Development and 
Submission of Near 
Infrared Analytical 
Procedures 
Guidance for Industry 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
 
August 2021 
Pharmaceutical Quality/CMC 
   
Development and 
Submission of Near 
Infrared Analytical 
Procedures 
Guidance for Industry 
 
 
 
Additional copies are available from: 
 
 
Office of Communications, Division of Drug Information 
Center for Drug Evaluation and Research 
Food and Drug Administration 
10001 New Hampshire Ave., Hillandale Bldg., 4th Floor  
Silver Spring, MD  20993-0002  
Phone: 855-543-3784 or 301-796-3400; Fax: 301-431-6353; Email: druginfo@fda.hhs.gov 
https://www.fda.gov/drugs/guidance-compliance-regulatory-information/guidances-drugs 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
 
August 2021 
Pharmaceutical Quality/CMC 
 
   Contains Nonbinding Recommendations 
TABLE OF CONTENTS 
 
I.  INTRODUCTION............................................................................................................. 1 
II.  BACKGROUND ............................................................................................................... 2 
III.  GENERAL MODES OF MEASUREMENT FOR NIR IMPLEMENTATION......... 4 
A.  Off-Line or At-Line........................................................................................................................ 4 
B.  On-Line or In-Line ........................................................................................................................ 5 
IV.  DEVELOPMENT OF NIR MODELS ............................................................................ 6 
A.  Construction of a Calibration Set ................................................................................................. 6 
B.  Presentation of Samples ................................................................................................................ 8 
C.  Development of Chemometric Models ......................................................................................... 8 
D.  Internal Validation of Identification Libraries ........................................................................... 9 
E.  Internal Validation of Quantitative Calibration Models ............................................................ 9 
F.  Development of Rate-of-Change Models ................................................................................... 10 
V.  EXTERNAL VALIDATION OF NIR ANALYTICAL PROCEDURES .................. 11 
A.  Qualitative Analytical Procedures .............................................................................................. 11 
B.  Quantitative Analytical Procedures ........................................................................................... 12 
C.  Rate-of-Change Procedures ........................................................................................................ 13 
VI.  IMPLEMENTING AND MAINTAINING NIR ANALYTICAL PROCEDURES .. 13 
VII.  INFORMATION SUBMITTED IN AN APPLICATION........................................... 14 
A.  Procedural Information............................................................................................................... 15 
B.  Development Information ........................................................................................................... 16 
C.  Validation Information ................................................................................................................ 17 
VIII.  LIFE CYCLE MANAGEMENT ................................................................................... 18 
A.  Major Changes ............................................................................................................................. 20 
B.  Moderate Changes ....................................................................................................................... 20 
C.  Minor Changes ............................................................................................................................. 21 
D.  Other Minimal Changes .............................................................................................................. 22 
GLOSSARY................................................................................................................................. 23 
  Contains Nonbinding Recommendations 
Development and Submission of Near  
Infrared Analytical Procedures 
Guidance for Industry1 
 
 
 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or Agency) on 
this topic.  It does not establish any rights for any person and is not binding on FDA or the public.  You 
can use an alternative approach if it satisfies the requirements of the applicable statutes and regulations.  
To discuss an alternative approach, contact the FDA office responsible for this guidance as listed on the 
title page.   
 
 
 
 
I.  INTRODUCTION  
 
This guidance provides recommendations to applicants to aid the development, validation, and 
use of near infrared (NIR)-based analytical procedures in evaluating the identity, strength, 
quality, purity, and potency of drug substances and drug products.  The recommendations apply 
to new drug applications (NDAs), abbreviated new drug applications (ANDAs), and 
supplemental NDAs and ANDAs for small molecule drugs.  The principles in this guidance also 
apply to drug substances and drug products covered in Type II drug master files.  FDA intends to 
issue recommendations specific to NIR methods used for biological products under biologics 
license applications in a future revision to this guidance.  This guidance provides 
recommendations to applicants for applying the concepts described in the guidance for industry 
PAT  A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality 
Assurance (September 2004) (PAT guidance) and the International Council for Harmonisation 
(ICH) guidance for industry Q2(R1) Validation of Analytical Procedures:  Text and Methodology 
(November 2005)2 to NIR analytical procedures that use chemometric models.3  This guidance 
also provides recommendations for submitting NIR documentation in applications.4   
 
1 This guidance has been prepared by the Office of Pharmaceutical Quality in the Center for Drug Evaluation and 
Research at the Food and Drug Administration. 
 
2 In November 2005, the ICH incorporated both the ICH guidance for industry Q2A Text on Validation of Analytical 
Procedures and the ICH guidance for industry Q2B Validation of Analytical Procedures:  Methodology into ICH 
Q2(R1).  Although the FDA guidance web page separately lists ICH Q2A and ICH Q2B, any references to ICH 
Q2(R1) in this guidance, unless otherwise indicated, refer to both ICH Q2A and ICH Q2B.  
 
3 We update guidances periodically.  For the most recent version of a guidance, check the FDA guidance web page 
at https://www.fda.gov/regulatory-information/search-fda-guidance-documents. 
 
4 This guidance contains technical and scientific recommendations that may be useful during development of NIR-
based analytical procedures for nonprescription drugs to which the application submission recommendations in this 
guidance do not apply. 
  1  Contains Nonbinding Recommendations 
 
Additionally, NIR implementation at commercial manufacturing sites must be in accordance 
with current good manufacturing practice (CGMP) regulations at 21 CFR parts 210 and 211 for 
drug products5 and should be in accordance with the ICH guidance for industry Q7 Good 
Manufacturing Practice Guidance for Active Pharmaceutical Ingredients (September 2016) 
recommendations for drug substances.  
 
This guidance pertains only to the development and validation of NIR analytical procedures and 
does not provide recommendations concerning the setup, qualification, maintenance, or 
calibration of NIR instruments.  Although this guidance specifically addresses NIR spectroscopy, 
this guidances concepts of validation can be applied to other process analytical technologies 
(PATs), including, for example, Raman, focused beam reflection measurement, particle imaging, 
and X-ray. 
 
The contents of this document do not have the force and effect of law and are not meant to bind 
the public in any way, unless specifically incorporated into a contract.  This document is 
intended only to provide clarity to the public regarding existing requirements under the law.  
FDA guidance documents, including this guidance, should be viewed only as recommendations, 
unless specific regulatory or statutory requirements are cited.  The use of the word should in 
Agency guidances means that something is suggested or recommended, but not required.  
 
 
II.  BACKGROUND 
 
NIR analytical procedures are increasingly being used in the pharmaceutical industry (1) for 
identification testing and assay measurements performed on pharmaceutical starting materials, 
intermediates, and finished products, and (2) for monitoring and controlling manufacturing 
processes.  Therefore, to ensure the quality of pharmaceuticals, it is important for applicants who 
use these procedures to develop robust NIR analytical procedures and to understand both the 
factors that can affect the performance and suitability of these procedures and the approaches 
that can be used to validate them. 
 
