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Document Number:

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Revision #: 02

Revision Date:

08/13/2019

Title: 

Ensuring the Quality of Test Results Page 1 of 17

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Sections in This Document

1. Purpose ....................................................................................................................................1

2. Scope .......................................................................................................................................1

3. Responsibility............................................................................................................................2

4. Background...............................................................................................................................2

5. References ...............................................................................................................................2

6. Procedure .................................................................................................................................2

6.1. Laboratory Quality Control Program ..............................................................................2

6.1.1. Quality Control Materials..................................................................................3

6.1.2. Internal Quality Control ....................................................................................3

6.1.3. External Quality Control Program ....................................................................6

6.1.4. Other Quality Control Monitoring Activities ......................................................8

6.1.5. Evaluation of Quality Control Data...................................................................8

6.1.6. Quality Control Charts......................................................................................9

6.1.7. Statistical Process Control .............................................................................11

6.1.8. Treatment of Outliers and Trends ..................................................................13

7. Glossary/ Definitions...............................................................................................................14

8. Records ..................................................................................................................................16

9. Supporting Documents ...........................................................................................................16

10. Document History ...................................................................................................................16

11. Change History.......................................................................................................................17

12. Attachments............................................................................................................................17

1. Purpose

This procedure describes the monitoring activities in a laboratory quality 

control (QC) program to ensure the quality of test results.

2. Scope

This procedure is applicable to Office of Regulatory Science (ORS) 

laboratories performing regulatory testing.
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3. Responsibility 

A. Laboratory Management

1. Establish a laboratory quality control program. 

2. Ensure that quality control is performed and review quality control 

data for acceptability and trends. 

B. Analysts 

1. Conduct quality control analyses in accordance with the laboratory 

quality control program.

C. Quality System Managers

1. Monitor quality control data for non-conformances and trends.

4. Background

None

5. References

A. Taylor, J. K. (1993). Handbook for SRM users. Gaithersburg, MD:

National Institute of Standards and Technology

B. ISO/IEC 17025:2017, General requirements for the competence of 

testing and calibration laboratories, Section 7.7

C. AOAC International Guidelines for Laboratories Performing 

Microbiological and Chemical Analysis of Food, Dietary Supplements, 

and Pharmaceuticals. An Aid to Interpretation of ISO/IEC 17025:2017; 

August 2018.

6. Procedure

6.1. Laboratory Quality Control Program

Laboratory quality control (QC) is an essential aspect of ensuring that data 

released is fit for the purpose determined by the quality objectives (i.e. 

accuracy and precision). The dual foundations of the laboratory quality control 

program are its internal quality control, composed of day-to-day and sampleset to sample-set monitoring of analytical performance, and its external QC, 

based on the laboratory’s performance in proficiency testing programs. 
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When properly executed, quality control samples monitor the various aspects 

of data quality on a routine basis. In instances where QC falls outside 

acceptable limits, the sample data produced may be questionable and, after 

investigation, a determination is made as to its validity. With professional 

experience and a common-sense approach quality control is the principal 

recourse available for ensuring that only defensible data is released. 

6.1.1. Quality Control Materials

A quality control material may include, but is not limited to, Certified Reference 

Materials (CRMs), Reference Materials (RMs), replicate analysis, 

positive/negative control samples, laboratory control samples (LCS), blanks, 

and matrix spikes.

In the absence of any CRM or RM, the laboratory shall do its best to obtain a 

material with some limited consensus of accuracy (e.g. by subjecting material 

to multiple methods or analyses in-house, sharing material with another 

laboratory to determine an average result, etc.)

The suitability of the quality control material used shall be justified by the 

laboratory.

For enumeration assays, a quantified quality control material shall be used. 

When testing for pathogens or select agents, a quality control material that 

contains a surrogate analyte may be used.

6.1.2. Internal Quality Control

QC is used to measure accuracy, precision, contamination, and matrix effects. 

QC material shall be used with each batch of samples analyzed. Generally, 

QCs are run per batch or set of samples at a frequency of 5% or one every 

twenty samples. If the laboratory is not able to meet this guideline, the batch 

must be defined and justified in the laboratory’s documents. The batch shall 

begin and end with QC material. 

The laboratory determines, where feasible, the accuracy and precision of all 

analyses performed.

