Federaal Agentschap voor de Veiligheid van de Voedselketen

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Federaal Agentschap voor de Veiligheid van de Voedselketen

Validation of a Quantitative Analytical Procedure – Accuracy (total error) profile

Dr. Jacques O. DE BEER

Workshop IPH 27th April 2007

Scientific Institute of Public Health - Brussels (Belgium)

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Method Validation – General ConceptsMethod Validation – General ConceptsDifferent regulations relating to GLP, GMP,

GCP (OECD, EU)Normative or Regulatory documents (ISO

17025, ICH, EMEA, FDA, dir. 2002/657/EG) both suggest that analytical procedures both suggest that analytical procedures have to comply to certain acceptance criteria.have to comply to certain acceptance criteria.

This request imposes that these procedures are to be validated.- Some documents define the validation criteria- No proposals on experimental approaches !!- Limited to general concepts !!

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Introduction - DefinitionIntroduction - DefinitionMethod Validation: is the confirmation by examination

and the provision of objective evidence that the particular requirements for a specific intended use are fulfilled. EN ISO/IEC 17025 § 5.4.5.1

Methods need to be validated or revalidated:

before introduction into routine application whenever conditions change for which the method has

been validated (e.g. Instrument with different characteristics)

whenever the method is modified and modifications are outside original scope of the method.

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European and International regulatory bodies and European and International regulatory bodies and their guidelines on different aspects of QAtheir guidelines on different aspects of QA

Body Full name Guidance on

Eurachem Focus for Analytical Chemistry in Europe Method validation

CITAC Cooperation of International Traceability in Analytical Chemistry

Proficiency testingQuality Assurance

EA European Cooperation for Accreditation Accreditation

CEN European Committee for Normalization Standardization

IUPAC International Union of Pure & Applied Chem. Method validation

ISO International Standardization Organisation Standardisation

AOAC

ILAC

Association of Official Analytical Chemists

International Laboratory Accreditation Cooperat.

Internal qual. ControlProficiency testingAccreditation

FDA US Food and Drug Administration Method validation

USP United States Pharmacopoeia Method validation

ICH International Conference on Harmonization Method validation

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Objectives of an analytical procedureObjectives of an analytical procedureAble to quantify as accurately as possible

each unknown quantity to be determined.After analysis: the difference between

returned result xreturned result x and the unknown “true “true value µvalue µTT”” be small or < acceptance limit acceptance limit λλ:

-- < x - µ < x - µTT < < λ λ x - x - µµT T < < λ (eq.1)λ (eq.1) λλ : depends on objective of analytical

procedure e.g. 1-2 % on bulk, 5 % on pharmaceuticals, 15 % for biological samples previously defined

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Objectives of an analytical procedureObjectives of an analytical procedureAnalytical procedures characterized by (cfr. def.): “true bias” MM = systematic error (unknown) “true precision” σ²σ²MM = random error measured by a

standard deviation or variance (unknown)Estimates of biasbias and precisionprecision obtained by

experiments during the validationReliability of these estimates depends on adequacy

of experiments on known samples (Valid. Stds), experimental design, number of experiments

These estimates an intermediary but obligatory step to evaluate if procedure is likely or not to quantify with sufficient accuracy the unknown quantities; not objectives per se

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x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

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x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

Bias = +7 %RSD = 3%

Bias = +1 %RSD = 8%

Bias = 0 %RSD = 20%

Bias = +7 %RSD = 12%

Procedure 1 Procedure 2

Procedure 3 Procedure 4

Examples of procedures having the same acceptance limits = ± 15%

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Objectives of an analytical procedureObjectives of an analytical procedure FigureFigure: 4 different (hypothetical) methods giving the

distribution of 95% of the measures Each method has a true bias M , a true precision σ²M , a

common acceptance limit λ (= 15% bioanalytical procedure):

Procedure 3Procedure 3: negligible bias (0%); unsatisfactory precision (20% CV); too many measures beyond +/- 15% of the true value; does not fulfill objective

Procedure 4Procedure 4: bias (7%); precision (12%); important proportion outside acceptance limits; does not fulfill objective; but both < 15%: required by Washington Conf.