The PAT guidance and ICH Q2(R1) provide information about analytical procedures, such as 
those used for NIR.  The PAT guidance explains the different modes of measurement that can be 
used by a process analyzer during the manufacturing process to measure a chemical or physical 
property of interest based on vibrational spectroscopy (e.g., NIR or Raman).  ICH Q2(R1) 
provides:  
 
  A discussion of the characteristics that should be considered during the validation of 
analytical procedures 
 
 
5 Although NIR procedures could be used in positron emission tomography drug production, it is not typical.  
Therefore, references to 21 CFR part 212, Current Good Manufacturing Practice for PET Drugs, are not included in 
this guidance. 
  2  Contains Nonbinding Recommendations 
  [G]uidance and recommendations on how to consider the various validation 
characteristics for each analytical procedure  
 
  An indication of the data that should be presented in a new drug application6   
 
Although many of the concepts described in ICH Q2(R1) can apply to a wide variety of 
analytical methodologies, ICH Q2(R1) does not address some characteristics unique to NIR 
analytical procedures.7  NIR analytical procedures typically combine the following features:   
 
  Instrumentation elements (e.g., an analyzer consisting of an NIR spectrophotometer, a 
reflectance or transmission probe, or spectral analysis software) 
 
  Acquisition parameters 
 
  A sample presentation (interface) 
 
  A sampling scheme for process applications 
 
  The composition of spectral datasets 
 
  Spectral pretreatments 
 
  Wavelength ranges 
 
  A chemometric model 
 
This guidance addresses the NIR-specific features listed above that are not addressed in ICH 
Q2(R1).  
 
 
 
6 See ICH Q2B, p. 1. 
 
7 At the time of this guidances publication, the ICH Q2(R2)/Q14 expert working group planned to develop a new 
ICH quality guideline, ICH Q14, on analytical procedure development, and revise the ICH Q2(R1) guideline on 
validation of analytical procedures, with a view to potentially combine both documents into one, for simplification 
and clarity.  See https://www.ich.org/page/quality-guidelines.  ICH is a consensus-driven process that involves 
technical experts from regulatory authorities and industry parties in detailed technical and science-based 
harmonization work that results in the development of ICH guidelines.  The commitment to consistent adoption of 
these consensus-based guidelines by regulators around the globe is critical to realizing the benefits of safe, effective, 
and high-quality drug products for patients as well as for industry.  As a Founding Regulatory Member of ICH, FDA 
plays a major role in the development of each of the ICH guidelines, which FDA then adopts and issues as guidance 
to industry. 
  3  Contains Nonbinding Recommendations 
III.  GENERAL MODES OF MEASUREMENT FOR NIR IMPLEMENTATION 
 
For NIR-based process analyzers, the following modes of measurement are commonly used for 
process understanding, monitoring, and control:8 
 
  Off-line, where the sample is analyzed away from the process stream or reactor (e.g., the 
identity testing of raw material samples by NIR in the quality control lab) 
 
  At-line, where the sample is removed, isolated from, and analyzed in close proximity to 
the process stream or reactor (e.g., a measurement of a tablet assay or content uniformity 
by NIR where the NIR analyzer is located next to the tablet press and fed manually or 
automatically) 
 
  On-line, where the sample is diverted to a side stream off the main manufacturing process 
and may be returned to the process stream or reactor (e.g., a measurement of cell density 
in an anaerobic fermentation process using a flow-through cell) 
 
  In-line, where the sample is not removed from the process stream or reactor (e.g., an in-
line monitoring of blend uniformity by NIR where the NIR analyzer is interfaced with the 
blender through a window and takes continuous spectra measurements) 
 
The following subsections describe some specific features that applicants should consider during 
development when selecting the appropriate mode of measurement for NIR implementation. 
 
A.  Off-Line or At-Line 
 
Generally, off-the-shelf NIR interfaces are used for off-line or at-line measurements.  However, 
customized sample holders can be used when indicated for a specific application.  Applicants 
should consider the following factors while developing off-line or at-line measurements: 
 
  Measurement.  NIR instruments typically allow for transmission measurements and for 
reflectance measurements, but selection of the appropriate measurement type should be 
based on both the optical properties of the sample and the intended application.  For 
example, although a transmission measurement probes the bulk of the sample, a 
transmission measurements useful spectral range is often more limited than a reflectance 
measurements useful range, and a transmission measurements spectra may contain 
more noise than a reflectance measurements spectra.  Similarly, although a reflectance 
measurement includes a surface signal component, that reflectance measurement 
typically produces less noise and a wider useful spectral range than a transmission 
measurement.  Therefore, applicants should carefully choose the NIR instrument that 
balances these issues. 
 
 
8 When used for monitoring or control of the drug product during commercial manufacturing, each of these sample 
testing modes must satisfy existing CGMP requirements (see, for example, 21 CFR 211.110 and 21 CFR 211.165). 
  4  Contains Nonbinding Recommendations 
  Spectral Acquisition Time.  A spectral acquisition time that simultaneously optimizes 
both the signal-to-noise ratio and the measurement duration for a given application 
should be selected. 
 
  Sampling.9  A sampling plan should be developed that ensures that the samples 
(1) represent the processed materials, (2) are based on rational criteria, and (3) accurately 
portray the material being sampled.  Additionally, the sampling plan should involve time- 
and location-based sampling.  
 
  Sample Preparation.  Generally, there is no need to prepare (or change) the physical 
characteristics of the sample (e.g., through grinding) to make the sample more suitable 
for NIR analysis.  However, if samples are prepared before spectral acquisition, the same 
sample preparation should be used both for calibrating and validating the sample and for 
analyzing the production batches. 
 
B.  On-Line or In-Line 
 
Typically, on-line or in-line measurements use a custom-built interface to provide an acceptable 
signal-to-noise ratio and spectral acquisition time.  Therefore, the following factors during the 
development of on-line or in-line measurements should be considered: 
 
  Interface.  First, the appropriate measurement interface depends on the application.  For 
example, to monitor blending in a rotary blender or mixer, a sapphire window is often 
built into the blender or mixer wall or lid with an analyzer bolted outside the mixer to 
ensure that the analyzer will not be dislodged by the rotary motion of the equipment.  For 
other types of measurements (e.g., for measuring the solvents content during drying), a 
probe connected to the analyzer by a fiber optic cable can be used.  (However, an NIR 
signal transmitted through a fiber optic cable should be adequate for the intended 
measurement.)  Second, the location of the interface (e.g., the interfaces position, 
distance, and depth) should ensure that spectra that represent the properties of the entire 
processed materials are obtained.  Finally, NIR interface consistency and cleanliness 
should be maintained throughout the entire data acquisition process to ensure data 
integrity.   
 
