Validation concept considerations
Download
1 / 39

Validation: concept, & considerations - PowerPoint PPT Presentation


  • 168 Views
  • Uploaded on

Validation: concept, & considerations. Beni Kaufman. Will be presenting:. Review The concept Validation Components and their measurement experimental design of PCR validation Process vs. Modular validation. References:. Guidance for Industry: Bioanalytical Method Validation.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Validation: concept, & considerations' - hua


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Will be presenting
Will be presenting:

  • Review

    • The concept

    • Validation Components and their measurement

    • experimental design of PCR validation

  • Process vs. Modular validation


References
References:

  • Guidance for Industry: Bioanalytical Method Validation.

    U.S. Department of Health and Human Services, Food and Drug Administration (FDA), Center for Drug Evaluation and Research (CDER), Center for Veterinary Medicine (CVM) May 2001

  • PCR Validation & Performance Characteristics

    Analytical Environmental Immunochemical Consortium (AEIC) Biotech Consensus Paper; S. Charlton, R. Giroux, D. Hondred, C. Lipton, K. Worden

  • Validation of Analytical procedures: Methodology, International Conference on Harmonization of Technical Requirements for the Registration of Pharmaceuticals for Human Use, 1996


Warning
Warning

Politicallysensitivematerial!

Politically!!!

sensitive material!!

Discuses components… avoid criteria!



Selectivity specificity
Selectivity(Specificity)

  • The ability of the analytical method to differentiate (and quantify) the analyte in the presence of other components in the sample (to amplify only the Sequence of interest.)

    Selectivity may be affected by:

    • Interference:

      • Cross amplification of non target sequences (function of, Primer design)

    • Matrix effects:

      • Background signal (Sybr green)

      • Quality & quantity of DNA

      • Reaction conditions (master-mix, thermocycling profile)


Selectivity cont
Selectivity(Cont.)

Assessed by:

  • Fragment length analysis (right size amplicon)

    • Electrophoresis gel analysis

    • CE


Validation concept considerations

Selectivity(Cont.)

Dissociation Curve

do not use r2774, 02-08-2006, 15Hr 58Min.mxp

  • Assessed by:

  • Melting curve analysis


Precision
Precision

  • The closeness of agreement (degree of scatter) between a series of measurements obtained from multiple sampling of the same homogeneous sample under the prescribed conditions.

  • Variation among rep.s within an assay

  • Same as Repeatability

  • Measured by parameters of variation, mostly %CV



Accuracy trueness
Accuracy/Trueness

  • The closeness of mean test results to the true value of the analyte.

    Qualitative assay:

    Measured by error rate:

    % false positive = False positives/ # of negatives

    % false negative = False negatives/# of positives


Accuracy trueness cont
Accuracy/Trueness (cont.)

  • Quantitative assay:

    • The mean recovery at several points across the quantitative range

      % Recovery =100 (observed/actual)

      (also,

      the deviation of the mean from the true value)



Linearity range
Linearity & Range

  • Linearity: The ability of the assay (within a given range) to obtain test results which are directly proportional to the concentration/amount of the analyte

  • Range: The interval between the upper & lower concentrations of an analyte for which the assay has suitable levels of precision, accuracy & linearity.


Linearity range cont
Linearity & Range (cont.)

  • Linearity and Range can be evaluated simultaneously

  • Demonstrated on a dilution series (transgene genomic DNA/null genomic DNA) across a relevant range of concentrations

  • The Range is established by confirming acceptable degrees of linearity, accuracy, & precision, within or at the extremes of a specified range.


Linearity evaluated
Linearity evaluated

  • Linearity is evaluated by a plot of signals as a function of analyte concentration & linear regression analysis.


Sensitivity
Sensitivity

Two concepts of sensitivity:

  • Change in response per amount of reactant -> dose-response curve

    In PCR the dose response is derived from the amplification efficiency - We optimize the assay for a maximal dose response (~100% amp. Efficiency)

    Therefore,

  • dose-response is reflected in the standard curve. It’s captured in the Linearity component &

    • is the basis for quantification

    • The source of our resolution power


Sensitivity cont
Sensitivity (cont.)

  • Limit of detection (LOD), The minimum amount of target analyte that can be detected with a given level of confidence

    • Applies to QL & QT PCR

      Limit of quantification (LOQ), The lowest amount of target analyte that can be quantified with acceptable levels of precision and accuracy.

    • Applies only to QT PCR


Determining lod loq
Determining LOD & LOQ:

“Spiking” series:

  • Decreasing amounts of transgenic seed are mixed in with conventional seed to create a series of seed pools with varying proportion of transgenes.

  • Seed pools are ground to flour

  • DNA isolated from flour and used for PCR; targeting the corresponding target sequence.


