• To understand the laboratory quality requirements and appreciate the need for a quality system accordingto the International Standards Organization ISO 17025.
• To understand the significance of calibration methods and traceability.
• Identify the factors which have to be considered when choosing an analysis method.
• To understand how to validate analytical methods.
• To use international the Guide to Lab Quality for accreditation standard methods.
• To recognize the characteristics of a laboratory environment that affect the performance of instrumentsand hence influence the validity of measurements.
• To use a standard safety work ethic in the laboratory.

The course is designed for people who implement, maintain and review laboratory quality systems. It is suitable for all laboratory staff including managers, quality assurance officers, lab technicians, chemists, chemical engineers and instrument engineers.

1. Introduction to lab quality and accreditation

2. Lab Quality Management Requirements ISO 17025 (organization, quality system, document control, reviewof contracts, subcontracting, purchasing, service to the client, complaints, control of non-conforming work,improvement, corrective actions, preventive actions, control of quality records, internal audits,management review).

3. Lab Quality Technical Requirements ISO 17025 (personnel, accommodation, test methods and validation,equipment, measurement traceability, sampling, test items, quality control, reports/calibration certificates)

4. Quality in the laboratory:

• Quality of the sample
• Analyte manipulation technique
• Selecting the method
• Chemicals
• Glassware and equipment
• Instrumental technique
• Preparation

5. Making measurements and reporting:

• Capacity factor
• Selectivity factor
• Column efficiency
• Column resolution
• Evaluation of peaks area
• Calibration using external and internal standards
• Instrumental graph-interpolated method
• The correlation coefficient
• Calculation of analyte concentration
• Standard addition-extrapolated method
• Errors in quantitative analysis
• Standard deviation
• Confidence limit
• Detection limit
• Outliers test
• Optimization design
• Repeatability and reproducibility

6. Validation of analytical methods
7. Quality management functions
8. Laboratory accreditation

More details of the course outline can be provided on request.