Internal QC is run with each analytical batch to verify continuous system 

suitability specifications established are met, as well as demonstrates 

accuracy and precision or other parameters determined for the method type.

Method precision is periodically evaluated by the laboratory using the QC 

schemes described below.

6.1.2.1. Chemistry QC schemes 

A. QC schemes required for chemistry consist of:
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1. Meet system suitability requirements: system suitability is intended 

to determine whether the ‘system’ including instruments, analysts, 

etc. is capable of performing a particular process, test, or assay.

2. Blanks, either matrix or reagent, to determine and measure 

contamination and interferences - The results of blanks should be 

compared with the sample analyzed per analysis to determine 

whether the source of any analyte present is due to sample or 

laboratory contamination, interferences, the sample matrix, or the 

actual analyte in the samples. Blanks should be below the method 

detection limit where possible. Blank results are evaluated and 

corrected where possible. If blank results are consistently above the 

method detection level (MDL) established, the MDL should be reestablished. High blank results may also indicate contamination 

either from the solvent, laboratory equipment or laboratory 

environment. 

3. Matrix spikes and/or reagent spike- Matrix spikes measure the 

effects the sample matrix may have on the analytical method, 

usually the analyte recovery. Method accuracy is recorded and 

controlled based on the percent recovery of matrix spikes for 

quantitative analysis and the positive response of the analyte for 

qualitative analysis.

4. Duplicate samples or matrix spike duplicates - Duplicate sample or 

matrix spike duplicates measure precision of the analytical process. 

Duplicate analysis usually involves a replicate sample, sub-sampled 

in the laboratory, but for some methods it is in the form of a matrix 

spike duplicate. Method precision is recorded and controlled based 

on the relative percent difference (RPD) or the positive response for 

qualitative analysis. 

5. Quality control samples - Quality control samples (QCS) measure 

method performance. The matrix of the QCS should match the 

matrix of the samples being analyzed and should pass through the 

entire sample preparation process. The QCS, therefore, measures 

both the sample preparation process and the analytical process.

6. Standards - Calibration check standards referred to as initial 

calibration verification (ICV) and continuing calibration verification 

(CCV) are used to determine whether an analytical procedure is in 

control and stays within control. They are used to detect analytical 

method errors from procedural or operator errors or contamination 

from laboratory sources. 

7. Accuracy and precision control charts
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B. The chemistry laboratories shall define the acceptance criteria for each 

test method for the following items (when included in the test method): 

system suitability, calibration curves, calibration checks, ICV, CCV, 

QCS, blanks, matrix spikes, and duplicates.

C. The accuracy expressed as percent recovery should be 80% to 120% 

unless otherwise specified, i.e. by in-house statistical analysis.

D. The precision expressed as relative percent difference (RPD) should be 

< 20% unless otherwise specified, i.e. in-house statistical analysis. In 

procedures where multiple determinations or subs are analyzed, one 

can be chosen as the duplicate quality control sample. 

E. Analyze calibration check standards/samples. Each Initial Calibration 

Verification (ICV) and Continuing Calibration Verification (CCV) should 

have a percent recovery of 90% to 110% unless otherwise specified, i.e. 

by in-house statistical analysis.

F. The chemistry laboratories shall have a procedure or policy that 

provides guidance and/or criteria for the reprocessing and/or 

reintegrating of analytical data.

G. Drug Chemistry must meet USP system suitability requirements when 

performing a USP method. Requirements are stated in USP 

monographs.

6.1.2.2. Microbiology QC Schemes

A. QC schemes required for microbiology include running QC controls 

concurrently with each sample batch or set. They are:

1. Positive and negative culture controls - positive and negative 

controls give correct response, 

2. System controls

3. Collector controls,

4. Applicable kit controls (positive and negative),

5. Media quality - the culture controls additionally verify the 

acceptability of the media,

6. Un-inoculated media – un-inoculated media control reveals no 

visible growth, and

7. Accuracy and precision control charts. 
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B. Sample Duplicates or Spiked Samples– For quantitative methods, 

sample duplicates (for samples with expected values > 25 cfu/g) or 

spiked samples will be run for each batch of samples.

