How the modern concept of a lifecycle model, which is based on process validation and described in ICH guidelines Q8, Q9, and Q10, can be applied to analytical procedures.
Analytical control strategy - Part -4 : How the ACS Applies to the Product Lifecycle and How the modern concept of a lifecycle model can be applied to analytical procedures.
This free preview presentation is a very confusing subject for many consultants and QA/QC professionals. We discuss target measurement uncertainty (TMU), which is the maximum admissible uncertainty defined for a specific measurement. TMU is included in the analytical target profile, which in turns is a tool to define a priori quality criteria for results generated by analytical methods.
Analytical Target Profile (ATP) - Structure and Application Throughout the An...pi
ICH Q2: Validation of Analytical Procedures describes the current concepts of validation, verification and transfer of procedures. This approach addresses portions of the analytical lifecycle but also has a number of downsides. As an alternative to this approach, predefined criteria can be established in the form of an Analytical Target Profile (ATP).
How the modern concept of a lifecycle model, which is based on process validation and described in ICH guidelines Q8, Q9, and Q10, can be applied to analytical procedures.
Analytical control strategy - Part -4 : How the ACS Applies to the Product Lifecycle and How the modern concept of a lifecycle model can be applied to analytical procedures.
This free preview presentation is a very confusing subject for many consultants and QA/QC professionals. We discuss target measurement uncertainty (TMU), which is the maximum admissible uncertainty defined for a specific measurement. TMU is included in the analytical target profile, which in turns is a tool to define a priori quality criteria for results generated by analytical methods.
Analytical Target Profile (ATP) - Structure and Application Throughout the An...pi
ICH Q2: Validation of Analytical Procedures describes the current concepts of validation, verification and transfer of procedures. This approach addresses portions of the analytical lifecycle but also has a number of downsides. As an alternative to this approach, predefined criteria can be established in the form of an Analytical Target Profile (ATP).
This presentation was made to solely for students to make them aware/ understand basics of “Analytical Method Validation”. These slides are part of lectures delivered in M. Pharmacy Curriculum & taken up from various books and websites
Data Analysis Of An Analytical Method Transfer ToDwayne Neal
To provide the basis for a PDA task force discussion to arrive at a consensus of best industry practices for data analysis of method transfers. The discussion is also relevant to method validation activities.
What is Validation?
Methods validation is the process of demonstrating that analytical procedures are suitable for their intended use-Guidance for Industry
Validation is a process-risk will determine the effort
High Risk:Total validation
Moderate Risk:Testing,Documentation
Low Risk:Testing the change
Accuracy
ICH defines accuracy of an analytical procedure as the closeness of agreement between the conventional true value or an accepted reference value and the value found.
% Accuracy = Experimental- True Value * 100
True Value
Precision
Precision of analytical procedure is defined as closeness of agreement in values between a series of measurements. As per ICH, precision is considered at three different levels:
Repeatability or intra—assay precision: precision data are obtained by repeatedly analyzing, in one lab on one day, aliquots of a homogeneous sample.
Intermediate precision: precision obtained when the assay is performed by multiple analysts, multiple instruments, and multiple days in one lab.
Reproducibility: precision between laboratories.
Specificity
Specificity is the ability of the method to accurately measure the analyte response in the presence of all potential sample components.
It is very important in the analysis of complex mixtures by GC, HPLC, AA, ICP, etc.
Limit of Detection (LOD)
Limit of Detection (LOD) is the lowest amount of analyte in a sample which can be reliably detected but not necessarily accurately or precisely measured.
Signal/Noise = 2 to 3
Limit of Quantitation (LOQ)
Limit of Quantitation (LOQ) is the lowest amount of an analyte that can be quantitatively determined with suitable precision and accuracy.
Signal/Noise = 10 to 20
Linearity and Range
Linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample.
