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Related Concept Videos

Clinical Trials01:16

Clinical Trials

10.1K
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...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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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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Dosage Regimens: Designs and Approaches01:28

Dosage Regimens: Designs and Approaches

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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...
210
Bioavailability Study Design: Healthy Subjects Versus Patients01:15

Bioavailability Study Design: Healthy Subjects Versus Patients

104
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,...
104
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

114
It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...
114
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

626
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...
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Related Experiment Video

Updated: Jan 1, 2026

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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Optimising medication data collection in a large-scale clinical trial.

Jessica E Lockery1, Jason Rigby1, Taya A Collyer1

  • 1Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Plos One
|December 28, 2019
PubMed
Summary

The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a cost-effective framework for collecting structured medication data in community research. This method significantly reduces costs compared to traditional free-text data collection, enabling large-scale analysis.

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Area of Science:

  • Clinical research methodology
  • Health informatics
  • Pharmacovigilance

Background:

  • Medication data in community research is often unstructured free-text, making large-scale coding expensive.
  • The ASPirin in Reducing Events in the Elderly (ASPREE) study aimed to address this challenge for 19,114 participants.
  • Efficient collection of structured medication data is crucial for clinical care and research.

Purpose of the Study:

  • To evaluate the cost-effectiveness of a novel two-pronged framework for collecting structured medication data in community-based research.
  • To compare the ASPREE framework with traditional free-text data collection methods.
  • To determine the feasibility of large-scale, cost-effective medication data collection and coding.

Main Methods:

  • The ASPREE framework utilized a type-to-search box with automated coding and linked free-text entry.
  • This was compared against the traditional method of free-text only collection and post hoc coding.
  • Medications were classified by Anatomical Therapeutic Chemical (ATC) group, and collection costs were analyzed.

Main Results:

  • Over 122,910 structured medication reports were collected via the type-to-search box, with 5,983 in free-text.
  • Free-text entries identified 211 unique medications not in the automated system, often due to spelling errors.
  • The ASPREE method cost approximately $0.03 per medication, significantly less than the traditional method's $0.20 per medication.

Conclusions:

  • The ASPREE two-pronged framework offers a cost-effective alternative to traditional free-text data collection in community research.
  • Despite higher initial setup costs, the long-term economic benefits and enhanced scientific potential justify its implementation.
  • This structured data collection approach facilitates greater analysis and discovery in large-scale studies.