Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Preclinical Development: Overview01:28

Preclinical Development: Overview

4.2K
Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
4.2K
Drug Discovery: Overview01:26

Drug Discovery: Overview

7.5K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.5K
Pharmacovigilance01:19

Pharmacovigilance

773
Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
773
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

235
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
235
Clinical Trials: Overview01:11

Clinical Trials: Overview

2.8K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
2.8K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

58
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
58

You might also read

Related Articles

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

Sort by
Same author

Probability of success and group sequential designs.

Pharmaceutical statistics·2023
Same author

On implementing Jeffreys' substitution likelihood for Bayesian inference concerning the medians of unknown distributions.

Pharmaceutical statistics·2022
Same author

Optimising the trade-off between type I and II error rates in the Bayesian context.

Pharmaceutical statistics·2021
Same author

Response-adaptive clinical trials: case studies in the medical literature.

Pharmaceutical statistics·2016
Same author

Simulation-based sample-sizing and power calculations in logistic regression with partial prior information.

Pharmaceutical statistics·2016
Same author

Idle thoughts of a 'well-calibrated' Bayesian in clinical drug development.

Pharmaceutical statistics·2016

Related Experiment Video

Updated: Jun 6, 2025

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis
07:45

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

325

Pre-Posterior Distributions in Drug Development and Their Properties.

Andrew P Grieve1

  • 1Fairholme, Upper Street, Tilmanstone, Kent, UK.

Pharmaceutical Statistics
|November 26, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces pre-posterior distributions for treatment success or failure. These distributions aid in planning studies to effectively distinguish between effective and ineffective treatments.

Keywords:
Bayesian inferenceconditional probability of successgroup sequential designpre‐posterior distribution of failurepre‐posterior distribution of successprobability of successsub‐probability distributions

More Related Videos

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.6K
Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.7K

Related Experiment Videos

Last Updated: Jun 6, 2025

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis
07:45

Author Spotlight: Standardizing Mouse In Vivo PET Imaging with Body Conforming Molds and Automated Analysis

Published on: October 25, 2024

325
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

9.6K
Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis
07:48

Tracking Drug-induced Changes in Receptor Post-internalization Trafficking by Colocalizational Analysis

Published on: July 3, 2015

8.7K

Area of Science:

  • Statistics
  • Clinical Trial Design

Background:

  • Pre-posterior distributions represent beliefs about treatment effects before a study concludes.
  • These distributions are crucial for interpreting study outcomes (success or failure).

Purpose of the Study:

  • To demonstrate the utility of pre-posterior distributions in study planning.
  • To assess a study's ability to discriminate between effective and ineffective treatments.

Main Methods:

  • Utilizing pre-posterior distributions to evaluate study design.
  • Employing simulations when asymptotic normality assumptions are not met.
  • Linking pre-posterior distributions to the probability of success (PoS).

Main Results:

  • Pre-posterior distributions can be determined via simulation for complex scenarios.
  • A clear link is established between pre-posterior distributions and the probability of success.
  • The method is applicable to both frequentist and Bayesian analyses.

Conclusions:

  • Pre-posterior distributions are valuable tools for planning clinical studies.
  • These distributions enhance the ability to design studies that effectively discriminate treatment effects.
  • The approach is flexible, accommodating various analytical frameworks.