Range: Interval from the upper to the lower concentration (amounts) of analyte in the sample (including these concentrations) for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy and linearity
Must cover 80-120% of product claims
Usually evaluated from the same data set as linearity, precision, accuracy
Want to learn more about analytical method validation, FDA requirements and best practices to comply with them? ComplianceOnline webinars and seminars are a great training resource. Check out the following links:
ICH, FDA and USP Requirements for Method Validation
How to Validate Analytical Methods and Procedures
Validation of Analytical Methods and Procedures
Eliminate the Confusion - Analytical Method Qualification and Validation
Lifecycle Approach to Analytical Methods with QbD Elements
Analytical Instrument Qualification and System Validation
Lifecycle Approach to Analytical Methods for Drug Products
For details vis
Introduction to Analytical Method Development and Validation for Therapeutic ...PeteDeOlympio
Training Seminar: Introduction to Analytical Method
Development and Validation for Therapeutic Proteins
Wednesday, January 21, 8:30 AM-4:25 PM - Thursday, January 22, 8:30 AM-12:30 PM
Part of PepTalk: The Protein Science Week
This course is a panoramic review of analytical method development and validation for therapeutic proteins, including antibodies and enzymes. It is intended for scientists working on therapeutic proteins in AD, QC, PD or related functional areas. It starts with basic knowledge of work on therapeutic proteins: manufacturing of proteins drugs, regulatory affair knowledge and protein chemistry. It then discusses fundamentals and practical aspects of commonly used analytical methods for proteins, including methods for structure elucidation, glycan characterization, biophysical characterization, potency measurement, purity and impurity analyses. The course concludes with the strategy and common practice in method validation and method transfer, including regulatory compliance at different stages of product development, application of DOE and QbD. The course emphasizes practical applications, real-world examples and useful tips.
For full details visit www.chi-peptalk.com/peptalk_content.aspx?id=140090&libID=140061
Analytical method validation, ICH Q2 guidelineAbhishek Soni
Analytical Method Validation, ICH Q2 Guideline.
General principles related to the analytical method validation.
Validation of analytical method as per International Council for Harmonisation(ICH) guidelines and the United States Pharmacopeia(USP).
Glossary.
Useful in understanding the terms :
Specificity
Linearity
Range
Accuracy
Precision
Detection limit
Quantitation limit
Robustness
Ruggedness
System suitability testing
Understanding of Analytical Method Validation Approach in Pharmaceutical Industry. Analytical method validation Verification is a wide chapter and a huge scope of applicability. In different types of methods, instrument, measurement approach all can effect the validation effort. However the basic fundamental will remains same, the parameters, acceptance criteria, functionality may vary depending upon the type of method, instrument etc.
This presentation was made to solely for students to make them aware/ understand basics of “Analytical Method Validation”. These slides are part of lectures delivered in M. Pharmacy Curriculum & taken up from various books and websites
Data Analysis Of An Analytical Method Transfer ToDwayne Neal
To provide the basis for a PDA task force discussion to arrive at a consensus of best industry practices for data analysis of method transfers. The discussion is also relevant to method validation activities.
What is Validation?
Methods validation is the process of demonstrating that analytical procedures are suitable for their intended use-Guidance for Industry
Validation is a process-risk will determine the effort
High Risk:Total validation
Moderate Risk:Testing,Documentation
Low Risk:Testing the change
Accuracy
ICH defines accuracy of an analytical procedure as the closeness of agreement between the conventional true value or an accepted reference value and the value found.
% Accuracy = Experimental- True Value * 100
True Value
Precision
Precision of analytical procedure is defined as closeness of agreement in values between a series of measurements. As per ICH, precision is considered at three different levels:
Repeatability or intra—assay precision: precision data are obtained by repeatedly analyzing, in one lab on one day, aliquots of a homogeneous sample.
Intermediate precision: precision obtained when the assay is performed by multiple analysts, multiple instruments, and multiple days in one lab.
Reproducibility: precision between laboratories.
Specificity
Specificity is the ability of the method to accurately measure the analyte response in the presence of all potential sample components.
It is very important in the analysis of complex mixtures by GC, HPLC, AA, ICP, etc.
Limit of Detection (LOD)
Limit of Detection (LOD) is the lowest amount of analyte in a sample which can be reliably detected but not necessarily accurately or precisely measured.
Signal/Noise = 2 to 3
Limit of Quantitation (LOQ)
Limit of Quantitation (LOQ) is the lowest amount of an analyte that can be quantitatively determined with suitable precision and accuracy.
Signal/Noise = 10 to 20
Linearity and Range
Linearity of an analytical procedure is its ability (within a given range) to obtain test results which are directly proportional to the concentration (amount) of analyte in the sample.