Procedures 1 and 2Procedures 1 and 2: fulfill (valid): at least 95% of results inside acceptance limits

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Objectives of an analytical procedureObjectives of an analytical procedure Procedure 1Procedure 1: presents a bias (+ 7%), but is very precise

(3% CV) Procedure 2Procedure 2: presents a negligible bias (+ 1%), but is

less precise (8% CV)

FIRST CONCLUSION: Differences between these two procedures don’t matter since results are never too far from true values of the sample to quantify.

Quality of results is far more important than the intrinsic characteristic properties of procedure in terms of bias or precision.

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Objectives of an analytical procedureObjectives of an analytical procedure To develop a procedure without bias and error

considerable cost; not acceptable strategy Analyst has to take minimal risks, compatible with the

analytical objectives (within reasonable time!!) Set up acceptable maximum proportion of measurements

that might be outside acceptance limits (acceptance limits (±±):): e.g. 5%5% or 20 %20 % of measurements outside (±) as

maximum riskrisk. inside triangles (next fig.) space of acceptable

procedures characterized by “true bias” “true bias” MM and a “true “true precision” precision” ²²MM

Acceptable procedures: 95, 80, 66% of measurements within ± 15% limits (recommendations Washington Conference) proportion depends on objectives!!!proportion depends on objectives!!!

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x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

True bias (%)

Tru

e p

reci

sion

(%

)

-10 -5 0 1050

5

10

15

20

66%

95%

80%

Proc.3

Proc.4

Proc.1

Proc.2

(0,20)

(7,12)

(1,8)

(7,3)

% measurements within % measurements within ± 15% bias-precision ± 15% bias-precision limitslimits

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Objectives of an analytical procedureObjectives of an analytical procedure Interior triangleInterior triangle = = area of all analytical procedures

of which 95% of result X should be included within acceptance limits (±), set according constraints of analytical domain

2 other triangles2 other triangles: proportions of 80% and 66% of measurements included within ± (accept. limits)

procedure with true bias =0true bias =0 ; true precision = true precision = 15%15% : only 66% will fall within acceptance limits (±)

procedure with true bias =0true bias =0 ; true precision = true precision = 8%8% : 95% will fall within acceptance limits (±)

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Objectives of an analytical procedureObjectives of an analytical procedureFigure: procedures 1 and 2procedures 1 and 2 located inside region of

acceptance this region guarantees that at least resp. 95% and

80% of the results are within acceptance limits (±)

for the same risk of the measurements outside acceptance limits, procedures 3 and 4procedures 3 and 4 not considered as valid

for more important risk, procedures 3 and 4procedures 3 and 4 could be valid.

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Objectives of an analytical procedureObjectives of an analytical procedureFURTHER CONCLUSION: Procedure qualified as acceptable if:

it “guarantees” that the difference between every sample measurement (x)(x) and its “true value” (µ(µTT)) is inside the predefined acceptance limits (±

In equation: P(P(x - x - µµT T < < ) ) eq. eq. 2)2) = proportion of measurements inside acceptance limits = acceptance limit, fixed a priori according objectives of the method

Expected proportion of measurements falling outside the acceptance limits risk of an analytical risk of an analytical procedureprocedure

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Objective of the validationObjective of the validationWhat ?

to give to the laboratories as well to the regulatory bodies “guarantees” that every single measurement performed in routine is close enough to the unknown “true value” of the sample: x - x - µµT T < acceptable limit < acceptable limit

Objective of validation: not simply to obtain estimates of bias and precision; it is to evaluate these guarantees and risks

These estimates of bias and precision are required to evaluate risks

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Objective of the validationObjective of the validationWith respect to this objective, 2 basic notions2 basic notions

should be considered:

““close enough”close enough” (eq. 1) meaning that routine measure will be less than the acceptance limit λ from its unknown “true value”

““guaranteed”,guaranteed”, (eq. 2) meaning that it is very likely that analysis result will be close enough to the true unknown value.