Sensitivity cont1
Sensitivity (cont.)

The LOD will be lowest spike detected with an acceptable confidence level.

The LOQ will be the lowest spike that can be differentiated from zerowith an acceptable confidence level


Ruggedness
Ruggedness

  • The effectiveness of an analytical process in face of small environmental/operating conditions, such as:

    • Different analysts

    • Different equipment

    • Different labs

  • Effectiveness is measured as changes in the precision or accuracy.


Ruggedness cont
Ruggedness (cont.)

Effectiveness is measured as changes in the precision or accuracy:

  • For qualitative PCR evaluated by the changes in error rate and LOD

  • For quantitative PCR evaluated by HORRAT

    Where the Relative Standard Deviation of Reproducibility (RSDr) is given as:

    RSDr = 2(1-0.5lnC) ~ 2C-0.1505

    (C= concentration or quantity) And

    HORRAT = RSDr(observed)/RSDr(expected)

    HORRAT is expected to be close to 1

  • Horwitz, W. (1995) Protocol for the design, conduct and interpretation of method performance studies, Pure and Appl. Chem, 67:331-343



Robustness
Robustness

  • Describes the reliability of an analysis with respect to variations in method parameters.

  • Measured by experimentally defining the critical range of:

    • Template concentration

    • Primer concentration

    • Mg2 Concentration

    • Thermocycling temperature range

      Usually part of the assay optimization, prior to the validation process.




Validation concept considerations
But,

the right

experimental design

Can take away some of the edge…

For example:


Qt pcr validation design
QT PCR Validation design:

Experiment:

  • Series of conventional seed pools fortified with transgenic seed at a decreasing ratio.

    (For example: from 2% to 0.01% at -0.5X increments).

  • Highest level serves as positive control

  • Negative control

  • Five reps per level

  • Isolate, quantify, normalize, PCR (IQNP)

  • All in all: 8 spike levels x 5 replicates = 40 amplifications

  • Repeat 3 times, 3 different instruments, different analysts,

    (3 different dates (?) Astrological effect)


Qt pcr validation design1
QT PCR Validation design:

Analyze

  • Selectivity: all amplifications yielded the right size amplicon (on gel, or by Tm)

  • Precision: Calculate %CV among reps within plates

  • Accuracy: Calculate mean % recovery within plates

  • Linearity: use samples as standards – create standard curve- test linearity

  • Range: based on results of Precision, Accuracy, & Linearity; define range.

  • LOD: Identify the lowest detected spike with an accepted confidence limit

  • LOQ: Identify lowest spike that its confidence interval does not overlap zero.

  • Ruggedness: HORRAT, or alternatively, ANOVA between plates, runs, annalists.


Ql pcr validation design
QL PCR Validation design

Experiment

  • Series of conventional seed pools fortified with transgenic seed at a decreasing ratio.

    (… from 2% to 0.01% at -0.5X increments).

  • Highest level serves as positive control

  • Negative control

  • Five reps per level

  • IQNP

    Analyze:

  • Selectivity: all amplifications yielded the right size amplicon (On gel or by Tm)

  • LOD: The lowest spike level to yield amplification = tentative LOD


Ql pcr validation design1
QL PCR Validation design

Experiment:

  • Two plates, each plate, half null, and half spiked at tentative LOD.

  • Isolate, quantify, normalize,

  • PCR the two plates on different instruments, different analysts, etc

    Analyze:

  • Accuracy: Calculate positive and negative error rate.

  • Confirm LOD: if %false negative < defined criteria (5?)

  • Ruggedness: compare error rates between plates/instruments/analysts



Not only pcr
Not only PCR!

The testing process is made of a number of consecutive steps, all can be validated, some have to be validated

  • Sampling

  • Sub-sampling

  • DNA Isolation

  • DNA Quantification

  • DNA Normalization

  • PCR

  • Post-PCR

  • Data Analysis


Modular validation
Modular Validation

The recognition that many of the applications – steps, in the testing process require independent validation of their function

&

For better efficiency

Brought about the idea of Modular Validation

A. Holst-Jensen, J-AOAC, 1995


Modular validation1
Modular Validation

Validate each step (module).

Once, validated, different modules can be combined in to a process that no longer require validation

DNA is DNA!?

IT IS NOT.


Whole process validation
Whole Process Validation

  • Particle size

  • DNA isolation efficiency

  • Instrument error

  • Matrix effect

  • Standards

    All affect the out come of the testing process, therefore, the validation is of the whole process and only in the context of the given matrix, instrumentation, & standards…


Validation concept considerations

You can’t “mix & match”

Any deviation…will require

VALIDATION.