Validation of Analytical Methods Based on Mass Spectrometric

Analytica Chimica Acta 483 (2003) 325–334

Validation of analytical methods based on mass spectrometricdetection according to the “2002/657/EC” European

decision: guideline and application

Jean-Philippe Antignac∗, Bruno Le Bizec, Fabrice Monteau, François AndreLaboratoire d’étude des résidus et contaminants dans les aliments (LABERCA), Ecole Nationale Vétérinaire de Nantes,

BP 50707, F-44307 Nantes Cedex 3, France

Received 27 June 2002; received in revised form 3 October 2002; accepted 22 October 2002

Abstract

The purpose of the present paper is to present an interpretation of the concepts introduced in the new 2002/657/EC Europeandecision and to propose a practical guideline dedicated to the validation of analytical methods based on mass spectrometry.Considering both the statistical significance of the results and practical aspects, the minimal number of assays permitting asatisfying validation to be achieved appeared to be 45 for qualitative methods and 55 for quantitative methods. The parametersvalidated with this protocol are specificity, sensitivity, linearity, decision limit (CCα), repeatability, detection capability (CCβ)and recovery. It is proposed to estimate these parameters on the basis of the most intense (or unique) ion for screening methodsand on the basis of the “critical ion” (less intense ion permitting the unambiguous identification of the analyte according tothe required number of identification points) for confirmatory methods. An application of this guideline is presented anddiscussed, through the validation of a liquid chromatography-tandem mass spectrometric (LC–MS/MS) method dedicated tothe determination of the corticosteroid triamcinolone acetonide (Tri Acn) in meat samples.© 2002 Elsevier Science B.V. All rights reserved.

Keywords: Validation; 2002/657/EC; Mass spectrometry; Decision limit (CCα); Detection capability (CCβ)

1. Introduction

Validation of analytical methods dedicated to themeasurement of a physico-chemical parameter orproperty relative to a substance, material or systemis not a recent problem. When developing a theoryor a technical process, scientists have always tried todemonstrate the validity of their work using originalexperimental methodology or a more conventionaldata set, for example some repetitions of the measure-

∗ Corresponding author. Tel.:+33-2-40-68-77-66;fax: +33-2-40-68-78-78.E-mail address: [email protected] (J.-P. Antignac).

ment in identical and/or different experimental con-ditions. Nevertheless, the diversity of the applicationfields, validation procedures, estimated parameters, aswell as terms and concepts definitions, led to a lack ofobjective quality criteria and harmonization, causinggreat difficulty in comparing methods or results.

Moreover, the exponential development of appliedmathematics, statistics and informatics as well astheoretical considerations from several expert groupshas introduced much in the way of normalization, re-searching and universal concepts. The two main workaxes have been on one side the definition of pertinent“quality indicators” of an analytical method, and onthe other side their associated calculation modalities.

0003-2670/03/$ – see front matter © 2002 Elsevier Science B.V. All rights reserved.PII: S0003-2670(02)01379-X

326 J.-P. Antignac et al. / Analytica Chimica Acta 483 (2003) 325–334

This approach permitted real progress but some diffi-culties remained, linked both to the existence of sev-eral official institutions (ISO, CODEX, IUPAC, etc.)each with their own specifications, and to the diffi-culty of changing some practical habit in laboratories.The best illustrative example are the concepts limitof detection (LOD) and limit of identification (LOI).These two parameters are probably the most widelyapplied to estimate method performance in terms ofsensitivity. However, the nature of the measured sig-nal, the calculation mode (practical approach basedon the signal-to-noise ratio or theoretical approachbased on the noise amplitude of blank samples), theunambiguous identification criteria, as well as thestatistical significance (number of repetitions, toler-ance and confidence level) are not systematically welldefined, even though important literature has beendedicated to these concepts[1–6].