Range: Interval from the upper to the lower concentration (amounts) of analyte in the sample (including these concentrations) for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy and linearity
Must cover 80-120% of product claims
Usually evaluated from the same data set as linearity, precision, accuracy
Want to learn more about analytical method validation, FDA requirements and best practices to comply with them? ComplianceOnline webinars and seminars are a great training resource. Check out the following links:
ICH, FDA and USP Requirements for Method Validation
How to Validate Analytical Methods and Procedures
Validation of Analytical Methods and Procedures
Eliminate the Confusion - Analytical Method Qualification and Validation
Lifecycle Approach to Analytical Methods with QbD Elements
Analytical Instrument Qualification and System Validation
Lifecycle Approach to Analytical Methods for Drug Products
For details vis
Introduction to Analytical Method Development and Validation for Therapeutic ...PeteDeOlympio
Training Seminar: Introduction to Analytical Method
Development and Validation for Therapeutic Proteins
Wednesday, January 21, 8:30 AM-4:25 PM - Thursday, January 22, 8:30 AM-12:30 PM
Part of PepTalk: The Protein Science Week
This course is a panoramic review of analytical method development and validation for therapeutic proteins, including antibodies and enzymes. It is intended for scientists working on therapeutic proteins in AD, QC, PD or related functional areas. It starts with basic knowledge of work on therapeutic proteins: manufacturing of proteins drugs, regulatory affair knowledge and protein chemistry. It then discusses fundamentals and practical aspects of commonly used analytical methods for proteins, including methods for structure elucidation, glycan characterization, biophysical characterization, potency measurement, purity and impurity analyses. The course concludes with the strategy and common practice in method validation and method transfer, including regulatory compliance at different stages of product development, application of DOE and QbD. The course emphasizes practical applications, real-world examples and useful tips.
For full details visit www.chi-peptalk.com/peptalk_content.aspx?id=140090&libID=140061
Analytical method validation, ICH Q2 guidelineAbhishek Soni
Analytical Method Validation, ICH Q2 Guideline.
General principles related to the analytical method validation.
Validation of analytical method as per International Council for Harmonisation(ICH) guidelines and the United States Pharmacopeia(USP).
Glossary.
Useful in understanding the terms :
Specificity
Linearity
Range
Accuracy
Precision
Detection limit
Quantitation limit
Robustness
Ruggedness
System suitability testing
Understanding of Analytical Method Validation Approach in Pharmaceutical Industry. Analytical method validation Verification is a wide chapter and a huge scope of applicability. In different types of methods, instrument, measurement approach all can effect the validation effort. However the basic fundamental will remains same, the parameters, acceptance criteria, functionality may vary depending upon the type of method, instrument etc.
Analytical method development and validation are one of the very imp aspects in Drug testing and approval process.Here I tried to explain the same with my experience.
Analytical Method Validation is a process that is used to demonstrate the suitability of an analytical method for an intended purpose.Regulations and quality standards that have an impact on analytical laboratories require analytical methods to be validated.
Variability of clinical chemistry laboratory resultsAdetokunboAjala
Understanding the concepts associated with variability of laboratory results would help laboratorians improve the quality of laboratory service as well as aid the drive towards harmonization of laboratory quality practices.
NDSRIs - Nitrosamine Drug Substance-Related Impurities (NDSRIs)Chandra Prakash Singh
NDSRIs impurities share structural similarity to the API (having the API or API fragment in the chemical structure) and are therefore unique to each API.
NDSRIs generally form in the drug product through nitrosation of APIs (or API fragments) that have secondary or tertiary amines when exposed to nitrosating agents such as residual nitrites in excipients used to formulate the drug product.
Generally, the presence of high levels of NDSRIs has been associated with drug products rather than APIs because NDSRI formation usually results from a reaction between the API or API fragment and nitrosating agents in the drug formulation.
However, NDSRIs can potentially form in APIs when nitrosating agents are present in the API manufacturing process or when APIs undergo processing steps that can potentially induce their formation such as fluid bed drying at an elevated temperature and jet milling because these can create favorable conditions in which nitrogen oxides can react with at-risk APIs.
NDSRIs often lack carcinogenicity and mutagenicity study data (typically from animal studies) from which an AI limit can be determined.
