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

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

412
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...
412
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

405
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...
405
Methods of Medium Optimization01:28

Methods of Medium Optimization

68
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
68
Experimental Designs01:16

Experimental Designs

11.3K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
11.3K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

622
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,...
622
Study Design in Statistics01:15

Study Design in Statistics

7.4K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
7.4K

You might also read

Related Articles

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

Sort by
Same author

Optimization of poly (3-hydroxybutyrate) production by recombinant <i>Escherichia coli</i> using an experimental screening design.

Preparative biochemistry & biotechnology·2026
Same author

Comparative Evaluation of Postoperative Pain and Clinical Success Following Rotary and Reciprocating Instrumentation in Teeth with Symptomatic Irreversible Pulpitis: A Randomized Clinical Trial.

Journal of endodontics·2026
Same author

Novel resistance loci against Pyrenophora teres f. teres map to chromosomes 3H and 6H of barley.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik·2025
Same author

Marine cosmetics and the blue bioeconomy: From sourcing to success stories.

iScience·2024
Same author

Algae in Biomedicine.

Advances in experimental medicine and biology·2024
Same author

Holistic biorefinery approach for biogas and hydrogen production: Integration of anaerobic digestion with hydrothermal carbonization and steam gasification.

Environmental research·2024

Related Experiment Video

Updated: Apr 21, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

821

Experimental design methods for bioengineering applications.

Tuğba Keskin Gündoğdu1, İrem Deniz1, Gülizar Çalışkan1

  • 1a Department of Bioengineering , Ege University , Bornova-Izmir , Turkey.

Critical Reviews in Biotechnology
|November 7, 2014
PubMed
Summary

This review explores experimental design methods for optimizing bioengineering processes. It details techniques like full factorial and Taguchi designs for factor analysis and process improvement.

Keywords:
BioprocessBox–Behnken designPlacket–Burrman designTaguchi designcentral composite designfull factorial design

More Related Videos

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

16.3K
Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
09:28

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

8.0K

Related Experiment Videos

Last Updated: Apr 21, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

821
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

16.3K
Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
09:28

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

8.0K

Area of Science:

  • Bioengineering
  • Process Optimization
  • Experimental Design

Background:

  • Bioengineering processes are influenced by numerous factors.
  • Effective experimental design is crucial for understanding these factors and optimizing outcomes.
  • Process analysis requires careful selection of factors to achieve desired responses.

Purpose of the Study:

  • To review and summarize various experimental design methods applicable to bioengineering.
  • To analyze the application of these designs in studying different bioengineering processes.
  • To provide a foundation for selecting appropriate experimental designs for bioprocess optimization.

Main Methods:

  • The review covers full factorial design, fractional factorial design, Plackett-Burman design, Taguchi design, Box-Behnken design, and central composite design.
  • Each method is briefly introduced.
  • Applications of these designs in bioengineering are analyzed.

Main Results:

  • Experimental designs offer systematic approaches to identify key factors influencing bioengineering processes.
  • Different designs provide varying levels of efficiency and information for factor screening and optimization.
  • The selection of an appropriate design depends on the specific bioengineering challenge.

Conclusions:

  • Experimental design is a powerful tool for analyzing and optimizing bioengineering processes.
  • Understanding and applying methods like factorial, Plackett-Burman, Taguchi, and response surface designs are essential.
  • This review serves as a guide for researchers in selecting and applying suitable experimental designs.