At the European level, an important working groupwas mandated to propose a decision, now referenced2002/657/EC,1 to harmonize the characterization andthe validation procedure of analytical methods perfor-mance. This decision provides rules on how methodsare to be used in the testing of official samples accord-ing to Article 15, paragraph 1, second sentence of theCouncil Directive 96/23/EC, and common criteria forthe interpretation of analytical results of official con-trol laboratories for samples taken according to thesame Directive. This decision shall not be applicablewhere for certain substances more particular rules havebeen laid down in Community Legislation. The appli-cation field of this reference document is analysis ofbiological matrices for residue and contaminants, in-cluding organic and mineral substances, forbidden andregulated substances, based on qualitative and quan-titative methods, screening and confirmation analysis.One merit of such a document is to extend some gen-eral concepts to a very large panel of detection tech-niques, and to propose a common backbone for thevalidation of the corresponding analytical methods.The best example could be the notion of identificationpoints for confirmatory analysis[7] and the introduc-tion of the decision limit (CCα) and detection capabil-ity (CCβ) concepts to replace LOD and LOI. However,

1 2002/657/EC Commission Decision of 12 August 2002. “Im-plementing Council Directive 96/23/EC concerning the perfor-mance of analytical methods and the interpretation of results”.

this very complete and complex document is not al-ways very easy to read for the analyst, and the need fora practical “fit-for-purpose” guideline clearly appearedboth for the reference and application laboratories.

In this context, the purpose of the present paperwas to extract from the original reference documentonly the necessary theoretical and practical recom-mendations for the validation of analytical methodsdedicated to the analysis (qualitative/quantitative,screening/confirmation) of residues and contaminants(forbidden/regulated) in biological matrices. Onlymass spectrometry was considered as the main de-tection technique for use in this domain. First, thepractical meaning of the decision limit and detec-tion capability concepts will be presented. Secondly,a practical validation guideline will be proposed,which was built considering a discussed compro-mise between statistical significance and practicalaspects. Finally, an application of this guideline willbe presented and discussed, corresponding to theliquid chromatography-tandem mass spectrometry(LC–MS/MS) analysis of the corticosteroid fluoci-nolone acetonide residues in meat samples.

2. Decision limit and detection capability

In the 2002/657/EC European decision, the deci-sion limit (CCα) was defined as “the limit at andabove which it can be concluded with an error prob-ability of α that a sample is non-compliant”, and thedetection capability (CCβ) as “the smallest content ofthe substance that may be detected, identified and/orquantified in a sample with an error probability ofβ”.In fact, these concepts had already been introducedin the ISO/11843-1 normative document[8], to pro-pose a method fixing a limit from which a system canbe declared different from its basic state (Fig. 1). Inthe present case, the system is a diagnostic ion chro-matogram of the target analyte, and the basic statecorresponds to this ion chromatogram for a blank sam-ple (forbidden substances) or for a sample containingthe analyte at the MRL concentration (regulated com-pounds). As shown inFig. 2, the measured value forcharacterizing the system is the analyte signal ampli-tude (noise or analyte peak height), expressed relativeto the internal standard signal amplitude. In practice,two main sources have to be considered to explain

J.-P. Antignac et al. / Analytica Chimica Acta 483 (2003) 325–334 327

Fig. 1. Definition of CCα and CCβ according to the ISO/11943 normative document.

the variability observed for the recorded signal; onefrom the noise (mainly due to the matrix effect, de-pending of the method specificity) and one from themeasurement (depending of the method sensitivityand repeatability). CCα and CCβ permits these twodifferent factors to be characterized.

The signal associated with CCα corresponds to amaximal noise amplitude (forbidden substances) or toa maximal signal amplitude for a sample containingthe analyte at the MRL concentration (regulated sub-stances), i.e. the amplitude that can only be exceededin α% of the cases. This signal can be considered asan horizontal line drawn on the ion chromatogramto materialize a limit below which the observed sig-nal can be declared as not statistically different fromthe noise (forbidden substances) or not statisticallyhigher than the one induced by a sample contain-ing the analyte at the MRL concentration (regulated

substances). In other words, when the recorded sig-nal is lower than CCα, the sample can be declaredcompliant (analyte absent or present at a concentra-tion lower than the MRL) with a confidence level of(1 − α).

CCβ is the critical real measured concentrationabove which it can be concluded that the analyteis unambiguously present (forbidden substances) orpresent at a concentration unambiguously higher thanthe MRL (regulated substances). In other word, sup-posing the analysis of a sample (1) giving a signalhigher than the decision limit and (2) leading to anestimated concentrationC, this sample can be de-clared non-compliant (analyte present or present ata concentration higher than the MRL) ifC ≥ CCβ,with a confidence level of (1− β).

