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Clinical Trials

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
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Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.

Clinical Trials: Overview

Clinical Trials: Overview

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...

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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...

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...

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Related Experiment Video

Updated: Jun 14, 2026

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

Published on: September 20, 2019

Adding experimental treatment arms to multi-arm multi-stage platform trials in progress.

Thomas Burnett¹, Franz König², Thomas Jaki^3,4

¹Department of Mathematical Sciences, University of Bath, Bath, UK.

Statistics in Medicine

|June 9, 2024

Summary

Multi-arm multi-stage (MAMS) platform trials can add new treatments during studies. This method ensures statistical validity and error rate control when incorporating new hypotheses into ongoing trials.

Keywords:

adaptive designs conditional error design modification multi‐arm multi‐stage

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Area of Science:

Clinical Trials Methodology
Statistical Inference
Biostatistics

Background:

Multi-arm multi-stage (MAMS) platform trials offer efficient comparison of multiple treatments against a common control.
These designs inherently allow for multiplicity adjustments, crucial for maintaining statistical integrity, especially with varying doses or administration routes.
Adding new treatments to ongoing trials is desirable for practical and statistical efficiency.

Purpose of the Study:

To demonstrate a method for adding new treatment arms to ongoing MAMS platform trials.
To ensure the family-wise error rate (FWER) remains strongly controlled despite design modifications.
To adapt existing statistical procedures for incorporating unplanned hypotheses.

Main Methods:

Utilizing the conditional error approach to integrate new hypotheses into FWER-controlled testing procedures.
Applying this framework to add treatments to a MAMS trial that is already in progress.
Employing simulations to evaluate the characteristics of the proposed procedures.

Main Results:

The conditional error approach provides a valid framework for adding hypotheses to FWER-controlled procedures.
This method successfully allows for the incorporation of new treatments into ongoing MAMS trials.
Simulations show the feasibility and characteristics of such modified trial designs.

Conclusions:

The conditional error approach is a robust statistical tool for enhancing the flexibility of MAMS platform trials.
It enables the seamless addition of new treatments without compromising the overall statistical validity.
This methodology supports adaptive clinical trial designs, improving efficiency and responsiveness.