The purpose of the SDTM Trial Design Model is to represent a brief, clear description of the overall plan and design of a nonclinical study or clinical trial. Guidance in this section is applicable only to TIG Nonclinical and Product Impact on Individual Health use cases. In this section, the term "trial" is equivalent to "study" in the nonclinical contextstudies of tobacco products. Trial Design datasets contain study-level, rather than subject-level, information. Implementation of The Trial Design datasets requires the explicit statement of certain decision rules that may not be addressed or may not be as explicit in the textual description of a study plan such as an approved study protocol.
The Trial Design Model provides a standardized way to describe those aspects of the planned conduct of a clinical trial shown in the study design diagrams of these examples. The standard Trial Design Datasets will allow reviewers to:
- Clearly and quickly grasp the design of a clinical trial
- Compare the designs of different trials
- Search a data warehouse for clinical trials with certain features
- Compare planned and actual treatments and visits for subjects in a clinical trial
Modeling a clinical trial in this standardized way requires the explicit statement of certain decision rules that may not be addressed or may be vague or ambiguous in the usual prose protocol document. Prospective modeling of the design of a clinical trial should lead to a clearer, better protocol. Retrospective modeling of the design of a clinical trial should ensure a clear description of how the trial protocol was interpreted by the sponsor
based on the Trial Design Model describe the planned design of the study and provide the representation of the study product in its most granular components, as well as the representation of all sequences of these components as described in the protocol.
Guidance in this section is applicable to TIG Nonclinical and Product Impact on Individual Health use cases only.In this section, the term "trial" is equivalent to "study". The TIG guides implementation of the Trial Design datasets described in the following table for use cases as indicated.The TIG guides implementation for the following Trial Design datasets:
| Metadataspec |
|---|
Purpose | Description | Use Case(s) |
|---|
| 1 | Trial Arms (TA) | Represents each planned arm in the study including the sequences of elements in each epoch for each arm |
, and thus describes the complete sequence of elements in each arm.. The TA and TE datasets are interrelated and provide the building blocks for subject-level information. | - Nonclinical
- Product Impact on Individual Health
| | 2 | Trial Elements (TE) | Represents the elements used in the |
trial.study including unique codes for each element, element descriptions, and the rules for starting and ending an element. The TA and TE datasets are interrelated and provide the building blocks for subject-level information. | - Nonclinical
- Product Impact on Individual Health
| | 3 | Trial Visits (TV) |
Clinical Only schedule | order and number of visits |
.| in the study within each arm | - Product Impact on Individual Health
| | 4 | Trial Inclusion/Exclusion (TI) |
Clinical Only | criteria used to screen subjects.inclusion and exclusion criteria for the study
| - Product Impact on Individual Health
| | 5 | Trial Summary (TS) | Represents |
Lists key facts (parameters) about the trial that are likely to appear in a registry of clinical trialskey summary characteristics for the study | - Nonclinical
- Product Impact on Individual Health
| | 6 | Trial Sets (TX) |
Nonclinical | add text hereRepresents planned sets of subjects (e.g., in vivo studies) or sources of information (e.g., in vitro studies) that result from combinations of experimental factors defined for the study | |
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