This guidance provides a recommended methodology for AI limit determination that uses structural features of NDSRIs to generate a predicted carcinogenic potency categorization and corresponding recommended AI limit that manufacturers and applicants can apply, in the absence of other FDA recommended AI limits, in their evaluations of approved and marketed drug products as well as products in development or under review by FDA.
Currently Identified Risk Factors for Presence of Nitrosamines.pptxChandra Prakash Singh
N-Nitrosamines can be formed when an amine and nitrosating agent are combined under favourable conditions although other generation pathways are also possible, such as e.g. oxidation and reduction processes from hydrazine-type compounds and N-nitro derivatives.
Root causes for N-nitrosamines in medicinal products identified to date can be grouped as risk factors linked exclusively with the manufacturing process and storage of active substance and/or as risk factors associated with manufacture and storage of the finished product.
Moreover, there are risk factors specifically linked to GMP aspects.
Basic Understanding of LCMS
Ion Optics Path and Parameters.
Mass spectrometry measures the mass-to-charge ratio of ions to identify unknown compounds, to quantify known compounds, and to provide information about the structural and chemical properties of molecules.
The mass spectrometer has a series of quadrupole filters that transmit ions according to their mass-to-charge (m/z) ratio.
When the energy of the accelerated electrons is higher than a certain threshold value (which depends on the metal anode), a second type of spectrum is obtained superimposed on top of the white radiation. It is called the characteristic radiation and is composed of discrete peaks.
The energy (and wavelength) of the peaks depends solely on the metal used for the target and is due to the ejection of an electron from one of the inner electron shells of the metal atom.
This results in an electron from a higher atomic level dropping to the vacant level with the emission of an X-ray photon characterised by the difference in energy between the two levels.
CHARACTERIZATION OF CRYSTALLINE AND PARTIALLY CRYSTALLINE SOLIDS BY X-RAY POWDER DIFFRACTION (XRPD)
USP <941>
Every crystalline phase of a given substance produces a characteristic X-ray diffraction pattern.
Diffraction patterns can be obtained from a randomly oriented crystalline powder composed of crystallites (crystalline regions within a particle) or crystal fragments of finite size.
Essentially three types of information can be derived from a powder diffraction pattern:
The angular position of diffraction lines (depending on geometry and size of the unit cell).
The intensities of diffraction lines (depending mainly on atom type and arrangement and preferred orientation within the sample.
Diffraction line profiles (depending on instrumental resolution, crystallite size, strain, and specimen thickness).
LCMS - Ion Optics Path and Parameters
Source and gas parameters: These parameters can change depending on the ion source used.
Compound parameters: These parameters consist mostly of voltages in the ion path. Optimal values for compound-dependent parameters vary depending on the compound being analyzed.
Resolution parameters: These parameters affect the resolution and calibration.
Detector parameters: These parameters affect the detector.
A divert valve allows you to switch portions of the mobile phase to waste before the mass spectrometer.
This is particularly important for the portion containing all the un-retained components – many of which are likely to be involatile and contaminate the source. If you really want to keep things clean use a divert valve to divert everything to waste except the compounds of interest.
The integrated diverter valve, which is located next to the ion source, can be plumbed in injector mode or diverter mode.
LCMS Interface
API techniques (ESI, APCI and APPI)
In LCMS, ions can be generated through either the continuous or pulsed (discontinuous) modes.
The three API techniques (ESI, APCI and APPI) that were introduced operates in the continuous mode, giving a constant flow/supply of ions to the MS.
On the other hand, the pulsed mode generates a discontinuous source of ions such as the Matrix-Assisted Laser Desorption/Ionization (MALDI).
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Advantages and Disadvantages of CMS from an SEO Perspective
Analytical control strategy 3
1. Analytical Control Strategy – Part-3
How the modern concept of a lifecycle model can be applied to analytical procedures.
Chandra Prakash Singh
2. The QRM process begins once
Appropriate analytical technique has been selected . Tentative procedure conditions have been chosen.
The aim of the QRM process is to take the proposed procedure conditions and identify appropriate controls on the process inputs
that will ensure the desired process output (i.e., a reportable value that meets the requirements stipulated in the ATP).
The first step in the QRM process is
the risk assessment, which starts
with the risk (hazard) identification.
At this time, the question is, What
might go wrong?
