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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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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

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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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Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

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The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
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Bioavailability Study Design: Healthy Subjects Versus Patients01:15

Bioavailability Study Design: Healthy Subjects Versus Patients

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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,...
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Clinically Relevant Drug Product Specifications: Methods of Establishment01:29

Clinically Relevant Drug Product Specifications: Methods of Establishment

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Product specifications define the acceptable quality of a pharmaceutical product by ensuring identity, purity, potency, and strength. These specifications serve as benchmarks during development, manufacturing, and post-approval quality control. Clinically relevant specifications are particularly important because they directly relate to a drug's safety and efficacy in clinical use.Dissolution studies are critical biopharmaceutic tools that link in vitro behavior to in vivo performance. They...
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Crossover Experiments01:16

Crossover Experiments

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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.
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Related Experiment Video

Updated: Jan 17, 2026

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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Clinical Trial Schedule of Activities Specification Using Fast Healthcare Interoperability Resources Definitional

Andrew Richardson1, Patrick Genyn2

  • 1fhir4pharma, Hungerford, Berkshire, United Kingdom.

JMIR Medical Informatics
|September 16, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a graph-based approach to represent complex clinical study schedules of activities (SoAs) using Fast Healthcare Interoperability Resources (FHIR). The method accurately captures intricate study designs, improving data quality and interoperability for digital health records.

Keywords:
FHIRFast Healthcare Interoperability ResourcesHL7Health Level 7clinical trialselectronic health recordsgraph methodsinteroperabilityschedule of activities

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Area of Science:

  • Clinical informatics
  • Biomedical data standards
  • Computational biology

Background:

  • Schedules of Activities (SoAs) are crucial for clinical research but traditional tabular formats struggle with complex designs.
  • Existing Fast Healthcare Interoperability Resources (FHIR) approaches for SoAs are limited, especially for oncology studies with conditional logic or repeat cycles.
  • There's a need for digital SoA representations that capture intricate study designs beyond simple linear schedules.

Purpose of the Study:

  • To develop methods for representing complex SoAs, including multiple paths and conditional logic, within a unified model.
  • To create a human-readable syntax for study specifications and map these to FHIR resources.
  • To enable bidirectional conversion between graph-based SoA models and FHIR representations for interoperability.

Main Methods:

  • SoAs were modeled using directed graphs with nodes for activities and edges for transitions, incorporating attributes for timing and conditions.
  • Graph models were translated into FHIR PlanDefinitions and related resources, with custom extensions (soaTimePoint, soaTransition) for graph-specific data.
  • Proof-of-concept models were implemented and validated using Python, NetworkX, pandas, FHIR Shorthand, and FHIR servers.

Main Results:

  • The graph-based approach successfully modeled complex SoAs, including multiple paths, unscheduled events, and conditional rules.
  • FHIR PlanDefinition extensions enabled comprehensive digital representation of SoA graphs, surpassing tabular limitations.
  • Bidirectional conversion between graph models and FHIR resources confirmed data fidelity, with the approach also identifying protocol inconsistencies.

Conclusions:

  • Graph-based modeling with FHIR PlanDefinition extensions provides an accurate and comprehensive method for representing complex clinical SoAs.
  • This approach enhances interoperability, reduces manual interpretation, and supports automated integration with electronic health records.
  • The methods offer a precise and extensible solution for digital protocol implementation, though further tooling is needed for full operational deployment.