analytical-method-validation
Helps your agent validate scientific analysis methods. This ensures tests and results are reliable and accurate for lab use.
What it does
This tool helps ensure that a testing method (like a chemical or biological test) works correctly for its intended purpose. It assists in planning, executing, and documenting these tests according to established rules.
When to use it
- ✓When planning a test to check if a method performs well.
- ✓When analyzing test results to see if the method is reliable.
- ✓When transferring a testing method to another lab or instrument.
Example of what to ask your AI
“How can I plan the validation of a testing method to ensure it's reliable for measuring a drug's concentration, following ICH Q2(R2) guidelines?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool uses different sets of rules (called 'frameworks') depending on the test type and goal. It helps define which characteristics of the test need to be evaluated and how the data should be collected and analyzed.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add K-Dense-AI/scientific-agent-skills --skill analytical-method-validationOr download just the file:
curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/analytical-method-validation/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Analytical Method Validation
When to use
Any time the question is whether an analytical procedure is fit for its intended purpose: designing a validation study, evaluating validation data, verifying a compendial procedure, transferring a procedure to another laboratory or instrument, or defending any of these in a report.
The two rules
1. Establish which framework governs before designing anything. The same assay validates differently under ICH Q2(R2), USP <1225>, ICH M10, CLSI EP, and ISO/IEC 17025. They differ in which characteristics are required, how the studies are laid out, and whether numeric acceptance criteria are supplied at all. Blending them produces a protocol that satisfies none of them.
2. State acceptance criteria before collecting data. Criteria chosen after seeing results are not acceptance criteria, and deciding them post hoc is a standing audit finding. ICH Q2(R2) deliberately supplies almost no numeric criteria — they have to come from the specification, the analytical target profile (ICH Q14 section 3), or development data. ICH M10 is the exception: it supplies explicit numbers, and they differ between chromatographic assays and ligand binding assays.
Scope
This skill plans studies, computes the statistics correctly, and structures the documentation. It
does not decide that a procedure is validated, release a batch, accept or reject a run, close
an investigation, or substitute for the analyst, the technical reviewer, the quality unit, or the
regulator. Every script reports computations and supported findings; only the responsible reviewers can
make the fitness-for-purpose decision. JSON uses null for unavailable statistics.
Copyright boundary
ICH guidelines are published openly and licensed for reuse with acknowledgement, so their requirements are encoded directly in this skill. USP general chapters, CLSI EP documents, and ISO standards are copyrighted and paywalled. For those, this skill supplies the designation, scope, and where to obtain an authorised copy — never the text, never invented thresholds. Do not ask an agent to retrieve, transcribe, or reconstruct their content. If a number matters and it lives in a paywalled document, read it from the authorised copy.
Frameworks
cd skills/analytical-method-validation/scripts
python3 plan_validation.py --list-frameworks
| Key | Governs | Numeric criteria supplied |
|---|---|---|
ich-q2r2 |
Release and stability testing of drug substances and products | Almost none — you derive them |
ich-m10 |
Bioanalytical concentration measurement (PK, TK, BE) | Yes, and they differ by modality |
usp-1220 |
Compendial procedure lifecycle, three stages | Paywalled |
usp-1225 / usp-1226 |
Validation / verification of compendial procedures | Paywalled |
clsi |
Clinical laboratory measurement procedures (EP series) | Paywalled |
iso-17025 |
Lab-developed and modified methods under accreditation | No — "to the extent necessary" |
Q2(R2) replaced Q2(R1) in November 2023 and restructured the characteristics. Range is now the parent characteristic (section 3.2), containing response (linearity) and validation of lower range limits (DL/QL). Accuracy and precision are section 3.3 and may be evaluated in combination against a single criterion. Robustness is treated as a development activity and cross-refers to ICH Q14. Multivariate procedures are addressed explicitly (2.5 and 3.2.2.3), and Annex 2 adds worked examples for techniques Q2(R1) never covered — quantitative ¹H-NMR, NIR, quantitative LC/MS, qPCR, biological assays, and particle size. A Q2(R1)-shaped protocol — a flat list of linearity, range, accuracy, precision, specificity, LOD, LOQ, robustness — is out of date. Note also the error correction dated 30 November 2023 to Table 5 and Tables 6–11.
Scripts
cd skills/analytical-method-validation/scripts
| Script | Question answered |
|---|---|
plan_validation.py |
Which framework, which characteristics, what study layout, what protocol? |
check_response.py |
Does the calibration model actually hold across the range? |
check_accuracy_precision.py |
What is the recovery, and how much of the variability is between days? |
check_detection_limits.py |
What are DL and QL by each allowed approach, and do they serve the reporting threshold? |
check_bioanalytical_run.py |
Which supported ICH M10 numerical checks raise findings? |
…
FAQ
What are 'frameworks'?
These are sets of rules and guidelines (like ICH Q2(R2), USP <1225>) that define how a testing method should be validated. Each has specific requirements.
What does it mean for a method to be 'fit for its intended purpose'?
It means the testing method is reliable and accurate enough to be used for what it was created for, such as measuring the amount of a substance or verifying its identity.
Does this tool replace a scientist or analyst?
No. It assists with planning and data analysis, but the final decision on method validation always rests with a qualified professional.
Details
Original description by the author
Plans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intende
Popularity
- GitHub stars
- 51k
- Ranking position
- #1831
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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