NOTE: The use of microbiological controls for sample analysis of 

virology samples and pharmaceutical analysis samples should follow 

virology SOPs, designated USP chapters and ORA-LAB.001 

(Microbiological Controls for Sample Analysis) or SOP-000288 

(Microbiological Controls for Medical Product Sample Analysis)

C. Media lot testing for suitability and acceptance for use must occur prior 

to sample testing (i.e. no concurrent studies).

6.1.2.3. QC Schemes for Other Testing

A. For other testing (e.g. radionuclides, microscopy, metrology, etc.) the 

required QC schemes are defined by the laboratory. The following 

performance parameters should be included, if applicable:

1. Meet system suitability requirements: System suitability is intended 

to determine whether the ‘system,’ including instruments, analysts, 

etc., is capable of performing a particular process or test.

2. Accuracy – a known or reference sample, 

3. Precision – a duplicate sample, 

4. Blank – a system control, reagent blank to check for environmental 

or laboratory contamination, and

5. If applicable, calibration check standards analyzed periodically in the 

analytical batch for quantitative analyses. 

6.1.3. External Quality Control Program

A. Participation in proficiency testing is an important means of quality 

control and assessing laboratory performance. Accrediting agencies 

require laboratories to participate in programs relevant to the 

laboratory’s scope of testing. 

B. Each laboratory maintains a documented proficiency testing (PT) plan 

that includes:

1. How the laboratory will cover its entire Biological and Chemical 

scopes annually.

Proficiency testing for all Chemical scope methods may not be 

necessary if the laboratory can provide evidence, showing similarity 
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of tests on the Chemical scope. The justification showing the 

similarities must be included on the PT plan.

2. The scheduled PT for 4 years.

C. When no PT or interlaboratory comparison is available, the laboratory 

shall develop and justify an alternative plan for monitoring data. 

D. The ORS laboratories participate in the AOAC - International Laboratory 

Proficiency Testing Program (LPTP), the FDA National Check Sample 

Program (NCSP) for foods, medical products, colors, metals, nutrition, 

sulfites, and filth, and other available proficiency tests identified by the 

laboratory or program. The Office of Regulatory Science (ORS) has the 

principal responsibility for managing the NCSP. 

E. Proficiency testing and interlaboratory comparisons are used as a tool 

to assist in the identification of laboratory problems that may exist and 

that have eluded the internal quality control program. They are not 

intended to represent individuals in the laboratory, unless this 

represents the normal mode of operation in which only one person is 

involved in the analysis. It is essential that proficiency testing samples 

are treated as routine samples to the extent possible. 

F. Analyses of proficiency samples should not be repeated, unless it is 

necessary to repeat the entire procedure or the data on those specific 

samples exceed the method’s linearity. 

G. Proficiency testing is quality control for method analytical data. It is not 

necessary to perform a check sample where normally done as a 

Program requirement. 

H. Samples should be run in duplicate only in those procedures where 

samples are normally analyzed in duplicate. 

I. Proficiency testing shall be rotated among qualified analysts

J. Management review all PT data and ensures proficiency and/or 

interlaboratory comparison data are submitted to the issuing authority 

by the date(s) defined when issued. Copies of all proficiency studies are 

retained in the laboratory. The final reports from the issuing authority 

are reviewed by the testing area management and the Quality System 

Manager upon receipt. All unacceptable results are investigated in 

accordance with ORA-LAB.4.9 Control of Nonconforming Work.

K. Most external PT providers issue acceptability limits and criteria; when 

issued, the laboratory shall use that criteria. If the PT provider does not 

issue acceptability criteria or the laboratory is performing proficiency 
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testing by alternative means, then they shall have procedures that 

define the acceptability of the results.

6.1.4. Other Quality Control Monitoring Activities

Other QC procedures that may be used include:

A. Replicate testing - Replicate testing may be performed on samples 

which are found to be violative. The original sample results are verified 

by using an alternative method or by rechecking results by the same 

method. A violative chemistry result may be verified by a second 

instrument, another method, a second analyst or repeated by the same 

analyst. A violative microbiology result by a rapid screening method is 

verified by a culture method.

B. Retesting of retained items - Retained samples can be re-introduced 

into the workload as regular samples in order to assess laboratory 

performance.

C. Correlation - Checking for correlation means evaluating the interrelated 

characteristics of the sample. By comparing results from different 

analyses on the same test item, one checks for reasonableness (i.e. 