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Objective of the validationObjective of the validation

decision tools are needed giving “guarantees” that future measurements are reasonably inside acceptance limits

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Decision rulesDecision rulesCurrent position with respect to the decision rules

used in the phase of validation most of them based on use of the null hypothesis:

H0 : bias = 0 H0 : relative bias = 0 % H0 : recovery = 100 %

- Bias = x - µBias = x - µTT

- Relative bias = 100 (x - µRelative bias = 100 (x - µTT)/µ)/µTT

- Recovery = 100 x/µRecovery = 100 x/µTT A procedure wrongly declared adequate when the

95% C.I. of the average biasaverage bias includes 0 Test inadequate in validation context of analytical Test inadequate in validation context of analytical

proceduresprocedures because decision based on computation of rejection criterion of Student t-testrejection criterion of Student t-test

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x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

x

-30 -15 0 15 300

0.03

0.06

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0.12

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x

-30 -15 0 15 300

0.03

0.06

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0.12

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x

-30 -15 0 15 300

0.03

0.06

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0.12

0.15

True bias (%)

Tru

e p

reci

sion

(%

)

-10 -5 0 1050

5

10

15

20Proc.3

Proc.4

Proc.1

Proc.2

Test based on H0 = bias = 0

(7,3)

(0,20)

(1,8)

-15 15

(7,12)

PROCEDURES VALID

NOT VALID

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Decision rulesDecision rulesAccording to the decision rule based on the null

hypothesis H0 in fig.: procedures 2, 3 and 4 are valid and procedure 1 is rejected

But: procedure 1 shows reduced bias (+ 7%) and a small RSD (3%) outside triangleoutside triangle: rejected !!

procedure 3 has high RSD (20%), procedure 4 has bias of 7% and RSD of 12% accepted !!

bad precision large C.I. contains 0 as bias value method acceptedmethod accepted

good precision small C.I. may not contain 0 as bias value method rejectedmethod rejected

null hypothesis Hnull hypothesis H0 0 inadequate in analyt. validationinadequate in analyt. validation

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x

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x

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0.03

0.06

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x

-30 -15 0 15 300

0.03

0.06

0.09

0.12

0.15

True bias (%)

Tru

e p

reci

sion

(%

)

-10 -5 0 1050

5

10

15

20Proc.3

Proc.4

Proc.1

Proc.2

Test based on acceptance limits (± 15%)

β ≥ 80%

-15 15

(0,20)

(7,12)

(1,8)

(7,3)

PROCEDURES NOT VALID

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Decision rulesDecision rulesAccording to the decision rule based on use of

acceptance limits triangle in fig. with acceptible valid procedures

Triangle in fig.Triangle in fig. corresponds to procedures with measurement proportion inside acceptance limits (±λ) ≥≥ a prioria priori chosen proportionchosen proportion (e.g. 80%) as given by equation: P(P(x - x - µµT T < < ) ) (eq. 2) (eq. 2)

more sensible decision rule: procedures with good precisiongood precision acceptedbad precisionbad precision rejected

Biased procedure small variance: acceptable !!Procedure with higher variance needs small bias

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Decision rules: Accuracy profileDecision rules: Accuracy profile easy and visual decision rule:easy and visual decision rule: use of the accuracy profileaccuracy profile

within the acceptance limits (± ) Accuracy profileAccuracy profile constructed from the β-expectation

intervals on the expected measurements:- allows to decide on capability of analytical procedure to give results inside ± - describes dosage intervaldosage interval (range) in which the procedure is able to quantify with known accuracy and a fixed riskfixed risk at the end of the validation

e.g. risk of 5%risk of 5% “guarantee” that 95/100 future measurements will be included in acceptance limitsincluded in acceptance limits, fixed according requirements (1-2 % on bulk, 5 % on pharmaceut., 15 % in bioanalysis)

