules, and liquids.
A typical manufacturing process involves milling an active pharmaceutical ingredient (API) into a powder of uniform particle size. The milled material is then blended with other ingredients to bulk up and evenly distribute the API. This blended material is then compressed into tablets, which are finally coated to aid shelf life, taste, and other properties. At the end of the process, various quality parameters including critical to quality (CTQ) metrics are populated, which further drive batch acceptance.
The process starts with a raw material that is a concentrated emulsion containing two organic compounds. The raw material is supplied by two vendors, and the incoming quality is monitored by measuring the concentration of the compounds in milligram per liter (mg/l). Each day, a quality lab operator takes raw input material in two batches from each supplier into the process.
The process of chromatography is a laboratory technique for the separation of a mixture. The company is currently leveraging gas chromatography (GC), a common type of chromatography used in analytical chemistry for separating and analyzing compounds that can be vaporized without decomposition.
The Task
Recently, the Total Quality Management (TQM) team observed a significant variability in the quality of the drug delivered. To address this issue, a cross-functional team was formed to identify the root cause of the problem and then solve it. Lawrence, head of the team and a quality engineer, is a firm believer of dataenabled decision making. He also knows that building a strong quality culture into the process demands the application of statistical techniques to discover actionable insights. He is aware that bringing operational excellence into a manufacturing process is a sequential and multistage process starting from raw material to final inspection. Fortunately, methodologies like Quality by Design (QbD) ensure high quality throughout the production process (starting from raw material to finished product) while leaving enough flexibility in the manufacturing system.
The challenge for Lawrence’s team is to resist just doing firefighting. To find a more sustainable solution, their strategy is to identify the key drivers for process variation and to improve stability, and finally, to optimize the process settings to better meet the customer requirements.
In this first stage of the project, we help Lawrence with the investigation of the raw material:
- -Can we assume normality for our data?
- -What is driving the variability in Compound 1 and Compound 2: Day, Batch or Vendor?
- -Can the process be considered as stable and under control?
- -Can the process be considered as capable (with a Cpk of 1.33 or higher)?
- -Which vendor is supplying the compounds that better meet the specifications?
- -Is the process stable from a multivariate perspective?
- -Which actions should be taken by Vendor A and Vendor B to improve the stability and/or capability of the two compounds?
- -What should be recommended as a follow-up study?