Transcript Title

Towards establishing uniform validation
procedures in Sasol analytical laboratories
Piet de Coning
Vina Thakally-Govender
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Overview of Sasol processes
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Sasol global involvement
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“Cleaner” fuels
Clean fuels burn cleanly
Emissions benefits are
immediately realisable
Particulate emissions
use
transport
production
upstream
Acidifying emissions
(SOx and NOx)
use
GTL Diesel
Low sulphur
refinery diesel
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production
upstream
Method format
Based on ISO 78-2
Divided into five sections
Site specific cover page
Document information
Number, Date, Revision history, Distribution, etc.
Method summary – Not IP sensitive
Can be copied for reports
Procedure – May be IP sensitive
Some methods are proprietary, others licensed e.g. ASTM
Typical data
Excluded from the method
Validation data
Issued as a separate report
Site and instrument specific procedures
Documented as Standard operating procedures or Work instructions
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Why should methods be validated?
Officially:
To prove that a method is fit for its purpose
Practically:
To protect the analyst from unreasonable demands / expectations
To increase confidence in the analytical ability of the analyst / laboratory
To facilitate laboratory management
To give the analyst increased confidence in his/her results
Why estimate the measurement Uncertainty ?
Officially:
It is an ISO requirement: Result = value + uncertainty + units
Practically:
It sums up most of the validation in a single figure
Uncertainty = Confidence
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Why are methods not validated?
It is not necessary
Highly qualified scientists
We have Integrity
But – do we have documented evidence of this
that will stand up in court?
It costs too much
CEO office
Executive
boardroom
Senior
management
Human
resources
Not so, if offset against product failure and loss of sales
We do not have the time
Finances
“Strangely there is never enough time to do things properly,
but yet we always seem to find the time to do things
over”
Street
The equipment is the best and maintained by
qualified service engineers
level
entrance
“Never before has it been so easy, and with so little effort,
to produce bad results”
Attitude
Sales
Staff
caffeteria
Typist pool
Foyer with pot plants
Executive car park
Central
air
conditioning
Building
utilities
Analytical chemistry is the poor relative of the chemistry disciplines
“It is not that people are ignorant, it is just that they know so much that isn't so”
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Analytical
laboratory
How?
Validation
Do only what is required to establish fitness for purpose
Do only what can be ...
Incorporated in the method uncertainty
Be used in the routine application of the method
Do additional validation tests only when ...
Specifically requested by the customer
The analyst considers it necessary
Uncertainty
Establish the purpose
Determine uncertainty requirement (how detailed?) in terms of
Method purpose
Customer requirements
Analyst’s experience & evaluation
Statistics
Use standard statistical tests at 95% confidence
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The requirement specification
Establish the purpose
From this follows a validation plan
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What ?
Determined during method
development:
Specificity / Selectivity
Robustness / Ruggedness
Recovery - correction
Determined from method
calibration
Sensitivity
Range
Quantitation limits
upper
lower
Detection limit
Accuracy
The single most important
parameter
Depends on:
Calibration
Trueness
Precision
Uncertainty
Determined from:
Calibration
Trueness
Precision
Uncertainty is the numerical
value of the accuracy!
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Calibration
Grubb’s tests
The linearity, slope, intercept and
regression uncertainties - from Excel
ANOVA function
The formula for conc. calculation provided
Range = LQL – UQL
= lowest – highest standard
Calibration curve with prediction limits
Prediction limits used for MDL calculation
Regression significance tested with t- and
F-tests
Fit evaluated using P-value and residual
plots
P-value on std.dev. used to determine if
WLS should be used
Several weighting models provided
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Accuracy
Accuracy as trueness
Three ways of doing it
Trueness by comparison with a reference standard
Trueness using a recovery study
Trueness by comparison with an alternative method
Accuracy as precision
Repeatability
Same analyst, same instrument, short time-scale
Reproducibility
Different analysts, different instruments, extended time-scale
Intermediate precision
Between repeatability and reproducibility
Precision limit
R  t  2   R
Qualitative analyses
False positives and false negatives
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Uncertainty
Uncertainty is a lot more uncertain
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Implementation
The validation manual
Validation philosophy
Validation procedures
Tools – generic formats, spreadsheets and workbooks
Statistical and mathematical procedures
Presentations
Management: High level overview – essentials
Supervisors: More detailed presentation
Workshops
Laboratory personnel
Selected methods
Next steps
Incorporate suggestions and criticism (e.g. flowcharts)
Benchmark validation procedure
Continued improvement
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Acknowledgements
The Validation workgroup:
Anna Potgieter
(Sasol Infrachem laboratories)
Johann Drews
(Sasol Infrachem laboratories)
Madelyn Bekker
(Sasol Waxes)
Martiens Henning
(Sasol Secunda Shared
Services)
Rene Engelbrecht
(Sasol Infrachem laboratories)
Roos van der Heide
(Sasol Solvents)
Vina Thakally-Govender
(Sasol Technology R&D,
Analytical Solutions)
Special acknowledgement:
Prof. Willem de Beer
(Tswane University of
Technology)
Angelique Botha
(National Metrology Institiute of
South Africa)
David Coleman
(Applied Statistician, Alcoa
Technical Center, PA, USA)
Lynn Vanatta
(Air Liquide-Balazs™ Analytical
Services, TX, USA)
piet.deconing @ sasol.com
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