Does the data make sense or correspond as anticipated?). Certain 

characteristics within the sample will maintain an analogous relationship 

to one another with regard to the type of test being performed. If one 

characteristic is dependent on or at all indicative of another 

characteristic, they should be compared for consistency. The 

designated reviewer should be able to anticipate and recognize an 

analogous relationship with different characteristics of the same sample. 

Any deviation such as the absence of expected primary characteristics 

or the sudden appearance of previously unobserved characteristics of 

the sample, signals the probability of error.

6.1.5. Evaluation of Quality Control Data

All worksheets are submitted to the supervisor or designee for review. The QC 

range of each quality control data is evaluated for acceptability. Data that fall 

inside established control limits are judged to be acceptable, while data lying 

outside of the control interval are considered suspect. Control limits 

established by the laboratory are not to be exceeded except as resolved under 

a recorded corrective action process. This planned action includes the 

checking of results for calculation or transcription errors, preparation or use of 

new standards, recalibration of instrument, reanalysis of all samples with new 

controls or reagents, use of alternate system, and repeating analysis.
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6.1.6. Quality Control Charts

The control chart is a graphical presentation of QC efficiency. If the procedure 

is in-control, the results will almost always be within established control limits. 

Accuracy and precision control charts are used to determine if the 

measurement system process is in control and whether the results generated 

by the measurement system are acceptable. The control chart provides the 

tool for distinguishing the pattern of indeterminate (random) variation from the 

determinate (assignable cause) variation. This technique displays the test 

data from a process or method in a form which graphically compares the 

variability of all test results with the average or expected variability of small 

groups of data, in effect, a graphical analysis of variance. 

The average or mean value is calculated and the spread (dispersion or range) 

is established. Common practice sets the warning limits at ± 2 standard 

deviations while control limits are set at ± 3 standard deviations on each side 

of the mean. Since the distribution of averages exhibits a normal form, the 

probability of results exceeding the control limits is readily calculated. 

Figure 1: Example of a Control Chart

 

Figure 2: A Control Chart showing a 3SD outlier

Further, the chart will disclose trends and shifts from assignable causes which 

can be corrected. A trend will show a tendency or movement in a particular 
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direction. If a series of consecutive data points move steadily either upward or 

downward, a trend is indicated. If a series of consecutive data points fall either 

above or below the center line, a shift is indicated. When a trend or shift is 

detected, it is annotated as such on the chart and reviewed to the extent 

possible to identify if a significant concern is indicated. If the review indicates a 

significant concern, follow the nonconforming work procedure.

Figure 3: Control Chart showing a trend

Figure 4: Control Chart showing a Shift
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It is emphasized that there is absolutely no substitute for sound judgment 

based on an appreciation of the analytical system, the technique, the quality 

control materials utilized, and the analytical interpretation of the data 

generated by the procedure.

Accuracy charts (other names are Mean Chart, Levy (Levey)-Jennings or 

Shewhart Control Chart) - The data from a series of analytical tests are plotted 

with the vertical scale in units such as percent (percent recovery), and the 

horizontal scale in units of batch number or time. The mean and standard 

deviation is calculated on the data. Upper and lower control limits are 

established at the mean ± 3X the calculated standard deviation. Upper and lower 

warning limits are established at the mean ± 2X the calculated standard 

deviation.

Precision charts (other names are Range Chart or R-chart) – The data from 

duplicates are plotted with the vertical scale in units such as percent (RPD), 

and the horizontal scale in units of batch number or time. The mean and 

standard deviation is calculated on the data. The upper control limit is 

established at the mean X 3.27 and the upper warning limit is established at 

the mean X 2.51. Precision control charts do not have a lower warning and 

control limit.

6.1.7. Statistical Process Control

A. Statistical limits are determined at the 99% confidence interval. The 

evaluation of control limits is made after no less than seven to ten points 

are accumulated from different conditions, i.e. separate runs/batches, 

different days, different analysts, etc.