An Example of a Process Flow Chart for an HPLC Procedure
Set up the HPLC
Prepare Mobile Phase
Start HPLC Run
Integrate Chromatograms
and Calculate Results
Prepare Standards Prepare Samples
The risk identification step begins by
developing a process flow chart
highlighting the key steps involved
in the analytical procedure.
3. The sample preparation step can be broken down into a number of detailed sub-steps.
Each high-level step in the process can be further broken down using process mapping tools.
HPLC Grade
Acetonitrile
HPLC Grade
Water
Sample
Received
form Store
and Ready
to weigh
Add 750 mL of
Acetonitrile to
the solvent
container.
Add 250 mL of
Water to
container.
Stir to Mix.
Dissolving
Solvent
Select
Qualified and
calibrated
balance.
Tare weighing
boat
Weigh 100 mg
/ ± 5 mg
Transfer to
100 mL
volumetric
flask.
Wash Sample
into the flask
with dissolving
solvent
Add approx. 70
mL dissolving
solvent.
Place flask in
sonicate bath
and sonicate for
15 minutes.
Makeup with
mark with
dissolving
solvent.
Transfer 1 mL
into HPLC vial.
Sample
Solution ready
to measure.
4. This detailed process map can then be used to identify the variables associated with the process. Ishikawa diagrams
(fishbone diagrams) can be used in conjunction with the detailed process maps to identify the potential variables.
The Ishikawa diagram is used in helping to brainstorm potential variables and, as with any type of brainstorming, no
judgment should be made at this stage on whether a variable is likely to be critical or not.
The aim is simply to ensure that the list of variables is as comprehensive as possible.
Ishikawa diagram, used to identify potential variables associated with the sample preparation step.
Man
Machine
Method
Measurement
Mother Nature
Materials
Skill in weighing
Skill in use of volumetric flasks
Sonic Bath Transducer frequency
Sonic bath No. of Transducers.
Sonication Time
%Acetonitrile in dissolution solvent
Number of flask in sonic bath
Mixing Time
Mixing Speed.
AcetonitrileSource
Water Quality
Glassware stability in solution
HPLC Vial type
Sonic Bath Water Level
Timer
Balance Accuracy
Room Temperature
Room Humidity
5. 1. RISK IDENTIFICATION
The first step in the assessment is risk identification. It answers the question, What can go wrong?
The variables associated with the sample preparation and HPLC setup steps.
(This is a subset of the total list of variables that may need to be examined.)
Variables for sample preparation unit of operation:
• % Acetonitrile in the sample solvent
• Sonication time
• Analyst skill in sample preparation
• Humidity of the laboratory
• Quality of acetonitrile used in the dissolving solvent
Variables for the measurement unit of operation (HPLC setup):
• Column temperature
• % Acetonitrile in the mobile phase
• Batch of packing material used in the HPLC column
• Quality of the acetonitrile
Risk Assessment
6. 2. RISK ANALYSIS
The next step in the assessment is the risk analysis.
The risk analysis answers the question, What is the likelihood (probability) it will go wrong?
Estimation of the risk associated with each of the variables.
1. Controlled Variables - When considering the variables identified in the risk identification step, it will be possible to
identify certain variables which, from prior knowledge, will be important to control within a certain range.
2. Noise Variables - Some of these variables will be difficult or impractical to control or are known to be of low risk.
3. Experimental Variables - whereas some will require the performance of experiments to understand how critical they are
and to determine the range over which they need to be controlled.
The risk analysis process aims to identify, from the many variables in the output from the risk identification step, those for
which an understanding of their impact on the reportable value is required in order to establish appropriate control limits.
7. Analytical Unit of
Operation
Variable Potential Hazard Accuracy Precision
Sample Preparation
% Acetonitrile in the sample
dissolution solvent
Completeness of the dissolution of the sample
Sonication Time Completeness of the Dissolution of the sample
Analyst Skill
Incorrect sample preparation weighing, dilutions, use of
volumetric flask.
Humidity of the laboratory
Moisture absorption can lead to inaccurate weighing or
degradation
Grade of acetonitrile used in
the dissolution solvent
Potentially can impact if contaminations interfere with the
analyte
Measurement
(HPLC Setup)
Column Temperature Column performance, resolution, peak shape
% Acetonitrile in the mobile
phase
Column performance, resolution, peak shape
Batch of packing material
used in the HPLC column
Column performance, resolution, peak shape
Quality of acetonitrile
Potential impact can affect the baseline, and or provide high
background noise depending on the analytical wavelength
Heat Map
Valuable tool to support a preliminary qualitative assessment of risks. The heat map provides a visual indication of which
variables are considered to have a potentially strong impact (red), medium impact (amber), or minor impact (green) on the
procedure performance in terms of accuracy and precision that can be related to the requirements of the ATP.
