Aims and Objectives
This subject aims to introduce good (quality control) laboratory practices for laboratory analysts and supervisors who are involved in regulated laboratories. The subject will also be of relevance to anyone with a general interest in GMP, GCP and GLP.
On completion of this subject students will be able to:
- State basic concepts and requirements of Good Laboratory Practices (GLPs).
- Implement basic concepts and requirements of G(QC)LPs in a regulated Laboratory.
- Implement techniques and procedures for the validation and control of analytical test methods.
- State the techniques and procedures for the validation and control of biological assays.
- List how to qualify laboratory instruments:
- Utilise techniques and procedures for statistical analysis of typical laboratory data.
- Construct statistical and practical sampling plans.
- Establish of stability programs
Content
This subject consists of 8 modules or topics:
#1 Introduction to Good (Quality Control) Laboratory Practices (GLPs)
This module introduces the participants to the basic concepts and requirements of Good Laboratory Practices (GLPs).
- List the key elements and basic principles that make up GLPs in an analytical chemical laboratory.
- Understand their professional role and responsibilities in contributing to GLPs.
- Design a table of contents for the Laboratory Quality Management Systems.
#2 G(QC)LPs in a Regulated Environment
This module introduces the participants to the basic concepts and requirements of GLPs in a regulated Pharmaceutical Laboratory.
- Relate the importance of laboratory records, raw data, traceability and documents to GMP compliance and regulatory inspections.
- State the requirements for Good Automated Laboratory Practices (GALP).
- Review laboratory systems for compliance with recognised standards.
- Implement GLP systems to ensure compliance with international pharmaceutical standards.
- Devise strategies for handling out of specification conditions.
#3 Analytical Method Validation
This module is designed to provide participants with techniques and procedures for the validation, analysis and control of analytical test methods.
- List the performance parameters required for analytical method validation.
- List the acceptance criteria for analytical method performance parameters.
- Prepare an analytical method validation protocol.
- List requirements for interlaboratory method transfer.
- Calculate the capability of a test method and determine the optimum number of workups.
#4 Biological Assay Validation & Control
This module is designed to provide participants with techniques and procedures for the validation, analysis and control of biological assays.
- List the parameters required for accepting biological assays.
- Identify potential bias in assay designs.
- Implement procedures to control biological assays and minimise bias.
- Combine biological assays using weighting techniques.
- Apply an outliers test to a data set.
#5 IQ/OQ for Laboratory Equipment
This module cover the essential cGMP/GLP requirements for the qualification of laboratory instruments:
- Understand the IQ/OQ requirements for instruments.
- State the importance of vendor involvement.
- Describe the difference between IQ, OQ and PQ.
- List specifications and calibration requirements for typical instruments eg. spectrophotometers, HPLC and dissolution apparatus.
- Describe different approaches for the validation of complex and simple equipment.
#6 Basic Statistics for Quality Control Laboratories
This module is designed to provide participants with techniques and procedures for analysis of typical statistical laboratory data.
- Describe the difference between precision and accuracy.
- Calculate the mean, standard deviation and co-efficient of variation for data sets.
- Identify attribute and variables data.
- Use normal distribution theory to examine the spread of laboratory data.
- State the basis and principle of hypothesis testing.
- Apply tests on Variance (F tests), Means (t tests), calculate and interpret confidence intervals and test a data-set for outliers.
#7 Pharmaceutical Sampling Plans
This module discusses the special problems associated with pharmaceutical sampling plans. It reviews the theory and application of statistical and practical sampling plans.
- Understand the applications of and limitations of sampling plans.
- Read and apply simple attribute sampling plans.
- Determine the appropriate sample size for a given confidence level.
#8 Stability Programs
This module covers the essential cGMP requirements for the establishment of stability programs - pre and post approval.
- State the rules and regulations regarding stability programs.
- Set up a stability programs schedule.
- Evaluate basic stability data using regression analysis.
- Calculate an expiry time for a typical stability trial.