B. Accuracy is expressed as percent recovery of spiked samples.

C. Percent recovery is calculated as follows for spikes in solvent or 

standard spikes:

% Recovery = 100 × K

X

where:

X = observed value

K = known value

D. Accuracy is calculated for spikes into natural matrices as follows:

Recovery = 100 × K

Xs − Xu

where:
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Xs = measured value for spiked sample

Xu = measured value for unspiked sample

K = known value of the spike in the sample

E. For accuracy, this interval is computed as:

Accuracy Interval = Mean Recovery ± 3 X S

where: S = Standard deviation for individual values

S = ( )

1

2

−

∑ −

N

Xi X

where:

Xi = value of individual measurement

X = arithmetic mean of the measurements

N = number of the measurements

F. For qualitative analysis, accuracy is expressed as positive (presence) or 

negative (absence).

G. Precision is expressed as relative standard deviation (RSD) or relative 

percent difference (RPD) of duplicate samples.

H. RSD is calculated from standard deviation and mean recovery, when 

the standard deviation is derived from multiple recovery results as 

follows:

RSD = CV = 100 × 

X

σ

where:

RSD = relative standard deviation

CV = coefficient of variation

σ = standard deviation

X = arithmetic mean of the measurements

I. RPD is calculated when only two sample results are available as 

follows:

where:
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| R1 - R2 | = Absolute difference between the determinations 

R = arithmetic mean of the two values

J. For precision based on RPD of duplicate samples this limit is computed 

as:

Upper Control Limit = 3.27 X RPD

where: RPD = mean relative percent difference

K. For qualitative analysis, precision is expressed as true and false 

positive rates; and true and false negative rates.

% false positive = total knownnegatives

falsepositives

#

# × 100 

% false negative = total knownpositives

falsenegatives

#

# × 100

6.1.8. Treatment of Outliers and Trends

A. An outlier is a datum that is different from the main data pattern, and/or 

is not representative of the data set. Outliers are extreme cases of one 

variable, or a combination of variables, which have a strong influence 

on the calculation or statistics. The principal safeguards against 

obtaining or using an outlier are vigilance during all operations and 

visual inspection of data before performing statistical analyses. Each 

suspected outlier is evaluated and rejected if found to be 

unrepresentative, or to have a high probability of being 

unrepresentative. Rejection for a reason is referred to as rejection for 

assignable cause.

B. A plot outside of the control limits may be an indication of an assignable 

cause. If a quality control result falls above or below the control limits (3 

SD) of the control chart, the value is investigated. The investigation is a 

planned action to correct the problem and to prevent the reporting of 

incorrect results. Sometimes the investigation will reveal a recording or 

computational mistake that can be revised to obtain the correct value. If 

the investigation reveals an assignable cause, i.e. deterioration of 

reagents, improperly prepared reagents, inadequate storage of 

reagents or standards, the analysis is repeated. When outliers are 

found, all analytical results for that analytical batch are inspected to 

ensure that erroneous results are not reported.

C. Quality control data outside of the control limits (3SD) rejected due to 

assignable cause remain in the permanent records of the laboratory, for 
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example, on QC charts. However, a datum so determined to be an 

outlier will be flagged as such and is excluded from the data set before 

statistical calculations are made. Control limits calculated from data sets 

containing outliers are not valid.

7. Glossary/ Definitions

A. Accuracy – Accuracy is the nearness of a measurement or the mean of 

a set of measurements to the true value. Accuracy is assessed in terms 

of percent recovery for quality control check samples and matrix spikes.

B. Analytical solution – An analytical solution is the sample in the form as 

introduced to an instrument. The analytical solution is the end result of 

the sample preparation, extraction, and digestion procedures.

C. Analytical spike – An analytical spike is a sample made by spiking an 

analytical solution after the sample preparation or digestion process. 

D. Batch - A batch is the basic unit of measure by which the number of 

quality control samples needed is determined. The analytical batch is 

those samples, sample extracts, or sample digestates that are analyzed 

together with the same method sequence, the same lots of reagents, 

and manipulations common to each sample within the same time period 

or in continuous sequential time periods. The extraction batch is those 

samples extracted or digested using the same techniques. Samples in 

each analytical or extraction batch should be of similar composition.

E. Calibration blank – A calibration blank is usually an organic or aqueous 

solution that is as free of analyte as possible and prepared with the 

same volume of chemical reagents used in the preparation of the 

calibration standards and diluted to the same volume with the same 

solvent (water or organic) used in the preparation of the calibration 

standard. The calibration blank is used to give the null reading for the 

calibration curve. For methods in which the calibration solutions receive 

the full sample preparation treatment, the calibration blank is identical 

to, and becomes referred to as, the method blank.