  Spectral Acquisition.  The interface should be designed to minimize the interference of 
spectral acquisition.  To accurately monitor an operation unit, the interface should be 
exposed to the material being processed throughout the entire spectral acquisition time.  
For rotary blenders, spectral acquisition time and frequency should be adjusted so that 
sample spectra are obtained only while the interface is exposed to the material being 
blended or mixed.  (For example, triggers based on chronometry or gravity should be 
used to synchronize the start or stop of spectral acquisition.)  For liquid samples, the 
effect of bubble formation should be evaluated. 
 
 
9 When used for monitoring or control of the drug product during commercial manufacturing, each of these 
sampling approaches must satisfy existing CGMP requirements at 21 CFR 211.110, 21 CFR 211.160, and  
21 CFR 211.165. 
  5  Contains Nonbinding Recommendations 
During development of the interface, it should be confirmed that the material does not 
stick or bind to the interface window.  Additionally, applicants should understand and 
characterize the material properties within the unit operation to ensure that the material 
analyzed at interface is representative of the material as a whole. 
 
  Data Collection.  If wireless communication is used to transmit the NIR signal to the 
controller, hardware and software that ensures the robustness and integrity of the data 
transmission should be installed. 
 
  Sampling.  The assessment of an effective sample size is important for some applications 
(e.g., for a blend uniformity analysis).  Applicants can determine if a sample size is 
effective for NIR measurements by evaluating the diameter of the NIR beam, the beams 
depth of penetration, and the density of the sample.  Generally, an effective sample size is 
small because the NIR beam would then illuminate a small sample volume.  Specifically, 
for monitoring blend homogeneity, the effective sample size should be comparable to a 
unit dose of the finished drug product. 
 
  Reference Measurement.  Ideally, spectral acquisition and reference analysis should be 
performed on the same samples that will be used to develop the calibration model.  It 
may be difficult, however, to use the same samples, particularly for in-line 
measurements.  Therefore, when identical samples cannot be used, applicants should 
justify the pairing of the spectra with the reference results. 
 
 
IV.  DEVELOPMENT OF NIR MODELS 
 
An NIR model is an integral part of an NIR procedure.  NIR models can be categorized as either 
quantitative (e.g., for assay) or qualitative (e.g., for identification or for limit testing for the 
absence of polymorphs).  Typically, the development of an NIR model is based on chemometrics 
and should involve the following steps. 
 
A.  Construction of a Calibration Set 
 
An essential part of developing an NIR model is the construction of a calibration set.  The 
spectra that comprise the calibration set are acquired from the calibration samples.  To create a 
robust model, applicants should build a calibration set with samples that:  (1) include an 
appropriate concentration range for the component to be analyzed; (2) address potential sources 
of variability (e.g., a variation in the processes, the analyzer, the physical characteristics of the 
materials, the water content, or the temperature); and (3) cover the expected variations in process 
parameters (e.g., in-design space parameters) that have a potential to influence the spectral 
response. 
 
Calibration samples should mimic as closely as possible the samples that are expected to be 
representative of the commercial process; calibration samples from batches that are either 
produced at the intended commercial scale or representative of the commercial process are ideal 
because they generally exhibit the expected process variability.  If the samples obtained from the 
  6  Contains Nonbinding Recommendations 
process do not provide a sufficient range of variability, additional samples can be prepared under 
laboratory conditions.  When preparing calibration samples, applicants should consider the 
following factors, including, but not limited to: 
 
  Variations from sample preparations (e.g., lack of batch homogeneity) can affect the 
calibration results. 
 
  The physical attributes of the prepared samples should ensure a spectral response similar 
to the response of materials manufactured with the use of a commercial process.  For 
example, tablets prepared in a laboratory should have physical characteristics equivalent 
to tablets prepared with a commercial process. 
 
  Spectral preprocessing should adequately minimize the influence of the difference in 
physical attributes for the laboratory-prepared and production samples on the measured 
spectra. 
 
  To capture the expected material variabilities calibration samples of qualified materials 
from multiple vendors or from different manufacturing lots should be used. 
 
  For quantitative NIR models, concentrations of the analyte of interest should span a range 
that is wider than the acceptable specification limit to ensure that the model can 
characterize nonconforming materials. 
 
  When the NIR procedure is intended to simultaneously characterize multiple analytes, the 
design of the experiment methodology can be used to select the optimum combination of 
the concentrations of analytes in the calibration samples. 
 
  Any potential variability from the sample presentation should be built into the calibration 
set. 
 
  Environmental variability can be addressed either by measuring spectra under different 
environmental conditions or by maintaining constant environmental conditions during 
sample acquisition and spectral measurement. 
 
  Inclusion of spectra from multiple instruments of the same type can facilitate future 
extensions of the calibration to a new instrument or to a new site. 
 
  Instrument characteristics may introduce a significant source of variability.  This 
variability can be lowered by activating standardization options, which are often available 
in the software associated with NIR instruments.  The design of calibration sets to 
support this standardization can facilitate future extension of the calibration model to new 
instruments or to new sites. 
 
  7  Contains Nonbinding Recommendations 
B.  Presentation of Samples 
 
For both qualitative and quantitative analyses, the presentation of samples to the NIR instrument 
can influence the instruments spectral quality, which would therefore affect the performance of 
the NIR analytical procedure.  A typical NIR analyzer offers multiple options for the 
presentation of samples (e.g., diverse reflectance and transmission measurements, single and 
multiple sample holders, different probe window sizes, and a variety of individual fibers in a 
fiber cable); applicants should decide which option best fits the requirements of the NIR 
procedure to their processes and properties of interest.  In addition, applicants should: 
 
  Use an equivalent interface and sample presentation to obtain calibration and routine 
production sample spectra   
 
  Ensure that, if sample holders are used that provide for multiple positions (e.g., tablet 
wheels or trays), the location of their samples in those holders does not affect the 
obtained spectra 
 
  Ensure that, if the obtained spectra depend on which side of a tablet is presented to the 
spectrometer, the same side of the tablet is presented to the spectrometer for each scan 
 
  Include replicate scans of the same materials if hand-held probes are used 
 
  Perform a replicate scanning of the samples that are placed in vials if those samples are 
scanned through the vial to reduce the interference of vial variability 
 
C.  Development of Chemometric Models 
 
For NIR analytical procedures, chemometric models are usually built upon predictor variables 
that are either wavelength-dependent spectral intensities or the linear combinations of those 
wavelength-dependent spectral intensities.  Chemometric models are usually developed using 
common chemometric algorithms such as principal component analysis, partial least square, and 
principal component regression, which are all typically included with commercially available 
chemometric software. 
 