8. The Rationale for The Risk Level Assignments is as Follows.
1. At this stage it is useful to separate the variables into those that can be controlled, those that cannot be controlled, and
those that will be subject to further experimentation.
2. An uncontrollable variable is one that may have an impact on the accuracy or precision of the data, but it is not possible
to directly measure the relationship between the variable and the response in an experiment.
3. It is not possible to understand and control how potential variability of column packing of future batches might impact
the chromatography. Although these variables are not directly controllable and therefore not included in a DoE, they are
still potential hazards that need to be considered in the ACS.
Batch-to-batch variability of the column packing cannot be studied. Adequate performance of the column will be verified by
the system suitability requirements to ensure performance of the analytical procedure. This risk has been mitigated by
increasing detectability of the variation. The column-to-column variability, however, needs to be accepted as residual risk.
9. The four controllable variables that are considered to present potential risk, studied in a DoE to determine the sensitivity of the
variables, eliminate bias, and determine ranges where the quality requirement of the reportable value established in the ATP
will be met.
When a significant number of variables requires an experimental study to understand their impact, a “screening DoE” may be
performed first, to identify those with the greatest impact on the quality of the reportable value.
DoE experiments can easily be run using software to analyze a series of samples under the conditions stated.
Conditions for the DoE Experiment
Variable High Level Mid Level Low Level
% Acetonitrile in sample solvent 80 65 50
Sonication time (min) 20 12 5
Column temperature (°C) 45 35 (Ambient; 25)
% Acetonitrile in mobile phase 80 70 60
The mid level is presented as the proposed condition of the analytical procedure.
At this time, the range (high to low) needs to be expanded beyond values expected as normal fluctuations typically
encountered during routine use.
10. The information from a DoE study indicated that all four of these variables (% acetonitrile in the sample solvent, sonication
time, column temperature, and % acetonitrile in the mobile phase) have a strong correlation with the accuracy and/or
precision of the data (i.e., the “severity of harm” from these variables is high).
The risk assessment needs to consider not only the severity of harm (or strength of the relationship between the input variable
and the desired output) but also the likelihood of occurrence - i.e., what is the probability that this variable will vary to the
extent that quality of the reportable value will be impacted? The assessment of the severity can be combined with the
assessment of probability of variation to give an overall risk score, and the resulting risk score can be further reduced by
incorporating analytical procedure performance checks in the system suitability).
11. The risk acceptance criteria (or the risk protection threshold) for this step is the TMU. Therefore, a risk target of 10 will
correspond to the TMU. Any variable or combination of variables that equal or exceed the risk target of 10 will need to be
controlled in ranges that will ensure the required performance of the procedure. If the above example is evaluated against the
criteria, it would be concluded that all four of the variables exceed TMU and therefore should be subject to ACS.
3. Risk Evaluation
Risk evaluation compares the risk versus the given risk criteria.
Risk Evaluation
Variation Severity (from DoE)
(1 Low, 5 high)
Probability of variation
(1 Low, 5 high)
Risk Score
% Acetonitrile in sample solvent 4 3 12
Sonication Time (min) 4 3 12
% Acetonitrile in mobile phase 5 4 12
Column temperature (°C) 5 2 10
12. The DoE essentially can establish a quantitative relationship between the variable studied and the response (i.e., the TMU).
Therefore, the DoE can also be used to predict ranges for the variables studied where the TMU will be met. The DoE results
suggest that, in the ranges specified in Table below, the criteria will be met.
Risk Control
Risk Reduction:
Risk reduction can include actions to reduce the risk, reduce the probability, or improve the detectability.
Conditions for the DoE Experiment
Variation High Level Mid Level Low Level
% Acetonitrile in sample solvent 70 65 60
Sonication Time (min) 15 12 10
Column temperature (°) 40 35 30
% Acetonitrile in mobile phase 75 70 65
13. At this time, a verification step confirms that the ranges predicted are acceptable for three of the four variables studied. The %
acetonitrile in the mobile phase, while it meets the risk threshold, is still marginal. As previously stated, because these variables
affect the CQA, the severity component of the risk does not change; the risk can be reduced to an acceptable level by
decreasing the probability of variation and increasing the detectability needed to reduce the risk.
