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Pharmaceutical Industry: Process Capability & Control

Capability

Regulatory, Compliance & Quality
Technical Services

Client

A major global pharmaceutical company with facilities in the U.S. and Puerto Rico manufacturing ethical drugs in a variety of dosage forms.

Problem

A drug product with a successful two-year manufacturing history was suddenly receiving field complaints about an unacceptable degree of variation in a non-release parameter characteristic. Two drug product lot recalls and a large scale in-house investigation resulted. Through a high-level root cause analysis the client determined that 82% of the variation for the parameter was due to the API lot used but could not identify the specific drivers of variation. Data for the key parameters resided in various locations (analytical lab, batch records, raw material CoAs, etc.) and in both electronic and paper form, compounding the problem. 

Approach

Using Tunnell’s Process Capability and Control solution, an approach encompassing both quantitative and qualitative analysis for identifying root causes of process parameter variation, the Tunnell team:

• Collected historical process data for all variables and organized it into a single electronic database, which included over 600 data rows across 70 individual production lots
• Developed process control charts and performed process capability analysis on all release parameters
• Carried out statistical predictive modeling, individually plotting each release parameter against every raw material and in-process characteristic in the database
• Conducted a scientific and engineering review of every step of the API manufacturing process and of other supporting documents
• Completed process mapping and in-depth focus interviews with key personnel

Results

Multiple sources of process variation were identified and new process knowledge was gained for the cause-and-effect relationships between key process parameters.

• Specific recommendations were developed to reduce process variation, to improve process capability and reduce risk of API and drug product rejection and investigations
• Product Characterization Package (PCP) for the API was assembled and delivered
• Statistical predictive model was developed on the “problem” characteristic with a R2 =93%; the model condition set to be used as a basis for design of confirmatory trials, batch record revisions, and subsequent production runs
• Detailed recommendations were made regarding equipment sizing, in-process procedures, sampling, material balance, measurement systems analysis, and batch record gaps and process data collected

 

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