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Decision rulesDecision rules Accuracy profileAccuracy profile by concentration level (C1, C2,

...) obtained by computing β-expectation tolerance interval allows evaluating the proportion of expected measurements inside acceptance limitsacceptance limits

This intervalThis interval is obtained from available validated estimates of the bias and precision of the procedure (by concentration level)

This intervalThis interval of measurements expected within level (= proportion of measurements inside ) has -expectation confidence limits

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Decision rulesDecision rules If for each concentration level jconcentration level j β-expectation

tolerance interval are included within acceptance limits method accepted!

Tolerance interval calculation:Tolerance interval calculation:- what matters is: the guarantee of the results, expected in the future by the same analytical procedure in routine

- estimation of µj, ²B,j, ²W,j at every conc. j are used to estimate the expected proportion of observations within the predifined acceptance limits [-i.e.:

EEµ,µ, P[P[x - x - µµT T < < ]]MM, , MM

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Calculation of Calculation of ββ-expectation -expectation tolerance intervaltolerance intervalestimated bias (mean added

concentrations minus mean calculated concentrations)

j = conc. level these statistical parameters (trueness,

within/between precision) might be calculated for each concentration level from validation standards.

jj xµ ˆ̂

jbetween,

jwithin,

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Calculation of the interval in which a proportion β of all samples with a certain real concentration is observed (method of Mee): β expectation tolerance interval:

Calculation of Calculation of ββ-expectation -expectation tolerance intervaltolerance interval

jIFj

tj pnBQµ ..2

ˆ1

11

ˆ

2,

2,

2.. ˆˆˆ jBjWjIF ISO 5725-2: calculation of

within and between variance

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= degrees of freedom (Satterthwaite):p = number of series (days)n = number of replicates per series

Calculation of Calculation of ββ-expectation -expectation tolerance intervaltolerance interval

2,

2,

ˆ

ˆ

jW

jBjR

1

1

j

jj nR

RB

pnn

p

nR

R

11

1

1

12

2

tQ

Qt = β quantile of the Student’s t-distribution with ν degrees of

freedom

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interval representing in % the region containing β % of analysis results for a certain concentration level j :

j

jjIFj

tj

x

xpnB

Qµ

..2

ˆ1

11

ˆ

100

Calculation of Calculation of ββ-expectation -expectation tolerance intervaltolerance interval

after rearrangement:

100ˆ1

1ˆ ..

2j

jIF

jt xpnB

Qbias

jIFj

t CVpnB

Qbias ..2

11ˆ

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Interval consists of two terms:% bias +/- coefficient of variation for intermediate precision = expression of method accuracymethod is accurate for this concentration level if obtained tolerance interval is included within acceptance limits [-λ,λ]

Calculation of Calculation of ββ-expectation -expectation tolerance intervaltolerance interval

jIFj

tj CVpnB

QbiasL ..2

11ˆ

jIFj

tj CVpnB

QbiasU ..2

11ˆ

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Accuracy profileAccuracy profilebias (%)

concentration

+

C1 C2 C3 C4

LLQ ULQRANGE

mean relat. bias

acce

ptan

ce li

mit

s

dosage interval

0

bias limits of confidence

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Decision rulesDecision rulesEstimates of bias and variance are essential to

compute evaluation of the expected proportion of measurements within acceptance limits

Accuracy profile obtained by connecting the lower or upper limits of confidence (cfr. fig)

If a subsection (concentration range) falls outside the acceptance limits new limits of quantification be defined and a new dosage interval (Upper and Lower Limits of Quantification)