For samples giving a signal higher than the deci-sion limit but leading to an estimated concentration


Fig. 2. Signal to consider for blank sample (upper) and for sample containing the analyte (lower).

between CCα and CCβ, high suspicion can be gener-ated, but from a statistical point of view, the result re-mains unclassified. Depending on political decisions,protection of producers, industrials or consumers, thesample would be declared compliant or not compliant.A second possibility should be to use an alternativemethod if available and/or increase the concentrationof the extract.

In theory, CCα and CCβ can be calculated for eachdifferent signal characterizing the analyte. However,some additional considerations are needed depend-ing on the screening or confirmatory purpose of the

method. For screening methods, e.g. mass spectrom-etry based on the most intense ion, or any otherscreening detection technique, these values can onlybe estimated for the unique diagnostic signal, andconsequently are not subject to further identificationcriteria requirements. For confirmatory methods, i.e.mainly mass spectrometry based on several ions per-mitting a minimal identification score (3 or 4 depend-ing on the substance) to be achieved, These valueshave to be preferably estimated for the more “criticalion” (in general the less intense one), and only afterhaving verified that all the identification criteria are


in the correct tolerance range (relative retention time,different ion ratio).

3. Proposed validation protocol

3.1. Qualitative and/or forbidden substances

Our objective was to find a compromise betweenthe 2002/657/EC decision requirements, an opti-mized organization for the assays to use the sameexperiments to validate several parameters, and somepractical aspects and limitations linked to a labora-tory activity. Finally, it was assumed that 45 assaysshould permit a satisfactory validation if conductedas follows: five concentration levels for calibration,2× 10 blank samples, and 2× 10 spiked samples. Itis recommended to divide these assays into five seriesconducted on separate days.

The analysis of at least 20 blank samples, from dif-ferent origins to check the ruggedness of the method,permits the specificity to be evaluated through the av-erage (µN) and standard deviation (σN) of the noiseamplitude, expressed relative to the internal standardsignal amplitude. The calibration should preferablybe realized on a pool of the 20 previously analyzedblank samples and include at least five fortificationlevels, using in addition the previously estimatednoise average (µN) as a forced intercept. The totalnumber of six concentration levels appears to satisfyfor many authors, and for the 2002/657/EC decision,to well define a calibration graph, but some dis-cussions still remain concerning the choice of theselevels as well as their equidistant or non-equidistantseparation. Our position was not to use systemati-cally equidistant levels, but on one side to verify thelinearity of the concentration domain globally usedin practice (for example 0–100 ng ml−1) and on theother side to give more importance to the low concen-trations (for example 0–5–10–15–50–100 ng ml−1),because this part of the graph has a strong influenceon the CCα and CCβ values. Finally, this calibra-tion graph permits linearity to be evaluated throughthe regression coefficient (R2) and the sensitivitythrough the slope of the fitted graph (a). Then,a andσN permit the decision limit (CCα) to be calculatedconsidering the equation of the calibration graph(Eq. (1)), whereI is the signal amplitude andC the

concentration, and the definition of CCα (Eq. (2)),the combination leading to the expression given byEq. (3).

ICCα=µN+aCCα (1)

ICCα=µN+2.33σN (2)

CCα=2.33σN

a(3)

An alternative method consists of using the stan-dard error of the fitted calibration graph interpolatedintercept (σ e) instead of the average of the noiseamplitude (σN). The advantage of this second ap-proach would be to avoid the analysis of the 20 blanksamples and to require only several (at least three)repetitions at each fortification level. Nevertheless,the interpolated intercept appears strongly sensitiveto the linearity, to the considered fortification levelsand to the repeatability of each three assays series.Consequently, some interpretation difficulties canarise with this method in the case of negative inter-polated intercept or standard error artificially under-or over-estimated. For example, a linearity better than0.9999 due to the influence of one particular highfortification level and an apparent high repeatabilitycan lead to a very poor intercept standard error andfinally to a largely underestimated CCα value. Thisexplains the choice made at present to consider thereal measured noise variability value (σN) and toforce the fitted calibration graph by the correspond-ing average (µN). However, it is recognized that thisvery critical point will merit further discussion andpractical testing.

