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

Randomized Experiments01:13

Randomized Experiments

9.1K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
9.1K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

500
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,...
500
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

300
Body: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...
300
Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

333
Body: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...
333
Data Collection by Experiments01:13

Data Collection by Experiments

27.7K
Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
27.7K
Clinical Trials01:16

Clinical Trials

10.9K
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.
There are four phases in a clinical trial. A phase one...
10.9K

You might also read

Related Articles

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

Sort by
Same author

APPRAISE: A Tool for Appraising Potential for Bias in Real-World Evidence Studies on Medication Effectiveness or Safety.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2025
Same author

Incidence of Conjunctivitis and Keratitis Among Individuals with Moderate-to-Severe Atopic Dermatitis Treated with Dupilumab in the United States: a Cohort Study in Routine Care Based on Healthcare Claims.

Dermatology and therapy·2025
Same author

Development and Validation of Claims-Based Algorithms for Conjunctivitis and Keratitis.

Pharmacoepidemiology and drug safety·2024
Same author

Efficacy Versus Effectiveness: The HORIZON-Pivotal Fracture Trial and Its Emulation in Claims Data.

Arthritis & rheumatology (Hoboken, N.J.)·2024
Same author

Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials.

JAMA·2023
Same author

Development and Validation of Algorithms to Estimate Live Birth Gestational Age in Medicaid Analytic eXtract Data.

Epidemiology (Cambridge, Mass.)·2022

Related Experiment Video

Updated: Feb 24, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K

When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?

Jessica M Franklin1, Sebastian Schneeweiss1

  • 1Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.

Clinical Pharmacology and Therapeutics
|August 25, 2017
PubMed
Summary
This summary is machine-generated.

Real world data (RWD) can substitute for randomized controlled trials (RCTs) in drug evaluation. Understanding when to use RWD and how to conduct valid analyses is key for regulatory decision-making.

More Related Videos

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.3K
Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health
06:13

Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health

Published on: December 1, 2023

1.8K

Related Experiment Videos

Last Updated: Feb 24, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

15.4K
Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

1.3K
Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health
06:13

Author Spotlight: Exploring the Impact of Reduced Resistance Exercise Volume on Metabolic Health

Published on: December 1, 2023

1.8K

Area of Science:

  • Pharmacovigilance and Drug Development
  • Health Services Research
  • Biostatistics

Background:

  • Randomized controlled trials (RCTs) are the gold standard for drug evaluation but face challenges like cost, duration, and generalizability.
  • Real-world data (RWD) from sources like registries and healthcare databases offer potential alternatives to RCTs.
  • Concerns regarding the validity of RWD studies have limited their impact in regulatory decision-making.

Purpose of the Study:

  • To explore the conditions under which real-world data (RWD) analyses can substitute for randomized controlled trials (RCTs) in regulatory decision-making.
  • To identify key factors determining the success or failure of RWD studies in yielding results comparable to RCTs.
  • To provide guidance on the 'when' and 'how' of implementing valid RWD analyses for regulatory purposes.

Main Methods:

  • Analysis of factors influencing the validity of RWD studies compared to RCTs.
  • Identification of criteria for determining when drug effects can be studied without randomization.
  • Examination of common pitfalls and best practices in conducting RWD analyses.

Main Results:

  • The applicability of RWD in place of RCTs is primarily determined by external factors not controlled by researchers.
  • Successful RWD analyses depend on avoiding specific, known methodological errors.
  • Understanding these 'when' and 'how' aspects is crucial for leveraging RWD effectively.

Conclusions:

  • Greater reliance on RWD for regulatory decisions necessitates a clear understanding of its appropriate use.
  • Methodological rigor in RWD studies is essential to ensure their validity and comparability to RCTs.
  • Addressing the 'when' and 'how' of RWD analysis will enhance its role in drug safety and effectiveness evaluation.