OMB Winter Mtg.-February 5-6, 2015

I N S I D E L A B O R A T O R Y M A N A G E M E N T

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N O V E M B E R / D E C E M B E R 2 0 1 4

Thompson also showed that the

robust

standard deviation

for PT data can usu-

ally be directly compared to the RSD

(R)

determined in a collaborative study (10).

Ellison et al. identified some condi-

tions that must be met in order for PT

data to be used to assess reproducibil-

ity: 1. collection of reproducibility data

is designed into the PT scheme before

the PT scheme is initiated; 2. the can-

didate method should be characterized

for precision and bias in a single-labo-

ratory type of evaluation prior to being

included in a PT validation project;

3. there must be a formal set of method

instructions; 4. some minimum number

of the laboratories participating in the

PT program must use the candidate

method under review; and 5. the PT

scheme must include a range of materi-

als covering the scope of the method.

Using Intermediate Reproducibility to

Determine Measurement Uncertainty

Estimation of measurement uncer-

tainty is an integral part of the modern

accreditation process. ISO 17025

states that measurement uncertainty

must be estimated and made avail-

able if requested by the customer. The

Codex Alimentarius

Commission has

guidelines that require laboratories

involved in the import/export of foods to

be accredited and report measurement

uncertainty (11). Historically, AOAC

has relied on the RSD

(R)

as an adequate

estimate of the measurement uncer-

tainty, and therefore AOAC does not

require method developers to calculate

or report measurement uncertainty as a

part of the method evaluation process.

However, measurement uncer-

tainty can be estimated using many

procedures which are described in the

literature (12–14). In principle, two

approaches may be used when calcu-

lating the measurement uncertainty of

a test result: the ‘Top-down’ or Type A

approach which is based upon a statis-

tical evaluation of the test results from

samples that have undergone the entire

analytical process; and the ‘Bottom-up’

or Type B approach in which all pos-

sible sources of variation of the result

are listed separately and the contribu-

tion of each source to the measurement

uncertainty is estimated. The Bottom-up

approach to estimate the uncertainty

of analytical results seems to be rather

impractical for methods of analysis

(15). In practice most laboratories have

used the Top-down or Type A approach,

estimating the measurement uncer-

tainty using the data available from

quality control, sample duplicates, and

method validation, especially intermedi-

ate reproducibility.

There are three kinds of data that

may be used to calculate the expanded

uncertainty (U) using the Top-down

approach:

1. Data from the original validation of

the method

2. Data obtained from collaborative

studies

Data obtained within a laboratory

using the method (16)

ISO Technical Standard 21748

“Guide to the Use of Repeatability,

Reproducibility and Trueness Estimates

in Measurements Uncertainty

Estimation” provides several procedures

for the estimation of the measurement

uncertainty using repeatability and true-

ness data. This would make it possible

to determine measurement uncertainty

using only in-house or single-laboratory

data. This may be an attractive option

in lieu of the difficulties in organizing

collaborative studies.

In a recent article entitled

The

Estimation and Use of Measurement

Uncertainty for a Drug Test Procedure

Validated According to USP <1225>,

Weitzel illustrated with examples the

procedures to determine measurement

uncertainty from single-laboratory vali-

dation (SLV) data (17). Weitzel used

accuracy, bias, precision, ruggedness,

and intermediate reproducibility data to

calculate the measurement uncertainty.

In a separate communication,

Weitzel also pointed out that that some

AOAC method manuscripts already

include a measurement uncertainty

calculation (18). For example, in AOAC

Official Method

2011.07,

a method for

the determination of vitamins A and E

by UPLC-UV or FLD, the authors use

a simplified approach described by

Barwick and Ellison (19) to calculate

measurement uncertainty using preci-

sion and trueness study data. AOAC

Official Method

2011.12,

a method for

the determination of vitamins D

and D

in food by UPLC/MS/MS, also includes an

estimate of the measurement uncertainty

calculated using a combination of preci-

sion and analytical competence data.

These method evaluations demon-

strate that calculating measurement

uncertainty from a variety of in-house

or SLV data is a relatively trivial task

if the evaluation studies are properly

planned to consider the necessary data

required to calculate measurement

uncertainty.

On-Site Verification

The main purpose for method vali-

dation is to ensure that an analytical

method designed and developed for a

specific purpose can actually achieve

an acceptable accuracy and precision.

The main purpose for investigating the

reproducibility of a method is to assess

he main purpose for method validation

is to ensure that an analytical method

designed and developed for a specific

purpose can actually achieve an acceptable

accuracy and precision.

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