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Sample Size Calculation01:19

Sample Size Calculation

6.7K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
6.7K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

6.7K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
6.7K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

4.1K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.1K
Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

291
Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
291
Factors Affecting Drug Response: Overview01:21

Factors Affecting Drug Response: Overview

3.0K
When it comes to infants and young children, they are typically administered smaller doses of medication in comparison to adults. This is primarily because their organ functions still need to fully develop, meaning their bodies are not as efficient at metabolizing or eliminating drugs. Additionally, their blood-brain barrier is more permeable than in adults. As a result, high concentrations of drugs can easily penetrate the central nervous system (CNS), potentially leading to neurological...
3.0K
Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

648
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
648

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Related Experiment Video

Updated: Jan 30, 2026

A New Portable In Vitro Exposure Cassette for Aerosol Sampling
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A New Portable In Vitro Exposure Cassette for Aerosol Sampling

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Power Determination During Drug Development: Is Optimizing the Sample Size Based on Exposure-Response Analyses

Aksana K Jones1, Ahmed Hamed Salem1,2, Kevin J Freise1

  • 1Abbvie, Inc., North Chicago, Illinois, USA.

CPT: Pharmacometrics & Systems Pharmacology
|January 20, 2019
PubMed
Summary

Model-based drug development (MBDD) can be complex. This tutorial presents a simple exposure-response analysis to improve power and reduce sample size in dose-ranging studies.

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Area of Science:

  • Pharmacometrics and Quantitative Pharmacology
  • Clinical Trial Design and Optimization
  • Drug Development Sciences

Background:

  • Model-based drug development (MBDD) enhances clinical trial efficiency but faces complexity challenges, especially in early development.
  • Conventional power calculations for dose-ranging studies may not fully leverage available data or optimize study design.
  • There is a need for accessible and generalizable methods to improve the statistical power and sample efficiency of early-phase clinical trials.

Purpose of the Study:

  • To present a simple and generalizable exposure-response analysis approach for determining statistical power in dose-ranging studies.
  • To demonstrate how this methodology can enhance power and reduce sample size compared to traditional methods.
  • To provide a tutorial for applying this exposure-response powering methodology in early clinical development.

Main Methods:

  • Development of a straightforward exposure-response modeling framework applicable to dose-ranging studies.
  • Application of the exposure-response powering methodology to calculate required sample sizes and statistical power.
  • Comparative analysis of the proposed method against conventional power calculation techniques.

Main Results:

  • The exposure-response powering methodology was shown to achieve higher statistical power for dose-ranging studies.
  • Utilization of this approach can lead to significant reductions in required sample size.
  • Specific scenarios were identified where the benefits of the exposure-response method are most pronounced.

Conclusions:

  • A simple exposure-response analysis provides a powerful and sample-efficient approach for designing dose-ranging studies.
  • This methodology offers a practical alternative to conventional power calculations, particularly in early drug development.
  • Implementing exposure-response powering can optimize resource allocation and accelerate drug development timelines.