The course is targeted toward people who are interested in how patient experience data and clinical outcome assessment (COA) data can be used as evidence across drug development, in the pharmaceutical industry. By the end of the course you will better understand how this data is collected and analysed to evidence how patients feel, function or survive in the context of a clinical trial. More specifically, the course will cover: i) a background to COAs; ii) a background to patient experience data; iii) how to select, develop/modify and validate COAs using qualitative data (a) and psychometrics (b); iv) interpreting data on a COA; v) measuring treatment related tolerability via patient reported outcomes; vi) Common COA data outputs.

Data Sciences in Pharma - Patient Centered Outcomes Research

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How patient experience data is used in the drug lifecycle
Developing a patient-centric measurement strategy and using qualitative and quantitative patient experience data as evidence in drug development
Common clinical outcome assessment outputs and considerations when interpreting clinical outcome assessment data
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- Data Literacy
- Clinical Trials
- Clinical Research
- Patient Evaluation
- Data Science
- Patient-centered Care
- Statistical Analysis
- Pharmaceutical Terminology
- Quantitative Research
- Statistical Methods
- Clinical Assessment
- Drug Development
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This module will cover a background of clinical outcome assessments (COAs) and patient experience data, what they are and what they consist of, how this data fits into drug development and the importance of this data as evidence to the external environement (such as health authorities) across the drug lifecycle
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This Module will discuss ways in which qualitative research is used to select, develop, modify or validate a COA. The amount of qualitative research study teams need to conduct can depend on how much qualitative research for the concept of interest in the context of use is already publically available. Qualitative research is often an initial step health authorities such as FDA mandate when they evaluate the suitability of existing and newly developed COAs selected for a clinical trial
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This Module will discuss some of the common quantitative methods used when selecting, developing, modifying and validating a COA. This will include a background to psychometrics and the different properties that are considered for classical test therory and item response theory. It will also touch on the important topic of evaluating change in a COA, what that change means and methods to establish what threshold in the COA of interest would be described as meaningful from the patient's point of view
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This module will provide an understanding of a how patient reported outcomes (PROs) are used to measure treatment related tolerability, with a focus on a commonly used measure called the PRO-CTCAE as well as common COA outputs and considerations when interpreting COA data
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