Related Experiment Video
Updated: Jan 19, 2026

Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
Published on: August 4, 2023
Variations in internal standard response: some thoughts and real-life cases
1Trials & Vigilance Inspection Department, French National Agency for Medicines & Health Products Safety (ANSM), Saint-Denis, France.
Monitoring internal standard response is crucial for reliable bioanalytical methods. Objective criteria handle isolated sample variations, while trends may necessitate expert judgment and run rejection.
Area of Science:
- Analytical Chemistry
- Bioanalytical Science
Background:
- Internal standards are vital for the reliability of chromatographic bioanalytical methods.
- Adequate monitoring of the internal standard's response is a prerequisite for its effective use.
Purpose of the Study:
- To differentiate between isolated sample variations and complex deviations in internal standard response.
- To establish criteria for managing deviations and ensuring data integrity in bioanalytical assays.
Main Methods:
- Analysis of internal standard response variations within analytical runs.
- Development of objective criteria for sample re-analysis.
- Evaluation of scientific judgment for complex deviations like trends and systematic differences.
Main Results:
- Isolated variations can be managed with objective criteria leading to sample re-analysis.
- Trends or systematic differences require scientific judgment and may lead to analytical run rejection.
- Effective monitoring protocols are key to validating bioanalytical data.
Conclusions:
- Proper monitoring and management of internal standard response are essential for reliable bioanalytical results.
- A clear distinction between isolated variations and systematic deviations guides appropriate corrective actions.
- Ensuring the integrity of bioanalytical data relies on robust internal standard performance evaluation.
More Related Videos
08:33A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
Published on: September 4, 2019
07:32Use of Galvanic Skin Responses, Salivary Biomarkers, and Self-reports to Assess Undergraduate Student Performance During a Laboratory Exam Activity
Published on: February 10, 2016
Related Concept Videos
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Case Studies
Systematic Error: Methodological and Sampling Errors
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Surveys
Regression Toward the Mean
Naturalistic Observations