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Decision rules (conclusion)Decision rules (conclusion)Accuracy profileAccuracy profile represents limits “ULQ and

LLQ” in agreement with definition of criterion:

LLQLLQ = smallest quantity of the substance that can be measured with defined accuracy

Accuracy profileAccuracy profile as single decision tool: Allows reconciling the objectives of the

procedure and those of the validation Allows to visually grasp the capacity of the

procedure to fulfill its analytical objective

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Validation Protocols: Life CycleValidation Protocols: Life CycleValidation has to be considered as an element

intervening after the development of a new analytical procedure

Objective of procedure = to be used in routineUsage in routine must be coupled with a quality

control (QC) of which the 2 objectives2 objectives are: the validity of the found results on the unknown unknown

samplessamples the assessment of the continuity of the continuity of the

performancesperformances of the procedure at the time of its exploitation

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Protocols in validation phaseProtocols in validation phaseMain objectives in validation phase:- demonstrate specificity/selectivity- validate the response function (or calibration

model used in routine)- estimate precision (repeatability and intermediate

precision), trueness, accuracy- validate the quantitation limits, validate the range

(dosage interval); cfr. accuracy profile!- assess linearity of the analytical procedure

(results directly proportional to concentration in the sample – cfr. definitions)

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Protocols in validation phaseProtocols in validation phase preparation of calibration standardscalibration standards (CS) with fixed

number of concentration levelsconcentration levels and repetitions by levelrepetitions by level preparation of the validation standardsvalidation standards (VS) in the

matrix; are independent samplesindependent samplesVS prepared and treated independenly as future samples essential for good estimation of between-series between-series variance.variance.

To estimate intermediate precisionintermediate precision, VS analyzed on different daysdifferent days, equipmentequipment and by different operatorsdifferent operators.

Validation phase is ultimate stage before exploitation; allows to estimate procedure’s performances in the expected experimental conditions allows to check procedure’s capability to quantify unknown sample

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Protocols in validation phaseProtocols in validation phaseQuestion whether or not presence of a matrix matrix

effect.effect.If no matrix effectno matrix effect, question is which

concentration levels will be used for calibration apply described validation protocolsvalidation protocols (V1V1 and V2V2)

Evidence of matrix effectmatrix effect: apply protocol V5protocol V5In case of doubtdoubt: apply protocols V3 and V4protocols V3 and V4

according to calibration levels (cfr.Table)Which types of standards (CS and VS), types of standards (CS and VS),

concentration levels?concentration levels?VSVS prepared in matrix and independent; must

similate future samplessimilate future samples

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Choise of number of CS and VS depending on Choise of number of CS and VS depending on selected protocolselected protocol

standardsstandards conc. conc. levelslevels

ProtocolProtocol (no matrix, doubt, matrix)

V1 V2 V3 V4 V5

CS. calibration out matrix

LowMidHigh

22(*)

22(-)

22

2(*)

22(-)

2

CS. calibration in matrix

LowMidHigh

Addit.

22(*)

22(-)

2

22(-)

22(+)

VS. validation in matrix

LowMidHigh

333

333

333

333

333

Minimum number of series 3 3 3 3 3

Total number of experiments 3333 4545(39)(39)

3939 6363(51)(51)

4545(39)(39)

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Description of protocol V1Description of protocol V1

Calibrationstandards

Validationstandards

(1)

(1)

(1) Additional validation standards (linearity ICH)

Series 1 Series 2 Series 3

Conc

R

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Description of protocol V2Description of protocol V2

Calibrationstandards

Validationstandards

(1)

(1)

(1) Additional validation standards (linearity ICH)

Series 1 Series 2 Series 3

( )) )( (

R

Conc

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Description of protocol V3Description of protocol V3CalibrationStandards without matrix

Validationstandards

(1)

(1)

(1) Additional validation standards (linearity ICH)