Applicants should consider the following factors when developing chemometric models: 
 
  The wavelength range of the spectral data used to construct the chemometric model does 
not need to include the full range of the analyzer.  However, restricting the calibration 
wavelength range to cover only narrow regions around an analyte peak can compromise 
the models robustness; therefore, model performance should be tested rigorously using 
both narrow and full ranges. 
 
  Usually, raw NIR spectra should be pretreated to reduce their variability and to enhance 
spectral effects related to chemical composition.  For example, impact of particle size or 
compression force on the intensity of scattered light can be significantly reduced through 
  8  Contains Nonbinding Recommendations 
spectral pretreatment.  However, inappropriate pretreatments can introduce artifacts or 
reduce the signal-to-noise ratio. 
 
  The appropriate number of factors or latent variables should be chosen to avoid 
underfitting or overfitting the model.  Most chemometric software packages include 
statistical tools to help determine the optimal number of factors.  Establishing the number 
of factors based on the number of components in the analyte sample is not considered to 
be a suitable substitute for the use of these tools.  Overfitting the data with too many 
fitting parameters can lower the robustness of the model and lead to poor predictive 
performance of the calibration model. 
 
  Potential outliers in the calibration set (e.g., samples with high leverages or high residuals 
or atypical NIR spectra or reference results), which can often be identified either by 
visual inspection of the data or during internal validation, should be investigated.  Most 
software programs contain outlier and model diagnostics during prediction.  Data 
resulting from spectral acquisition or reference analysis errors should be considered 
confirmed outliers and therefore rejected.  Any inclusion or exclusion of outliers should 
be justified. 
 
  To increase the accuracy of the NIR measurement of the active ingredient content of a 
tablet, the calibration model should be developed using reference assay values from 
individual tablets based on the matched weight and concentration for each tablet.  
Conversely, during a routine analysis of the model, the NIR concentration result from 
each tablet should be corrected for the weight of that tablet to obtain the assay value.  If 
weight correction is not feasible, an alternative approach should be justified. 
 
  The preprocessing regimen, the spectral range, and the number of latent variables should 
be optimized to improve the models performance and robustness through internal 
validation. 
 
D.  Internal Validation of Identification Libraries 
 
Identification libraries based on the chemometric models should be internally validated (1) to 
verify the proper assignment of spectra, (2) to ensure that there are no conflicts among library 
products, and (3) to confirm that the library threshold is appropriately set.  This internal 
validation should be performed by treating each spectrum in the library as an unknown and by 
determining whether each spectrum is correctly and uniquely identified by the library. 
 
E.  Internal Validation of Quantitative Calibration Models 
 
Two common approaches for internally validating quantitative calibration models include 
(1) cross-validation using the calibration set, and (2) validation using an internal validation set. 
 
(1) Cross-Validation Using the Calibration Set.  The cross-validation process involves the 
following steps:   
 
  9  Contains Nonbinding Recommendations 
(a) Removing one or more spectra from the calibration set  
(b) Creating a model based on the remaining spectra  
(c) Applying that model to the spectra that have been removed 
(d) Calculating the differences between the known reference values and the values 
predicted by the model (i.e., the residuals)   
 
These steps should be sequentially applied to the entire calibration set, and the resulting 
residuals can be used to calculate the root mean square error of cross-validation. 
 
(2) Validation Using an Internal Validation Set.  Validation using an internal validation 
set involves applying one or more of the models that were obtained from the calibration 
set to the internal validation set.  The resulting residuals can be used to calculate the 
standard error of prediction (SEP). 
 
The root mean square error of cross-validation or SEP can be used as one criterion for model 
optimization.  The optimum model for the analytical procedure usually exhibits an acceptable 
error but minimizes the sensitivity of the error to small variations in either sample characteristics 
or model parameters. 
 
At the end of the optimization process, the standard error of calibration (SEC) should ensure that 
the measurement is performed with the accuracy necessary for the intended purpose of the 
analytical procedure, such that the accuracy of the NIR method is comparable to that of the 
reference method.  
 
F.  Development of Rate-of-Change Models  
 
Typically, rate-of-change models are used to monitor and detect the endpoint of dynamic 
processes (e.g., blending or mixing).10  If these models are used, the endpoint usually will 
coincide with the measured rate of change reaching a predefined threshold that indicates that the 
process is complete.  These models can be based on a change in the (1) concentration of the 
active ingredient or other component, or (2) spectral magnitude related to the component of 
interest. 
 
Applicants should consider the following when developing rate-of-change models: 
 
  The endpoint criteria should provide assurance that the detected endpoint is not a 
transient phenomenon.  For example, applicants can specify that the rate of change 
remains below the endpoint value for a predetermined time or number of blender 
revolutions. 
 
 
10 When used for monitoring or control of the drug product during commercial manufacturing, the implementation 
of the processing endpoint must satisfy the CGMP requirements (see, for example, 21 CFR 211.110) and be 
validated (see 21 CFR 211.100 and 21 CFR 211.160). 
  10  Contains Nonbinding Recommendations 
  For endpoint criteria that are based on statistical considerations (e.g., the F-value between 
consecutive blocks of spectra), any underlying assumptions (e.g., data normality) should 
be met. 
 
  For blends in which a component of interest is present in a low concentration, risk exists 
that the endpoint represents a uniformity of the major components.  For these blends, the 
endpoint criteria should indicate a uniform distribution of the low-level component of 
interest. 
 
  If a rate-of-change model for blend uniformity (e.g., blending or mixing) is based on a 
quantitative model for either the active ingredient or another component, the rate-of-
change model and the quantitative model should separately be developed and validated to 
ensure an accurate and reliable endpoint detection. 
 
 
V.  EXTERNAL VALIDATION OF NIR ANALYTICAL PROCEDURES 
 
Applicants should perform validation after their chemometric models are developed.  This 
validation is sometimes referred to as external validation.  Internal validation of the chemometric 
model is not considered a substitute for external validation. 
 
The samples used by applicants for external validation should:  (1) span a suitable range of 
operating conditions (including the range expected during commercial production); (2) be 
independent from the calibration and internal validation samples used during the development of 
the NIR models; (3) be of a sufficiently large number to provide statistically meaningful results; 
and (4) either be produced at the intended commercial scale or represent the commercial process.  
Also, results should be acquired either (1) from the NIR and reference analytical procedures 
using the same sample when feasible, or (2) by using representative samples and providing a 
justification for those samples.   
 
Qualitative analytical, quantitative analytical, and rate-of-change procedures should be validated 
as follows. 
 
