ISO 17025 Method Validation: A Step-by-Step Guide for Laboratories
Method validation is a cornerstone of competence in ISO/IEC 17025-accredited laboratories. It provides objective evidence that a method is suitable for its intended use and produces reliable, repeatable, and accurate results. Whether you're validating an in-house procedure, a modified standard method, or a commercial kit, understanding the validation process is critical for maintaining compliance and scientific credibility.
This guide explains how to plan and execute ISO 17025 method validation with practical steps, technical considerations, and actionable strategies.
What Is Method Validation in ISO/IEC 17025?
Method validation is the process of proving that a method performs as intended under specified conditions. According to ISO/IEC 17025:2017 (Clause 7.2), laboratories must validate non-standard, laboratory-developed, or significantly modified methods before use.
Validation applies when:
A standard method is adapted or extended
A method is developed internally
A commercial test kit or software is used without official approval
There’s no reference method available
Step-by-Step Process for ISO 17025 Method Validation
1. Define the Scope and Intended Use
Start by clearly articulating what the method is intended to measure, under what conditions, and why the results matter. This clarity ensures that your validation process is targeted and aligned with your lab’s purpose and constraints.
Define:
Analyte(s), matrix, and concentration range: Specify the substances of interest, the sample types (e.g., water, soil, serum), and the expected operating range for quantification.
Method type: Determine whether the method yields qualitative (presence/absence) or quantitative (measured value) results.
Regulatory or client requirements: Identify whether the method must meet national standards, industry-specific tolerances, or contractual specifications.
Performance criteria: Choose criteria relevant to the method and context (e.g., accuracy, precision, LOD, LOQ, robustness, and measurement uncertainty).
Actionable Guidance:
Engage stakeholders (QA, regulatory, clients) to validate the scope early in the process.
Review similar existing methods or regulatory guidance for scope and criteria alignment.
Ensure the scope aligns with the analytical capability of your lab—including instruments, software, and analyst skill level.
Thoughtful Considerations:
If the method will support legally defensible results, the validation plan must be more rigorous and the acceptance criteria more conservative.
Ensure the defined scope is practical to evaluate given your available resources (e.g., matrix availability, reference materials, analyst time).
Document any assumptions or exclusions—for example, if the method will not apply to certain matrices or concentration ranges.
2. Choose Validation Parameters
Select appropriate parameters based on the method type and its intended use. The objective is to ensure the method produces reliable and consistent results under expected laboratory conditions.
Common parameters for quantitative methods:
Specificity / Selectivity: Can the method distinguish the analyte from other substances?
Linearity: Does the method provide results that are directly proportional to the analyte concentration across a defined range?
Limit of Detection (LOD): What is the lowest amount of analyte that can be reliably detected?
Limit of Quantification (LOQ): What is the lowest amount of analyte that can be quantified with acceptable accuracy and precision?
Accuracy (Trueness): How close are the results to the true value?
Precision (Repeatability and Reproducibility): How consistent are the results within and between runs?
Measurement Uncertainty: What is the quantified doubt in the result?
Robustness: How sensitive is the method to small changes in operating conditions?
Actionable Guidance:
Select parameters that are most relevant to your regulatory environment and sample type.
For qualitative methods, focus on parameters like selectivity, detection capability, and robustness.
Reference external sources (Eurachem Guide, AOAC Guidelines, ICH Q2(R2), CLSI) to define target performance levels.
Thoughtful Considerations:
Validate each parameter using a fit-for-purpose approach—some methods may not need all parameters.
Don’t overlook robustness; small operational changes (e.g., reagent lot or analyst) can affect performance.
Establish clear acceptance criteria based on the method’s intended decision-making role (e.g., pass/fail limits or reporting thresholds).
3. Design a Validation Plan
A well-structured validation plan sets expectations, defines responsibilities, and ensures the validation process is reproducible and aligned with ISO 17025 requirements.
The plan should include:
Objectives and scope: State the purpose and define what the validation will cover.
Method references or protocols: Include existing SOPs, standard methods, or literature sources.
Materials and equipment: List standards, reagents, instruments, and any software to be used.
Acceptance criteria: Define clear and justifiable thresholds for each selected parameter.
Roles and responsibilities: Assign tasks to qualified personnel, including analysts, reviewers, and approvers.
Schedule and timelines: Set realistic deadlines and review intervals.
Actionable Guidance:
Include contingency steps for method deviations or failures.
Cross-reference the plan with your lab’s quality manual or SOP on validation.