Series 1 Series 2 Series 3R

Conc

CalibrationStandards within matrix

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Possible concentation levels by type of Possible concentation levels by type of procedure (e.g. 6 comparative procedures)procedure (e.g. 6 comparative procedures)

1. Determination of single chemical substancesingle chemical substance; reference available or determination of active ingredient in a pharmaceutical speciality (matrix)

2. Determination of available synthesis impurityavailable synthesis impurity in an active substance or pharmaceutical speciality (matrix) at concentration levels > LOQconcentration levels > LOQ

3. Determination of available synthesis impurityavailable synthesis impurity in an active substance or pharmaceutical speciality (matrix) around impurity limitaround impurity limit (impurity limit > LOQ)

4. Simultaneous determination of chemical substance and chemical substance and one of its non-available impuritiesone of its non-available impurities in this substance or pharmaceutical speciality (use substance as tracer to allowed maximum concentration of impurity)

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Possible concentation levels by type of Possible concentation levels by type of procedure (e.g. 6 comparative procedures)procedure (e.g. 6 comparative procedures)

5. Determination of active substance for active substance for measuring dissolution kineticsmeasuring dissolution kinetics for a dry dosage form (matrix)

6. Determination of active ingredient and its active ingredient and its metabolites in plasmametabolites in plasma (drugs), drug residues, ...

WHICH CONCENTRATION LEVELS ? cfr. TABLE

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Examples of possible concentration Examples of possible concentration levels by type of procedurelevels by type of procedureProcedure 1 2 3 4 5 6

Calibration standards

LowMidHigh

addition

100%(120%)

LOQ

(½ Cmax)

(Cmax)

80% LA100% LA

(120% LA)

LOQ/LA(50%)120%

Cmin

(50%)120%

LOQ

½ Cmax

Cmax

X

Validation standards

LowMidHigh

80%100%120%

LOQ

½ Cmax

Cmax

80% LA100% LA120% LA

LOQ/LA50%120%

Cmin

(50%)120%

LOQ

½ Cmax

Cmax

LA = admitted limit; Cmax = max. conc.; Cmin = min. conc.

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Protocols in validation phaseProtocols in validation phaseIdentify relationship between response Y and relationship between response Y and

concentration Xconcentration X using calibration standardscalibration standards (response functionresponse function).

Regression modelsRegression models are fitted, accuracy profilesaccuracy profiles calculated, one model selected decision about validity of the procedure of interest.

Model: depends on procedure typeprocedure type (pharmaceutical, bio-analytical, immuno-assay)

fixed method objectivesfixed method objectivesLinear regression (origin or not) envisaged.Mathematical transformations applied on X and YQuadratic regression may be useful

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Protocols in validation phaseProtocols in validation phaseBack-calculation of estimated VS concentrationsVS concentrations

by series by by calibration curve equations calibration curve equationsFor each concentration level estimation of estimation of

trueness and precisiontrueness and precision

calculation of limitslimits forfor accuracyaccuracy : cfr. CIj (bias) (include large proportion of results)

accuracy profile for each fitted modelaccuracy profile for each fitted modelAccuracy profile visual decision toolvisual decision tool to evaluate

capability of the method if not within pre-fixed acceptance limits: - restrict dosis range new limits of quantification- extend acceptance limits (possible??)

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A

C

E

B

D

F

Bia

s (%

)B

ias

(%)

Bia

s (%

)

Bia

s (%

)B

ias

(%)

Bia

s (%

)

15

15

15

15

15

15

-15

-15

-15

-15

-15

-15

1 2 3 4 50 0 1 2 3 4 5Concentration Concentration

ACCURACY PROFILES with same VALIDATION PROTOCOL (0.01 – 5.0 ng/ml)

quadratic regression

weighed linear regression

linear regressionlinear regression throug 0

linear regression on square root transformed data

linear regression on log transformed data

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Protocols in validation phaseProtocols in validation phaseFigure: Accuracy profilesFigure: Accuracy profiles for validation of dosing

procedure of chemical substance in biological matrix.

