Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Data Validation

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:

Development of Analytical Methods

Development of Analytical Methods

An analytical methodology can be divided into four sequential steps: technique, method, procedure, and protocol. A technique is a scientific principle that rationalizes a specific phenomenon through chemical measurements. Adapting a technique for analyzing a sample of interest is termed a method. The procedure outlines the directions for performing the analysis via an analytical method. The protocol is the detailed guidelines on the procedure, which should be strictly followed to obtain the...

Bioequivalence Data: Statistical Interpretation

Bioequivalence Data: Statistical Interpretation

The statistical interpretation of bioequivalence data is a significant aspect of pharmaceutical research. Bioequivalence refers to the absence of any significant difference in the rate and extent to which the active ingredient in pharmaceutical products becomes available at the site of drug action when administered at the same molar dose under similar conditions. This helps determine if different drug products have similar absorption rates, ensuring their interchangeability.Statistical...

Comparing Experimental Results: Student's t-Test

Comparing Experimental Results: Student's t-Test

The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...

Therapeutic Drug Monitoring: Drug Analysis Methods

Therapeutic Drug Monitoring: Drug Analysis Methods

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood or body tissues to tailor drug therapy effectively. This monitoring is critical for managing drugs with narrow therapeutic indices like digoxin and phenytoin, ensuring they are both safe and effective. For instance, monitoring theophylline levels in asthma patients involves precision and sensitivity to adjust doses according to individual responses to therapy, ensuring efficacy and...

Measurement of Bioavailability: Pharmacokinetic Methods

Measurement of Bioavailability: Pharmacokinetic Methods

Pharmacokinetics is a vital branch of pharmacology that examines how drugs are absorbed, distributed, metabolized, and excreted by the body. Two key methodologies in pharmacokinetics are plasma drug concentration studies and urinary drug excretion analyses, both of which provide critical insights into a drug's therapeutic efficacy and bioavailability.Plasma Drug Concentration-Time StudiesPlasma drug concentration-time studies involve analyzing blood samples at specific intervals to quantify...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same authorSame journal

Special issue of nonclinical statistics in regulatory applications guest editors' notes.

Journal of biopharmaceutical statistics·2026

Same author

Statistical approaches for shelf-life determination of a drug product.

Journal of biopharmaceutical statistics·2026

Same author

Parallelism of four-parameter logistic bioassay models: equivalence testing for parameter differences.

Journal of biopharmaceutical statistics·2026

Same author

A survey of parallelism testing methods for bioassays.

Journal of biopharmaceutical statistics·2026

Same author

A multivariate equivalence test based on Mahalanobis distance with a data-driven margin.

Journal of biopharmaceutical statistics·2026

Same author

Sample size for confidence intervals for percentiles and application to cut-point determination.

Journal of biopharmaceutical statistics·2026

Search research articles

Related Experiment Video

Updated: Jul 1, 2026

A Cost Effective and Adaptable Scratch Migration Assay

A Cost Effective and Adaptable Scratch Migration Assay

Published on: June 30, 2020

Statistical assessment of analytical method transfer.

Jinglin Zhong¹, Kathy Lee, Yi Tsong

¹Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland 20993, USA.

Journal of Biopharmaceutical Statistics

|September 11, 2008

Summary

This summary is machine-generated.

Analytical method transfer requires demonstrating equivalence between labs. This study proposes and compares statistical methods, like tolerance intervals, for assessing individual sample equivalence, offering a scientifically sound alternative to mean equivalence.

More Related Videos

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species

Published on: May 7, 2018

Related Experiment Videos

Last Updated: Jul 1, 2026

A Cost Effective and Adaptable Scratch Migration Assay

A Cost Effective and Adaptable Scratch Migration Assay

Published on: June 30, 2020

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species

Quantitative and Qualitative Method for Sphingomyelin by LC-MS Using Two Stable Isotopically Labeled Sphingomyelin Species

Published on: May 7, 2018

Area of Science:

Analytical Chemistry
Biostatistics
Pharmaceutical Analysis

Background:

Analytical method transfer is crucial for method maintenance and reliable results.
Current practices often rely on mean equivalence, which may not be suitable for all assays.

Purpose of the Study:

To explore and compare statistical approaches for demonstrating individual sample equivalence in analytical method transfer.
To propose a tolerance interval approach as a robust alternative to mean equivalence.

Main Methods:

Discussion of statistical methods: limit of agreement, total deviation index, and tolerance intervals.
Proposal of a tolerance interval approach equivalent to two one-sided hypothesis testing.
Comparison of statistical properties of different equivalence approaches.

Main Results:

Individual sample equivalence offers a more scientifically sound assessment for certain assays.
The tolerance interval approach provides a robust framework for evaluating individual equivalence.
Comparisons highlight the statistical properties and practical implications of each method.

Conclusions:

Individual sample equivalence is a valuable consideration in analytical method transfer.
The tolerance interval approach is a recommended statistical strategy for demonstrating individual equivalence.
Adopting these methods can enhance the reliability and scientific rigor of analytical method transfers.