The analysis of 20 spiked samples permits therepeatability to be estimated through the standarddeviation of the signal amplitude (σ s). Ideally, thefortification level used should be exactly CCβ. Inpractice, this concentration is estimated during themethod development. Typically, a concentration in-ducing a signal-to-noise ratio of ca. 6 can be used. Inorder to minimize this estimation error, considerationof the signal relative standard deviation ((R.S.D.)s)is preferable to the standard deviation (σ s). Finally,σN, a, and (R.S.D.)s permit to the detection capa-bility (CCβ) to be calculated, considering the cal-ibration equation (Eq. (4)), where I is the signalamplitude andC the concentration, and the defi-nition of CCβ (Eq. (5)), the combination of these


two formula leading to the final expression given byEq. (6).

ICCβ = µN + 2.33σN + 1.64σCCβ

= µN + 2.33σN + 1.64(R.S.D.)sICCβ (4)

CCβ = 2.33σN + 1.64µN(R.S.D.)s

a[1 − 1.64(R.S.D.)s](5)

3.2. Quantitative methods and/or regulatedsubstances

It was assumed that 55 assays should permit a sat-isfying validation if conducted as follows. Calibrationshould be realized using real extracted samples whenpossible and include blank samples and at least fivefortification levels around the critical value (MRL) andblank samples. The minimal number of assays shouldbe 20 replicates at the MRL concentration, 10 repli-cates at 0.5MRL and 1.5MRL, and 5 replicates un-der 0.5MRL and above 1.5MRL as well as for blanksamples. These assays authorize the evaluation of thelinearity around the critical value through the regres-sion coefficient (R2), the sensitivity through the slopeof the fitted graph (a), and the intercept correspondingto the noise amplitude average obtained on the basisof the five blank sample analyses (µN).

The 20 spiked samples at the MRL concentrationgive access to the repeatability at this concentrationlevel through the average (µMRL) and standard de-viation (σMRL) of the signal amplitude. Finally,a,µN, µMRL andσMRL permit the decision limit CCαto be calculated considering the calibration equation(Eq. (6)), were I is the signal amplitude andC theconcentration, and the definition of CCα (Eq. (7)), thecombination of these two formula leading to the finalexpression given byEq. (8).

ICCα = µN + aCCα (6)

ICCα = µMRL + 1.64σMRL (7)

CCα = µMRL−µN + 1.64σMRL

a(8)

The 10 spiked samples at the 1.5MRL concentra-tion to the estimation of the repeatability at this con-centration level through the standard deviation of thesignal amplitude (σ s). Ideally, the fortification levelused should be exactly CCβ. As previously discussed,

this concentration is estimated during method devel-opment (concentration inducing a signal-to-noise ratio>6) and considering the relative standard deviation ofthe signal ((R.S.D.)s) rather than its standard deviation(σ s) to minimize the estimation error on the concentra-tion used for fortification. Finally,a, µN, µMRL, σMRLand (R.S.D.)s permit the detection capability (CCβ)to be calculated, considering the calibration equation(Eq. (9)), wereI is the signal amplitude andC the con-centration, and the definition of CCβ (Eq. (10)), thecombination of these two formula leading to the finalexpression given by theEq. (11).

ICCβ = µN + aCCβ (9)

ICCβ = µMRL + 1.64σMRL + 1.64σCCβ

= µMRL + 1.64σMRL + 1.64(R.S.D.)sICCβ

(10)

CCβ=µMRL − µN + 1.64σMRL + 1.64µN(R.S.D.)s

a[1 − 1.64(R.S.D.)s](11)

4. Application example

The analytical method presented to illustrate theproposed validation procedure concerns the analysisfor the corticosteroid triamcinolone acetonide (TriAcn) in meat samples. The extraction and purificationmethod was presented elsewhere[9]. The techniquewas liquid chromatography-tandem mass spectrome-try using negative electrospray ionization and MRMacquisition using two transitions. The analyte responsewas always related to the internal standard response(IS: triamcinolone acétonide-d6, added at 5 ng ml−1 ineach sample). The results are summarized inTable 1.