Protocol V5Protocol V5 applied + some concentration levelsEssentially low levels good estimation of LOQ2 of 6 response functionsresponse functions (A: quadratic regress. +

B: weighed regression) answer objective: acceptance limits ± 15%

accuracy profile allows to decide about method capability:

Quantifiable dosing range with known accuracy: 0.01 – 5.0 ng/ml at risk = 5%

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CONCLUSIONSCONCLUSIONSLack of generalisation between different validation

protocols harmonized approachharmonized approachProposal to review objectives of the validationreview objectives of the validation

according to objectives of the analytical procedureobjectives of the analytical procedureDistinction between diagnosis rulesdiagnosis rules and decision decision

rulesrulesObjectives of validation not simply to obtain not simply to obtain

estimates of bias and precisionestimates of bias and precision but also:To evaluate risks or confidencesrisks or confidences that any single

measurement is close enough to unknown true valueclose enough to unknown true valueTrueness, precision, linearity, ..., no longer

sufficient to make these guarantees.

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CONCLUSIONSCONCLUSIONSAdapted decision tool accuracy profile of the

analytical procedure, based on: -expectation tolerance interval at each concentration

level– concept of total error (bias + standard deviation)

Allows to bring together objectives of the procedure and those of validation

Allows to visually grasp the capacity of the procedure to fulfil its objectives

to control risk associated with its use in routine

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ReferencesReferencesC. Hartmann et al., An analysis of the Washington

Conference Report on bioanalytical method validationJ. Pharm. Biomed. Anal., 12(11) (1994) 1337-1343

Ph. Hubert et al., The SFSTP guide on the validation of chromatographic methods for drug bioanalysis: from the Washington Conference to the laboratory.Anal. Chim. Acta, Anal. Chim. Acta, 391391 (1999) 135-148 (1999) 135-148

P. Chiap et al., Validation of an automated method for the liquid chromatographic determination of atenolol in plasma: application of a new validation protocol.Anal. Chim. Acta, Anal. Chim. Acta, 391391 (1999) 227-238 (1999) 227-238

52

ReferencesReferences

B. Boulanger et al., An analysis of the SFSTP guide on validation of chromatographic bioanalytical methods: progress and limitations.J. Pharm. Biomed. Anal., J. Pharm. Biomed. Anal., 3232 (2003) 753-765 (2003) 753-765

Ph. Hubert et al., Validation des procédures analytiques quantitatives. Harmonisation des démarches.STP Pharma Pratiques, STP Pharma Pratiques, 13(3)13(3) (2003) 101-138 (2003) 101-138

Ph. Hubert et al., Harmonization of strategies for the validation of quantitative analytical procedures. A SFSTP proposal – part IJ. Pharm. Biomed. Anal., J. Pharm. Biomed. Anal., 3636 (2004) 579-586 (2004) 579-586

53

Ph. Hubert et al., Validation des procédures analytiques quantitatives. Harmonisation des démarches. Partie II - StatstiquesSTP Pharma Pratiques, STP Pharma Pratiques, 16(1)16(1) (2006) 28 – 58 (2006) 28 – 58

Ph. Hubert et al., Validation des procédures analytiques quantitatives. Harmonisation des démarches. Partie III – Exemples d’applicationSTP Pharma Pratiques, STP Pharma Pratiques, 16(2)16(2) (2006) 87 – 121 (2006) 87 – 121

M. Feinberg et al., New advances in method validation and measurement uncertainty aimed at improving the quality of chemical dataAnal. Bioanal. Chem 380 (2004) 502-514Anal. Bioanal. Chem 380 (2004) 502-514

M. Feinberg et al., A global approach to method validation and measurement uncertaintyAccred. Qual. Assur 11 (2006) 3-9Accred. Qual. Assur 11 (2006) 3-9

ReferencesReferences