A.  Qualitative Analytical Procedures 
 
Qualitative NIR procedures based on identification libraries should be validated for specificity 
and robustness.  Specificity normally involves demonstrating that positive and negative controls 
yield the correct pass or fail results.  Positive controls usually comprise samples of known 
identity, and acceptance of the samples quality should be confirmed by independent reference 
testing.  Placebos or other samples that show spectral similarities to the tested material can be 
used as negative controls.   
 
  11  Contains Nonbinding Recommendations 
B.  Quantitative Analytical Procedures 
 
Applicants should validate quantitative procedures for accuracy, precision, specificity, linearity, 
range, detection and quantitation limits, and robustness.11 
 
  Accuracy.  The accuracy of the NIR procedure should be determined by comparing the 
results from the NIR analytical procedure using external validation samples with the 
results from a suitable reference analytical procedure.   
 
The SEP can be calculated as a measure of accuracy relative to the external validation set.  
Significant differences between the SEC and SEP, as well as significant biases, could 
indicate either differences between the calibration samples and the validation samples or 
an inadequately optimized calibration model, both of which should be appropriately 
investigated and rectified. 
 
The independent validation set used to determine the accuracy of the NIR procedure 
should span a suitable range of sample concentrations. 
 
  Precision.  The standard deviation of repeat measurements (i.e., repeatability) can be a 
useful measure of precision.  Samples for repeatability measurements should cover the 
expected range of sample variation.  Multiple measurements should be made of each 
sample.  If possible, the sample should be repositioned in the sample holder or on the 
sample presentation module after each measurement.  Intermediate precision, which 
involves different analysts or different days, should also be determined. 
 
  Specificity.  Specificity is conventionally considered to be verified if the main features of 
the loadings plots correspond to the loadings plots of the NIR spectrum of the analyte of 
interest.  The NIR spectrum should be pretreated in the same way as spectra used in the 
model.  Another element of specificity is the ability of the method to reject outliers (e.g., 
samples with high leverages or high residuals). 
 
  Linearity.  To evaluate linearity, analytical results for the external validation samples 
obtained using the NIR analytical procedure should be compared to the results obtained 
using the reference analytical procedure.  If the resulting values are plotted over a 
suitable range, a correlation coefficient close to 1 and, where applicable, a y-intercept 
close to 0 indicate an acceptable linearity. 
 
  Range.  As recommended in ICH Q2(R1), the appropriate range for validation studies 
should depend on the attribute being evaluated. 
 
  Detection and Quantitation Limits.  If the NIR analytical procedure will be used near 
the limit of its detection capability, detection limit and quantitation limit should be 
determined by, for example, analyzing minor components or detecting the endpoint for 
drying. 
 
11 See ICH Q2(R1). 
  12  Contains Nonbinding Recommendations 
 
  Robustness.  Robustness can be addressed during the calibration models development 
by including anticipated sources of variability (e.g., raw materials and operating and 
environmental conditions).  Robustness can be confirmed during validation by using 
validation samples that include sources of variability that may occur during commercial 
production. 
 
C.  Rate-of-Change Procedures 
 
To validate rate-of-change procedures (e.g., blending or mixing), manufacturers should 
demonstrate both the adequacy of the NIR endpoint criteria and the specificity of the NIR 
procedure for components of interest.  First, the adequacy of the endpoint criteria should be 
confirmed with an appropriate reference methodology (e.g., a traditional blend uniformity 
analysis).  During the validation of the rate-of-change procedure (e.g., blending or mixing), the 
procedure should be stopped as soon as the endpoint criteria are achieved; otherwise, misleading 
results may occur.  Second, specificity can be demonstrated by showing that the wavelength 
region used for the NIR procedure included major bands of the components of interest. 
 
 
VI.  IMPLEMENTING AND MAINTAINING NIR ANALYTICAL PROCEDURES 
 
Applicants must ensure that NIR analytical procedures are appropriately followed, maintained, 
and updated as needed throughout the drug products life cycle in accordance with CGMP 
requirements.12  The CGMP regulations for finished pharmaceuticals require that drug product 
manufacturers establish procedures to: 
 
  Appropriately maintain hardware (by, for example, conducting reliability testing to 
estimate the mean time to failure and the mean time between failure, performing 
suitability testing, and creating and following a maintenance and repair schedule)13   
 
  Monitor calibration model predictions and model diagnostics to detect changes, including 
trends and shifts;14 continual monitoring is recommended to ensure rapid detection and 
timely intervention to prevent product failure 
 
  Recognize circumstances, such as the following, that may warrant revision of the 
calibration model:15 
 
12 When used for monitoring or control of the drug product during commercial manufacturing, CGMP requirements 
at, for example, 21 CFR 211.110, 21 CFR 211.68, and 21 CFR 211.160 apply. 
 
13 21 CFR 211.68 
 
14 21 CFR 211.100(b); 21 CFR 211.110; 21 CFR 211.160(b)(4) 
 
15 21 CFR 211.68; 21 CFR 211.160(b)(4) 
  13  Contains Nonbinding Recommendations 
 
  Significant changes of materials, equipment, and/or manufacturing processes 
  Unusual or erroneous NIR results 
  Failure to meet routine method verification criteria 
  Transfer of the NIR analytical procedure 
  Major repair of the analyzer 
 
  Revise and revalidate the calibration model16 
 
The extent of the models maintenance (e.g., periodic verification) should be dependent on the 
effect of the model on the drug products quality.  Retention of development and maintenance of 
NIR analytical procedures and calibration model must be consistent with record retention 
requirements in the regulations.17  The calibration model should be retained in a knowledge 
management system for as long as the information is useful in evaluating the models 
performance and history of use that is relevant to any product released using this model.18 
 
Applicants should consider developing contingency procedures to follow if their NIR equipment 
fails before or in the middle of measurements or ongoing operations.  This could reduce the need 
to reject drug material and limit production delays.  These contingency procedures are 
particularly important for the on-line or in-line implementation of an NIR analytical procedure 
when the measurement is to be used to satisfy a CGMP requirement. 
 
 
VII.  INFORMATION SUBMITTED IN AN APPLICATION 
 
An applicant must provide information about every NIR analytical procedure that is included in 
its commercial control strategy,19 as well as information about the development and validation of 
these procedures (as detailed in sections VII.A. through VII.C.).20  Additionally, applicants 
should provide high-level summaries of their plans for the life cycle maintenance of models 
associated with NIR analytical procedures.  Detailed life cycle maintenance plans, as well as 
records of any changes in software versions over the life cycle, must be maintained at the 
manufacturing site as part of the manufacturing sites quality systems risk and knowledge 
management programs and available for inspection.21  Information about the NIR procedures 
 
16 21 CFR 211.68; 21 CFR 211.180(e) 
 
17 21 CFR 211.68; 21 CFR 211.180.  NIR model information should be retained for active pharmaceutical 
ingredients consistent with ICH Q7 and as described here. 
 