The specificity, in terms of absence of interfer-ing compounds appearing on the ion chromatograms(Fig. 3) and noise variability, was greatly improved bythe use of MS/MS but clearly also by the efficient pu-rification process. The response linearity was found tobe satisfactory with aR2 value >0.99 for the two tran-sitions (Fig. 4). The sensitivity ratio between the twocalibration slopes (0.82) perfectly reflected the inten-sity ratio between the two product ions (0.85± 0.04,n = 20). For the spiked samples, all the required

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Fig. 3. Triamcinolone acetonide diagnostic ion chromatograms for a blank meat sample (left) and for a 150 ng ml−1 spiked meat sample (right).


Fig. 4. Calibration graphs determined on the basis of triamcinolone acetonide meat hair samples for the two diagnostic MRM transitions.

Fig. 5. Test of the identification criteria requirements for the spiked samples used for the method validation.


Table 1Validation results for the method dedicated to the LC–MS/MS determinations of the corticosteroid triamcinolone acetonide (Tri Acn) inmeat samples (15 g)

Process Parametera Signal 1 (more intense) Signal 2 (less intense)

(0) Diagnostic signals Analyte (Tri Can) 493 > 413 493 > 375Internal standard (Tri Can-d6) 499 > 419

(1) Blank samples Specificity (µN; σN) 0.0122; 0.006 0.0124; 0.007

(2) Calibration curve Concentration levels (ng ml−1) 0.15; 0.3; 1.5; 3; 7.5Linearity (R2) 0.9985 0.9984Sensitivity (a) 0.2141 0.1748

(3) Spiked samples Concentration level (ng ml−1) 1.50

Repeatability (R.S.D.)Signal (%) 5.7 5.8RRT (%) 0.4Ratio (%) 4.6

Recovery (%) 96.6 100

(4) Critical limits CCα (ng ml−1) 0.07 0.10CCβ (ng ml−1) 0.08 0.11

a R2, coefficient of determination;a, slope of the fitted curve; (µN; σN), average and standard deviation of the noise; R.S.D., relativestandard deviation; RRT, relative retention time.

identification criteria were successfully tested usinga self-made automatic diagnostic file (Fig. 5) andthe repeatability of the two signals appeared verysatisfying (5.7 and 5.8%, respectively). The decisionlimit and the detection capability were calculated foreach signal (Table 1). However, it was assumed thatthe values with main practical interest were the deci-sion limit estimated on the basis of the more intensetransition (the objective at this level is to detect theanalyte) and the detection capability estimated on thebasis of the less intense transition (the objective atthis level is to identify unambiguously the analyte).The obtained corresponding values (CCα = 70 ppt)and detection capability (CCβ = 110 ppt) appearedvery satisfying and coherent with the observation ofthe ion chromatograms in term of signal-to-noise ratioas shown inFig. 3.

5. Conclusion

The main objective for the presentation of this val-idation guideline was to underline the necessary re-quirements of the 2002/657/EC European decision for

its application in the field of drugs and contaminantresidue analysis by mass spectrometry. It appeared thatthe minimal number of assays to achieve this require-ments is 45 for qualitative methods and 55 for quanti-tative methods, if organized and applied as described.Of course, additional assays can be included especiallywhen recovery yield performances are needed. More-over, a continuous survey using quality test systems ascontrol charts remains as a necessary tool to preventany deviation of the method performance. This practi-cal methodology was established taking into accounta good compromise between statistical significanceof the results and practical aspects, with the objectiveto give a more “fit-for-purpose” protocol as possible.However, some important points remains to be de-fined and harmonized, such as an official position onthe decision to give a quantitative result regarding themethod CCα and CCβ. In conclusion, we think thata large diffusion and utilization of the detection ca-pability concept should be encouraged. Indeed, it canrepresent an elegant alternative to highly complex un-certainty calculations. The counterpart is the necessityof highly improved analytical methods, particularlyin term of specificity, for comfortable application.


References

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Documents

Validation of Analytical Methods Based on Mass Spectrometric