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

Crossover Experiments01:16

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.
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

Designing a dosage regimen, which refers to the manner of drug administration, is a complex process involving the selection of drug dose, route, and frequency. This process is underpinned by pharmacokinetic parameters derived from tests and population averages. These parameters are then tailored to patient-specific variables such as diagnosis, demographics, and allergy status. Once therapy commences, therapeutic response monitoring is critical and achieved through clinical and physical...
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
Bioavailability Study Design: Healthy Subjects Versus Patients01:15

Bioavailability Study Design: Healthy Subjects Versus Patients

Bioavailability studies are essential for evaluating a drug's therapeutic efficacy and understanding its absorption patterns under various physiological conditions. Conducting such studies on target patient populations provides more relevant data by simulating real-world disease states. However, practical challenges often necessitate the use of young, healthy adult volunteers as study subjects.Patients may exhibit altered drug absorption patterns due to the effects of the disease itself,...

You might also read

Related Articles

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

Sort by
Same author

Blinded sample size re-estimation in a crossover study.

Journal of biopharmaceutical statistics·2025
Same author

Statistical considerations in model-based dose finding for binary responses under model uncertainty.

Statistics in medicine·2024
Same author

Self-administered versus clinician-performed BinaxNOW COVID rapid test: a comparison of accuracy.

Microbiology spectrum·2024
Same author

Comparability of Elezanumab Safety, Tolerability, and Pharmacokinetics in Healthy Japanese, Chinese, and White Participants.

Clinical pharmacology in drug development·2024
Same author

Accuracy of Expired BinaxNOW Rapid Antigen Tests.

Microbiology spectrum·2023
Same author

CA-125 KELIM as a Potential Complementary Tool for Predicting Veliparib Benefit: An Exploratory Analysis From the VELIA/GOG-3005 Study.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2022

Related Experiment Video

Updated: May 10, 2026

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition
06:20

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Published on: March 11, 2021

Crossover versus parallel designs: dose-escalation design comparisons for first-in-human studies.

Zhiwu Yan1, Balakrishna Hosmane, Charles Locke

  • 1Allergan, Inc., Irvine, CA 92612, USA. yan_zhiwu@allergan.com

Journal of Biopharmaceutical Statistics
|June 22, 2013
PubMed
Summary

This study introduces efficient crossover designs for early phase clinical trials, balancing patient safety and statistical power. These designs offer advantages over traditional parallel group methods, especially when including baseline data.

More Related Videos

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

Use of a Linear Accelerator for Conducting In Vitro Radiobiology Experiments
06:08

Use of a Linear Accelerator for Conducting In Vitro Radiobiology Experiments

Published on: May 26, 2019

Related Experiment Videos

Last Updated: May 10, 2026

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition
06:20

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition

Published on: March 11, 2021

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

Use of a Linear Accelerator for Conducting In Vitro Radiobiology Experiments
06:08

Use of a Linear Accelerator for Conducting In Vitro Radiobiology Experiments

Published on: May 26, 2019

Area of Science:

  • Clinical trial design
  • Statistical methodology
  • Pharmacometrics

Background:

  • Rising-dose studies are crucial for first-in-human (FIH) trials.
  • Assessing both safety and statistical efficiency is paramount in early phase drug development.

Purpose of the Study:

  • To identify and evaluate efficient crossover designs for FIH studies.
  • To compare the statistical efficiency of a specific three-period, two-panel crossover design against parallel designs.
  • To assess the impact of baseline measurements as covariates in statistical analyses.

Main Methods:

  • Investigated a class of crossover designs balancing safety and efficiency.
  • Performed A-efficiency comparisons for a three-period, two-panel design.
  • Evaluated the influence of baseline covariate inclusion in statistical models.

Main Results:

  • A specific class of crossover designs demonstrates strong statistical efficiency and subject safety.
  • The three-period, two-panel crossover design shows favorable A-efficiency compared to parallel designs.
  • Including baseline measurements as a covariate can enhance the statistical analysis for both crossover and parallel designs.

Conclusions:

  • Identified promising crossover designs for optimizing FIH studies.
  • The proposed crossover design offers a statistically efficient alternative to parallel designs.
  • Baseline covariate adjustment is a valuable strategy for improving analytical precision in early phase trials.