18 See the ICH guidance for industry Q10 Pharmaceutical Quality System (April 2009) about knowledge 
management. 
 
19 21 CFR 314.50(d) 
 
20 See ICH Q2(R1). 
 
21 21 CFR 211.180 
  14  Contains Nonbinding Recommendations 
used only for developmental or informational purposes does not need to be included in the 
application. 
 
If NIR and another equivalent method are both submitted, the applicant should indicate the role 
of each method to provide clarity for decisions concerning in-process/intermediate material and 
finished batch disposition.  Specifically, the applicant should indicate which method will be used 
for the routine release and, if applicable, which will be considered the alternate method per 21 
CFR 314.50(d)(1)(i) (for drug substances) and 21 CFR 314.50(d)(1)(ii)(a) (for drug products). 
 
A.  Procedural Information 
 
For NIR analytical procedures, applicants should provide at least the following information: 
 
  The purpose of the procedure, including: 
 
  The location within the process (i.e., which unit operation) 
 
  The mode of measurement (i.e., in-line, on-line, at-line, or off-line) 
 
  The property or attribute of interest to be measured 
 
  The intended use (e.g., for in-process or end-product release testing) 
 
  The analyzer and software specifications, such as: 
 
  The instrument manufacturer, model, and type (e.g., dispersive or Fourier Transform) 
 
  Whether custom-made software will be used for spectral acquisition, model 
development, and routine prediction  
 
  Data acquisition, including the measurement principles (e.g., the transmission or 
reflectance mode), the acquisition times, the number of spectra averaged, the number 
of scans, the number of replicates, and the wavelength ranges, among others 
 
  The sampling accessories 
 
  The samples orientation (e.g., random, with indentation up or down) if a specialized 
sample holder is used 
 
  The steps for the samples analysis, including, when relevant: 
 
  The reference (background) spectrum collection 
 
  The sample presentation 
 
  The sample preparation or conditioning 
  15  Contains Nonbinding Recommendations 
 
  A system suitability description 
 
  The tablet weight measurement for assay and content uniformity 
 
For in-line or on-line methods, applicants should also provide information, as applicable, 
regarding: 
 
  How the NIR instrument is interfaced to the process 
 
  The system or procedure followed to ensure that the interface remains clean and free of 
adherent material 
 
  For on-line blending or mixing, the system used to trigger spectral acquisition to ensure 
that the interface window remains covered by the blend throughout the acquisition 
 
  The endpoint criteria of a process, such as blending or mixing 
 
  Any contingency plan that addresses both a potential failure of the NIR analyzer and a 
potential failure of an in-process NIR procedure to detect the pre-established endpoint 
 
B.  Development Information 
 
For the development of NIR analytical procedures, applicants should provide at least the 
following information: 
 
  For calibration and internal validation sets: 
 
  The associated batches, including the number of batches, the batch size, and the 
number of samples from each batch that were used to create the calibration set 
 
  If an internal validation set is used, the method used for distinguishing the calibration 
set from the internal validation spectra 
 
  For quantitative procedures, the distribution of the reference values in the calibration 
and internal validation sets (which can also be shown in the form of predicted versus 
reference results or in residual plots) 
 
  If some samples are prepared in small batches to represent a known concentration of 
the analyte, any differences in appearance (such as in shape, size, dimension, or 
indentation) between the small batch samples and the production samples 
 
  Any sources of variation included in the calibration set and how these variations 
relate to potential variations in the raw materials and process parameters expected 
during commercial production 
 
  16  Contains Nonbinding Recommendations 
  For chemometric models: 
 
  A rationale for using a particular wavelength range, spectral pretreatment,22 
algorithm, and threshold 
 
  For quantitative methods, the internal model validation conducted to justify the 
number of latent variables, including a predicted residual error sum of squares 
(PRESS) plot or other diagnostic to demonstrate that the model is not overfit 
 
  For a qualitative model (identification library), the positive predictive value used, 
such as the distances (match values) between all library products for small libraries or 
a graphical representation for large libraries 
 
  The applicants handling of outliers 
 
  Raw and pretreated spectra, including pure component spectra, if available 
 
  For in-line or on-line methods, as applicable: 
 
  Data that demonstrate the suitability of the probe window location 
 
  Data that support a contingency plan for the potential failure of the in-process NIR 
method to detect the pre-established endpoint even after prolonged processing 
 
  For on-line and in-line methods for blending or mixing, as applicable: 
 
  An estimation of and a rationale for the effective sample size, including the 
applicants consideration of the samples potential movement during spectral 
acquisition 
 
  A justification for using a rate-of-change-based method, as well as any data 
supporting the endpoint criteria of the blending or mixing process 
 
C.  Validation Information 
 
For the validation of NIR analytical procedures, applicants should provide at least the following 
information: 
 
  The external validation set, including: 
 
  The associated batches, including the number of batches, the batch size, and the 
number of samples from each batch that were used to create the external validation 
set 
 
22 For spectral pretreatments, applicants should also provide information about the order that the processing was 
applied. 
  17  Contains Nonbinding Recommendations 
 
  For quantitative procedures, the distribution of the reference values in the external 
validation set (which can also be shown in the form of predicted versus reference 
results or in residual plots) 
 
  The specificity, linearity, accuracy, precision, and robustness of the quantitative 
procedures used, as appropriate23 
 
  A validation of the qualitative method used, including testing for specificity of that 
method 
 
  The reference analytical procedure and its standard error 
 
  Data that demonstrate that the model is valid at commercial scale (e.g., the use of 
commercial-scale data during development of the procedure) 
 
  The procedures maintenance over the drug products life cycle, which can be written as 
a high-level summary and include, for example: 
 
  The frequency of, methods for, and acceptance criteria for periodic model verification 
 
  Any possible triggers for method verification to be conducted outside of the regular 
schedule 
 
For in-line blending or mixing, applicants should also provide validation information about their 
sampling strategies for the reference analytical procedure and the test results used to verify the 
blend uniformity as determined by NIR. 
 
For measuring assay and content uniformity, applicants should also, when feasible, provide 
validation information comparing their NIR results (including any tablet weight correction) with 
the reference analytical procedure results for the same samples.  This comparison should be 
performed on a statistically significant number of individual samples from commercial-scale 
batches. 
 
 
VIII.  LIFE CYCLE MANAGEMENT 
 
This section provides recommendations to applicants for the life cycle management of their 
qualitative and quantitative NIR analytical procedures.  Because of the unique characteristics and 
complexity of NIR procedures, as compared to conventional analytical procedures, FDAs 
recommendations for reporting postapproval changes to NIR procedures are detailed.   
 