Risk Evaluation
Variation Severity (from DoE)
(1 Low, 5 high)
Probability of variation
(1 Low, 5 high)
Risk Score
% Acetonitrile in sample solvent 4 1 4
Sonication Time (min) 4 1 4
% Acetonitrile in mobile phase 5 2 10
Column temperature (°C) 5 1 5
14. Risk Assessment
Variable
Severity (from DOE)
(1 low, 5 high)
Probability of variation
(1 low, 5 high)
Detection
Risk Score
(SXP)/D*
% Acetonitrile in
mobile phase
5 2 4 2.5
*S: Severity; P: Probability; D:Detectability
Adding a system suitability requirement to detect the hazard, before the harm occurs to the reportable value, reduced the risk
from 10 to 2.5, which is well below the risk acceptance threshold.
15. Risk Assessment after Implementation of ACS
Analytical Unit
of Operation
Variable Potential Hazard Control Strategy Accuracy Precision
Sample
Preparation
% Acetonitrile in the
sample dissolution
solvent
Completeness of the dissolution of the sample Specify % acetonitrile in the sample
solvent 65% +/-5%
Sonication Time Completeness of the Dissolution of the sample Sonication time between 10 and 15
minutes.
Analyst Skill Incorrect sample preparation weighing, dilutions,
use of volumetric flask.
Control by training mandated by GMP.
Humidity of the
laboratory
Moisture absorption can lead to inaccurate
weighing or degradation
No impact.
Grade of acetonitrile
used in the dissolution
solvent
Potentially can impact if contaminations interfere
with the analyte
Specify the grade of Acetonitrile.
Measurement
(HPLC Setup)
Column Temperature Column performance, resolution, peak shape Specify column temperature, 30+/-5°
% Acetonitrile in the
mobile phase
Column performance, resolution, peak shape Specify % acetonitrile in the sample
solvent 70% +/-5%.
Add system suitability requirement.
Batch of packing
material used in the
HPLC column
Column performance, resolution, peak shape Add system suitability requirement.
Quality of acetonitrile Potential impact can affect the baseline, and or
provide high background noise depending on the
analytical wavelength
Specify grade of acetonitrile.
16. Example-1.
The variability of the column packing for future columns cannot be controlled; and while the risk is reduced to an acceptable
level, it cannot be eliminated completely.
Example-2.
The composition of the sample solvent was established and verified using drug substance samples available to the laboratory
at the time of the analytical development qualification, and it is not likely to change during the product lifecycle. Therefore,
the probability that the polymorph will vary from one lot to the next is negligible because the polymorph control is typically
part of the drug substance specifications. However, because different polymorphs may have very different solubilities, in the
case of a compendial procedure the suitability of the sample solvent should be verified as part of the procedure installation.
By providing target acceptance criteria, linked holistically to the quality of the output, will trigger a systematic science- and
risk-based strategy for development, qualification, and performance monitoring during routine use. This will improve overall
performance of the analytical procedures by placing focus on the output. The output is held to the standard established in the
ATP and directly linked to the fitness for purpose of the analytical procedure.
RISK ACCEPTANCE
Risk cannot be completely eliminated but it can be reduced to an acceptable level.
17. Measures used to verify the adequate performance of an analytical procedure are, for example, %RSD for calibration
standards and replicates, system suitability for chromatographic procedures, and resolution, plate count, or tailing factor.
For an HPLC procedure, for example, replicate injections may be used to provide assurance that the system precision is
satisfactory. Replicate sample or standard preparations provide assurance of the precision of the sample/standard
preparation step, and a resolution check may be used to provide assurance that the accuracy of the procedure is not
adversely affected by interference from other components in the sample.
Ideally, system suitability checks should be designed to detect variation in the performance of a procedure in routine use.
They should be based on an understanding of the risk and impact of variation, and the acceptance criteria used should be
chosen to ensure that the measurement uncertainty does not exceed the TMU.
A control sample (i.e., a homogenous and stable sample with a defined value for the attribute being measured) can also be
used to provide confidence in the accuracy of the data generated.