DOMAIN 1: SCIENTIFIC CONCEPTS AND RESEARCH DESIGN
Encompasses knowledge of scientific concepts related to the design and analysis of clinical trials
Apply principles of biomedical science to investigational product discovery and development and health-related behavioral interventions
A1. Recognize the need to apply scientific principles to discovery and development of biomedical investigational products and health-related behavioral interventions
A2. Explain the basic scientific principles that should be applied during development of biomedical investigational products and health-related behavioral interventions
Example: When reviewing a clinical research protocol, researcher describes the objective and scientific techniques used to design and implement biomedical research.
B1. Apply scientific principles when implementing a clinical or behavioral study
B2. Implement data collection according to scientific principles and based on protocol design
Example: When given a clinical research protocol, researcher differentiates what principles could affect how the data should be collected and implement best practices accordingly.
C1. Plan biomedical research according to scientific principles
C2. Develop a data management plan according to scientific principles
Example: Given a clinical research protocol and data collected, the researcher evaluates the findings to assess results via a scientific framework.
Identify scientific questions that are potentially testable clinical research hypotheses
A1. Articulate the purpose of the study
A2. Describe the importance of the study
Example: Identifies the following elements in selected study protocols: Study title, Key purpose of the study, Why this study is important to be done, Who the specific population for the study is
B1. Identify the research hypothesis in a study protocol
B2. Identify endpoints (primary and secondary) that will be used in data analyses to measure outcomes
Example: When given a study protocol, describes and classifies the objectives and associated safety and efficacy endpoints that will be used to test the hypothesis and identify assessments (clinical, social/ behavioral, or economic) that will be used to measure endpoints.
C1. Develop protocol or source document checklist language that identifies the scientific questions (hypotheses), primary objectives, secondary objectives, and associated endpoints
C2. Align parameters for collecting data on endpoints with objectives
Example: Develops presentations to educate others on the scientific feasibility and conduct of the study to ensure quality collection of endpoints for hypothesis testing.
Identify the elements and explain the principles and processes of designing a clinical study
A1. Identify the key elements of a clinical study protocol
A2. Describe the general process of clinical study protocol development
A3. Recognize the basic differences between the various types of clinical studies
Example: When given a clinical study protocol, identifies the inclusion and exclusion criteria for a set of mock participants.
B1. Review a clinical study protocol to ensure all needed elements are included
Example: When given a clinical study protocol, identifies missing, incomplete or inappropriate features.
C1. Evaluate the clinical study design and make adjustments to the processes as needed
C2. Develop protocols as applicable to the therapeutic area
C3. Evaluate strengths and weakness of study designs and explain these to others
Example: When given a clinical study protocol that has misalignment between the measures and objectives, researcher appropriately modifies the protocol.
Critically analyze clinical study results
A1. Identify the study results
A2. Describe the relevance of the results to the research question
Example: When given study reports, paraphrases and summarizes the study results.
B1. Compare and assess the level of quality of results associated with study reports and publications
B2. Understand descriptive and exploratory data analysis
Example: When given two publications researching the same topic, researcher compares and contrasts what could have affected how the data from the two could be interpreted.
C1. Assess the potential for application of findings
C2. Identify trends and anomalies within the clinical study data
Example: Conducts pharmacovigilance assessments of collected data and generates queries to close data gaps