After an applicant successfully validates and implements its NIR procedure, it should 
periodically evaluate the procedure during the life cycle of the drug product to continually ensure 
 
23 See section V.B. of this guidance. 
  18  Contains Nonbinding Recommendations 
that the procedure remains fit for its intended purpose.  This periodic evaluation is particularly 
important because NIR procedures (1) are highly sensitive to the manufacturing process and to 
the incoming materials attributes, and (2) offer only limited availability of real-time reference 
standards. 
 
Changes to NIR procedures used for commercial manufacturing must be handled in accordance 
with CGMP24 and should be managed under the manufacturing sites pharmaceutical quality 
system (PQS).25 
 
An applicant should determine an appropriate mechanism for reporting each postapproval 
change to its NIR procedure based on the potential impact the change has on: 
 
  The performance of the procedure (e.g., the procedures accuracy or specificity) 
  The identity, strength, quality, purity, or potency of the drug substance and drug product  
 
The significance of that impact (i.e., low, medium, or high) depends on the role of the procedure 
in the applicants overall control strategy.  For example, a failure of the procedure used for the 
real-time release testing (RTRT)26 of a finished drug product can have a high impact on drug 
product quality. 
 
The following table is a schematic representation of how applicants can evaluate the potential 
impact of a change to the NIR procedure and the appropriate corresponding reporting mechanism 
(i.e., managed solely under the manufacturing sites PQS, an annual report (AR), a changes 
being effected in 30 days supplement (CBE-30), or a prior approval supplement (PAS)).  The 
reporting categories suggested in this table apply when the corresponding supportive criteria are 
met as exemplified in section VIII.A. through D. of this guidance. 
 
Table:  Levels of Changes and Reporting Mechanisms 
  Potential Impact of a Change on the Procedures 
Performance 
Low  Medium  High 
Potential Impact of  Low  Minimal change  Minor change  Moderate change 
a Change on the  (PQS2)  (AR)  (CBE-30) 
Products Quality1 
High  Minor change  Moderate change  Major change 
(AR)   (CBE-30)   (PAS) 
1 This potential impact depends on the role of the procedure in the applicants overall control strategy. 
2 This implies that no regulatory reporting (AR, CBE, PAS) is needed.  
 
 
24 21 CFR 211.22(c); 21 CFR 211.100(b); 21 CFR 211.166(a) 
 
25 See ICH Q10. 
 
26 See the ICH guidance for industry Q8(R2) Pharmaceutical Development (November 2009). 
  19  Contains Nonbinding Recommendations 
The following subsections describe types of postapproval changes and provide recommendations 
for appropriate reporting mechanisms.  These recommendations are written to be generally 
appropriate for any applicant and are not intended to address all possible scenarios for managing 
postapproval changes.  If applicants implement a postapproval change not mentioned below, they 
can either use a strategy similar to the ones listed to determine the appropriate filing mechanism 
or, for special cases, request additional guidance from the relevant FDA review division.  
Applicants can also choose to use tools outlined in the ICH guidance for industry Q12 Technical 
and Regulatory Considerations for Pharmaceutical Product Lifecycle Management (May 2021), 
such as established conditions and comparability protocols (referred to in ICH Q12 as 
postapproval change management plans),27 which can leverage increased product and process 
knowledge to support alternate approaches to identifying postapproval changes that require 
reporting along with the associated reporting categories.    
 
A.  Major Changes  
 
Major changes to an NIR procedure could potentially have a high impact on the procedures 
performance and on the quality of the drug substance or drug product.  For example, FDA would 
expect the following changes to NIR analytical procedures to have a substantial potential to have 
an adverse effect on the identity, strength, quality, purity, and potency of drug products: 
 
  The addition of a new NIR analytical procedure that will be used for the RTRT of drug 
substances or drug products. 
 
  The replacement of an analyzer or a sample interface that will necessitate a new spectral 
set and a new calibration model for the NIR analytical procedure that is used for the 
RTRT of drug substances or drug products.  (When the acceptance criteria for validation 
of the updated procedure are equivalent to those of the approved procedure, a reduced 
reporting category could be considered.)  
 
  Significant changes to the in-process procedures used for the RTRT of drug substances or 
drug products where the acceptance criteria for validation of the revised procedure are 
not equivalent to those of the approved procedure. 
 
Major changes, as described in the examples above, must be reported in a PAS.28  
 
B.  Moderate Changes  
 
Moderate changes to an NIR procedure could potentially elicit either (1) a high impact on the 
procedures performance but a low impact on the drug products quality, or (2) a medium impact 
on the procedures performance but a high impact on the drug products quality.  For example, 
FDA would expect the following change to an NIR analytical procedure to have a moderate 
 
27 See also the draft guidance for industry Comparability Protocols for Human Drugs and Biologics:  Chemistry, 
Manufacturing, and Controls Information (April 2016).  When final, this guidance will represent FDAs current 
thinking on this topic).   
 
28 21 CFR 314.70(b) 
  20  Contains Nonbinding Recommendations 
potential to have an adverse effect on the identity, strength, quality, purity, and potency of drug 
products:  
  
  The establishment of a new chemometric model resulting from a new calibration set for 
an NIR analytical procedure that will be used for testing raw materials, in-process 
materials, or intermediates for a drug substance or a drug product 
 
Such changes must be reported in a CBE-30 supplement.29   
 
C.  Minor Changes  
 
Minor changes to an NIR procedure could potentially elicit (1) a medium impact on the 
procedures performance but a low impact on the drug products quality, or (2) a low impact on 
the procedures performance but potentially a high impact on the drug products quality.  For 
example, FDA would expect the following changes to NIR analytical procedures to have a 
minimal potential to have an adverse effect on the identity strength, quality, purity, and potency 
of drug products: 
 
  The addition of a new product (material) to a validated identification library, provided 
that the acceptance criteria are identical to the criteria used in the validation of the 
original procedure   
 
  A minor change to the NIR procedure used for RTRT of the drug substance or drug 
product (e.g., addition or subtraction of few spectra, small change in a wavelength range) 
providing the following conditions are met: 
 
  The size, composition, distribution, and variation of the calibration and validation sets 
are equivalent to those used for the originally approved procedure 
 
  The spectral data are pretreated using the same method that was used for the original 
procedure 
 
  The number of factors is established using an approach that is the same (or similar) to 
the approach that was used in the original procedure 
 
  The validation of a revised NIR procedure covers at a minimum the same attributes 
with the same or improved acceptance limits as those used in the original procedure  
 
Such changes must be reported in an AR.30 
 
 
29 21 CFR 314.70(c) 
 
30 21 CFR 314.70(d) 
  21  Contains Nonbinding Recommendations 
D.  Other Minimal Changes 
  