Make it traceable—use version control and formal approval with signatures.
Thoughtful Considerations:
Predefine how data will be evaluated (e.g., statistical tools, acceptance limits).
Ensure alignment between this plan and any applicable client, regulatory, or accreditation body requirements.
Keep the plan concise but comprehensive—it should guide but not overwhelm.
4. Perform Experimental Validation
Carry out laboratory testing under controlled conditions to generate the data needed to evaluate each validation parameter.
Steps:
Use matrix-appropriate materials (e.g., blank samples, reference materials, spiked samples).
Design studies with sufficient replicates to ensure statistical significance.
Include inter-day and inter-analyst variation to capture reproducibility.
Monitor variables such as temperature, humidity, instrument conditions, and reagent lots.
Actionable Guidance:
Keep detailed lab notebooks or electronic logs for traceability.
Randomize sample order and blind analysts where possible to reduce bias.
Use quality control charts to visualize trends or anomalies during the experiments.
Thoughtful Considerations:
Validate with realistic samples that reflect expected variability and complexity.
Ensure analysts are trained and competent before performing validation work.
Build in pauses for data review before moving to the next phase—catching problems early prevents costly rework.
5. Analyze and Interpret Results
Once testing is complete, critically evaluate the results to determine whether the method meets its defined performance criteria.
Steps:
Perform statistical analysis appropriate for each parameter (e.g., regression analysis for linearity, t-tests for accuracy).
Use control charts, RSD calculations, and confidence intervals to support findings.
Assess sources of variation (e.g., analyst, batch, instrument) and whether variability is acceptable.
Actionable Guidance:
Visualize data using plots and histograms for clear communication of performance trends.
Document not just results, but interpretation: explain why the method is fit (or not fit) for its intended purpose.
Identify any anomalies or outliers, and decide whether they indicate a problem or can be justified.
Thoughtful Considerations:
Engage both technical and quality personnel in reviewing the analysis.
Relate results back to the method’s intended decision-making use—can it support confident action?
Be transparent about limitations—this builds credibility with clients, auditors, and stakeholders.
6. Document and Approve the Validation
All validation activities must culminate in a comprehensive report that demonstrates the method’s fitness for use and compliance with ISO 17025.
A complete validation report should include:
Method description and purpose
Summary of experimental design
Raw data and calculations
Statistical analysis and graphical representations
Discussion of results and decision on method validity
Any deviations from the plan and justifications
Conclusions and recommendations for use
Signature and date from authorized approver(s)
Actionable Guidance:
Store the report in a version-controlled system with secure access.
Ensure alignment between report content and initial validation plan.
Link the report to the method's SOP and quality records.
Thoughtful Considerations:
Treat the report as a living document—it should support regulatory inspections, client inquiries, and internal audits.
Include references to related documents such as risk assessments, equipment logs, and calibration records.
Avoid jargon and ensure clarity so that reviewers (internal and external) can easily interpret findings.
7. Maintain Ongoing Verification
Validation is not a one-time event—ongoing verification ensures the method continues to perform as expected over time and under real operating conditions.
Routine verification practices include:
Running quality control (QC) samples in every batch
Monitoring method performance with control charts
Periodic re-evaluation through internal audits and reviews
Participating in interlaboratory comparisons or proficiency testing programs
Actionable Guidance:
Define a revalidation trigger list: changes in personnel, equipment, reagents, sample matrix, or software all warrant reassessment.
Track trends over time to detect gradual performance shifts.
Update the validation record if minor changes are evaluated and deemed not to affect fitness.
Thoughtful Considerations:
Build verification into routine workflows to avoid compliance drift.
Don’t assume long-term reliability—methods can degrade due to factors like supply chain changes or maintenance issues.
Use verification data to continuously improve method robustness and confidence in reporting.
Additional Considerations
Training: Ensure analysts performing validation are qualified and trained in both the method and data analysis.
Software tools: Use LIMS or statistical software to automate calculations and reduce transcription errors.
Uncertainty estimation: Integrate uncertainty analysis into the validation process—not just post-certification.
Transparency: Clearly distinguish between verification and validation in your procedures and records.
Conclusion
ISO 17025 method validation is both a technical and quality-driven activity. By approaching it with structure, rigor, and clarity, laboratories can ensure the reliability of their test results, enhance scientific defensibility, and remain audit-ready.
Written by Wintersmith Advisory – helping labs build ISO 17025 systems that are scientifically sound and operationally sustainable.
