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Stacey Sandell 22 nd October 2009 – Laboratory Management.

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1 Stacey Sandell 22 nd October 2009 – Laboratory Management

2 ◦ Quality – Reliably and repeatedly attaining a standard of excellence. ◦ Quality Control – Use of scientific methods to maintain the most accurate data possible. ◦ Quality Assurance – A program monitoring and controlling laboratory procedures and results, to insure the reliability of results.

3  The World Health Organisation (WHO) External Assessment of Health Laboratories (1981) usefully describes Internal Quality Control (IQC) as “the set of procedures undertaken by the staff of a laboratory for continuously assessing laboratory work and the emergent results, in order to decide if they are reliable enough to be released”.  IQC applies to all staff all of the time.  Staff training is crucial.

4  Examples: ◦ Acceptance of suitably labelled samples which match the referral form. ◦ Checking tube transfers. ◦ Visual inspection and quantification of extracted DNAs.  Allows a rapid response to failure. ◦ Storage of DNA. ◦ Recording current batch and lot numbers. ◦ If using kits use exactly as specified by the manufacturer (storage conditions, expiry dates and protocol).

5  Examples: ◦ Routine maintenance of machines and calibration of laboratory equipment.  e.g. PCR machines and pipettes. ◦ Using suitable controls for each test.  If appropriate using controls which are at the limit of the test. ◦ SNP checking primers. ◦ Staff training. ◦ Results checking and confirming certain positive results. ◦ Checking demographic information before report is released. ◦ Follow SOPs and best practice guidelines. ◦ Accurate filing. ◦ Audit can help to assess quality control.

6 Internal validation is performed on newly designed techniques/diseases before they enter diagnostic service to establish if they are fit for purpose.  Validation is the process by which we acquire the necessary information to: ◦ Assess the ability of the procedure to obtain reliable results. ◦ Determine the conditions under which such results can be obtained. ◦ Define the limitations of the procedure.  Commercial kits have already been extensively validated by their manufacturers, but they should always undergo internal verification to insure that the product works as it is intended.

7  JAK2 – detection of the acquired point mutation V617F using a combination of ARMS PCR and pyrosequencing.  Validation ◦ Changes were made to the published ARMS method because the specificity was too low. ◦ Control band added to ARMS method. ◦ 100% plasmid control mixed with normal to establish limits of both tests. ◦ Optimum conditions established. ◦ SOP written.  Quality control ◦ 2%, 12% and 100% mutant controls on every run. ◦ Multiple water controls for pyrosequencing. ◦ Repeat discrepant results.

8  CSCE – technique used as the primary screen in the high throughput laboratory.  Extensive validation by NGRL: ◦ Mutation position and GC content validated. ◦ Each fragment optimised to give optimum peak height. ◦ Over 300 known mutations tested (blind).  Quality control ◦ Positive control, polymorphism control and water control for each fragment. ◦ Resequence normals if shift detected on CSCE. ◦ Peaks need to reach a minimum height.

9  Benefits of moving to automation: ◦ Fully automated systems have complete sample tracking. ◦ Standardised conditions. ◦ Larger capacity and faster throughput of samples. ◦ Less hands-on time. ◦ Reduced handling of reagents and samples. ◦ Batch information automatically electronically stored.

10  Drawbacks of moving to automation: ◦ Increased risk of product carry over. ◦ Often associated with a change in method (primer redesign and optimisation of new technique). ◦ Difficult to get all fragments to work under standard conditions. ◦ Machine breakdown (difficult to convert from automated to manual). ◦ Some step cannot be performed by the robot (check gels). ◦ More random failures.

11  Maintenance of quality. ◦ Concurrent/parallel runs. ◦ Blind testing. ◦ Lots of controls  Lots of water controls. ◦ Optimisation to get standardisation.  Peak height is important. ◦ Extra checks for sample tracking.  Scan tubes and batch plates. ◦ Pipetting accuracy.  Verification as already validated by manufacturer.

12  Maintenance of quality. ◦ Check for carry over.  Wax.  PCRs. ◦ Check files generated by automated systems.  Check all scenarios (1-92 samples).  Comparison program. ◦ Intensive training. ◦ Regular maintenance and calibration of robots.

13  EMQN draft best practice guidelines for laboratory quality control (2002)  CMGS draft guidelines for internal quality control of sample reception and DNA extraction (2004).  NGRL website (Wessex) – for examples of validation

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