Minimal changes to an NIR procedure are those that have no or a low potential to impact the 
procedures performance and the drug product quality.  These changes would not require any 
regulatory notification; however, all changes should be managed and documented within the 
PQS31 and must be approved by the sites quality unit.32  For example, FDA would expect the 
following changes to NIR analytical procedures to have no potential adverse impact on the 
identity strength, quality, purity, and potency of drug products: 
 
  Addition of a few spectra to augment variation in the calibration set, when major 
calibration parameters and scope of validation remains the same as in the original 
calibration model 
 
  Repairs to an existing NIR instrument(s) when there is no change in the calibration model 
 
  Update to existing software associated with the NIR procedure when verification shows 
there are no changes in the predictive performance of the method   
 
 
31 See ICH Q10. 
 
32 21 CFR 211.22, 21 CFR 211.100, and 21 CFR 211.160. 
  22  Contains Nonbinding Recommendations 
GLOSSARY 
 
Accuracy:  As defined in ICH Q2(R1), [t]he accuracy of an analytical procedure expresses the 
closeness of agreement between the value which is accepted either as a conventional true value 
or an accepted reference value and the value found.33  For NIR procedures, the accepted 
reference value is usually obtained from a reference procedure. 
 
Calibration Model:  A model used to predict characteristics or properties of unknown samples. 
 
Calibration Set:  A set of spectra with corresponding physical characteristics and known 
concentrations. 
 
Chemometric Models:  Multivariate models that describe the relationship between the spectral 
variation in the calibration set and the samples characteristics (e.g., the samples drug 
concentration and identity).   
 
Chemometrics:  Multivariate methods to analyze, extract, or compare data from chemical 
systems. 
 
Detection Limit:  The lowest amount of analyte in a sample that can be detected at a specified 
confidence level but not necessarily quantitated with suitable precision and accuracy. 
 
External Validation:  For quantitative models, external validation involves confirming the NIR 
calibration models performance with an independent (or naive) dataset.  For identification 
libraries, external validation involves analyzing samples (challenges) not represented in the 
library to demonstrate the discriminative ability of the library model. 
 
External Validation Set:  A set of spectra and the related reference values that are (1) separate 
from the calibration set and internal validation set, and (2) used to give an independent 
assessment of the performance of the calibration model.  Ideally, the range of the validation set 
should be similar to that of the calibration set. 
 
Identification Test:  A qualitative implementation of NIR spectroscopy for NIR procedures 
where an unknown sample spectrum is compared to one or more spectra representing materials 
of known identity included in a spectral library. 
 
Internal Validation:  A part of the model optimization process that involves a comparison of 
NIR predictions with corresponding reference values.  Internal validation can be accomplished 
using an internal validation set (test set) or the calibration data by cross-validation.  Internal 
validation is not a substitute for the external validation of the model.  Although this guidance 
uses the term internal validation, other publications might use the terms internal model testing or 
model optimization instead, in particular when referring to multivariate methods in general.   
 
 
33 See ICH Q2A, p. A-1. 
  23  Contains Nonbinding Recommendations 
Internal Validation Set:  A set of spectra with corresponding physical characteristics and 
known concentrations obtained from samples that have physical and chemical characteristics that 
span a range of variabilities similar to the samples used to construct the calibration set.  Note that 
this guidance uses the term internal validation set for consistency; however, the equivalent terms 
test set or internal test set can be found in other publications.34 
 
Linearity:  The ability of the NIR procedure (within a given range) to achieve predictions that 
are proportional to the concentration of the analyte in the sample (i.e., the reference 
concentration). 
 
NIR Model:  A mathematical expression that describes how the NIR spectral data are related to 
the analyte property of interest. 
 
Precision:  The closeness of agreement between a series of measurements obtained from 
multiple sampling of the same homogeneous sample under the measurements prescribed 
conditions.  Precision is determined by three factors:  (1) repeatability (intra-assay precision); 
(2) intermediate precision (within laboratory); and (3) reproducibility (between laboratories). 
 
Predicted Residual Error Sum of Squares (PRESS) Plot:  A function of the number of latent 
variables.  PRESS values decrease initially with an increasing number of latent variables, reach a 
minimum, and then increase again or remain stable.  PRESS plots are used to estimate an optimal 
number of latent variables to avoid overfitting. 
 
Quantitation Limit:  The lowest amount of analyte in a sample that can be quantitatively 
determined with the desired precision and accuracy. 
 
Rate-of-Change Model:  An NIR procedure based on observed changes in (1) the concentration 
of the active ingredient, (2) the other ingredients (i.e., the ingredients of primary interest), or (3) 
the spectral magnitude.  This model is typically used for blending monitoring where the endpoint 
is often related to the rate of change falling below a certain threshold. 
 
Real-Time Release Testing (RTRT):  The ability to evaluate and ensure the quality of the in-
process and/or final product based on process data, which typically include a valid combination 
of measured material attributes and process controls. 
 
Reference Method:  An analytical procedure (e.g., a high-performance liquid chromatography 
test) to obtain the reference values of the calibration and validation samples. 
 
Reference Values:  Numerical results obtained from a reference method. 
 
Robustness:  The capacity of NIR model predictions to remain unaffected by small variations in 
manufacturing and environmental conditions.  Robustness indicates the procedures reliability 
during its normal usage. 
 
 
34 See, for example, United States Pharmacopeia General Chapter <1039> Chemometrics. 
  24  Contains Nonbinding Recommendations 
Specificity:  The ability to unequivocally assess the analyte in the presence of components that 
may be expected to be present (e.g., impurities, degradants, or matrices).35 
 
Spectral Acquisition Time:  The period during which a specified number of scans are averaged 
into a sample spectrum. 
 
Standard Error of Calibration (SEC):  A measure of the difference between the NIR values 
and reference values of the same calibration set.  SEC is shown by the following equation: 
 
 
2
nn
ii=1yyCC,ii YYCC,ii
SSSSSS =   
nnpp1
 
Where Y  = NIR predicted value obtained from a calibration set sample; y  = reference value 
c c
from the same calibration set sample; n = number of samples; and p = number of coefficients in 
the model (e.g., wavelength (such as multiple linear regression), principle components (such as 
principal component analysis or principal component regression), or factors (such as partial least 
square)). 
 
Standard Error of Prediction (SEP):  A measure of the difference between the NIR values and 
reference values of the validation set.  SEP is shown by the following equation: 
 
 
2
nn
ii=1yyVV,ii YYVV,ii
SSSSSS =   
nn
 
Where Y  = NIR predicted value from a validation set sample obtained using the established NIR 
v
calibration model; y  = reference value of the same validation set sample; and n = number of 
v
samples. 
 
 
35 See ICH Q2A, p. A-1. 
  25