F. Continuing Calibration Verification (CCV) – A CCV is a standard 

solution used to verify freedom of excessive instrument drift. The CCV 

is a periodic check of the calibration.

G. Control charts – This is a chart consisting of an expected value 

(typically the mean) and an acceptable range of occurrences expressed 

as control limits. The values obtained from measurements versus the 

time sequence of entries are plotted to produce control charts.
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H. Duplicate samples – Duplicate samples are two separate samples taken 

from the same source (i.e. samples in separate containers and 

analyzed independently).

I. Initial Calibration Verification (ICV) – This is an independent standard 

solution used to verify the calibration standard level. An independent 

standard solution is defined as a standard solution composed of the 

analyte of interest from a separate (different) source, a different lot or a 

separately prepared set of two primary standards may be used.

J. Laboratory Control Sample (LCS) – A well characterized sample of 

known analytes and concentration, or a stable artifact, that is measured 

over time to monitor the stability of the measurement process.

K. Matrix spike sample – A matrix spike sample is prepared by adding a 

predetermined quantity of stock solution of representative analytes to an 

actual sample matrix (as opposed to an ideal matrix, e.g. reagent water, 

or site blanks, etc.) prior to sample extraction/digestion and analysis. 

The matrix spike is used to measure accuracy of the method in the 

sample matrix.

L. Matrix spike duplicate analysis - Equal and predetermined quantities of 

stock solutions of certain analytes are added to each of two aliquots of a 

sample prior to extraction or digestion and analysis. Matrix spike 

duplicates can be used to measure precision.

M. Method detection limit (MDL) – The MDL is the minimum concentration 

of a substance that can be measured and reported with 99% confidence 

that the analyte concentration is greater than zero. It is determined from 

the analysis of replicates of a sample containing the analyte at very low 

concentration.

N. Monitor – To monitor is to observe and record activity to measure 

compliance with a specific standard of performance; routine and 

ongoing collection of data about the indicator.

O. Precision – Precision is the agreement between a set of replicate 

measurements without assumption or knowledge of the true value. 

Analytical precision is assessed by means of laboratory duplicate or 

replicate or duplicate matrix spike analysis. The most commonly used 

estimates of precision are the relative standard deviation (RSD) or the 

coefficient of variation (CV).

P. Quality Assurance – Quality assurance is an integrated system of 

management activities involving planning, implementation, assessment, 

reporting, and quality improvement to ensure that a process, item, or 

service is the type and quality needed and expected by the client.
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8. Records

A. Control charts for accuracy and precision

B. Proficiency test results

C. Nonconforming work and corrective action records

9. Supporting Documents

A. ORA Laboratory Manual, Volume II, ORA-LAB.4.9 Control of 

Nonconforming Work

B. ORA Laboratory Manual, Volume II, ORA-LAB.4.11 Corrective Action

C. ORS.002 Standard Operating Procedures National Check Sample 

Program

D. ORA-LAB.001 Standard Operating Procedure (SOP): Microbiological 

Controls for Sample Analysis

E. SOP-000288 Microbiological Controls for Medical Product Sample 

Analysis

10. Document History

Revision

#

Status*

(D, I, R) Date Author Name and Title Approving Official Name and Title

1.2 R 12/06/06 LMEB LMEB

1.3 R 04/03/07 LMEB LMEB

1.4 R 11/15/07 LMEB LMEB

1.5 R 09/14/10 LMEB LMEB

1.6 R 01-22-13 LMEB LMEB

02 R 08/13/2019 LMEB LMEB

* - D: Draft, I: Initial, R: Revision
FOOD AND DRUG ADMINISTRATION

OFFICE OF REGULATORY AFFAIRS

ORA Laboratory Manual Volume II

Document Number:

ORA-LAB.5.9

Revision #: 02

Revision Date:

08/13/2019

Title: 

Ensuring the Quality of Test Results Page 17 of 17

For the most current and official copy, check QMiS.

11. Change History

Revision 

# Change

02

Revisions made as needed to align this procedure with the revised ISO/IEC 

17025:2017 and AOAC requirements. Revision to formatting and policy clarifications 

were also made. Images of control chart examples were included.

12. Attachments

None