Deliverable

6.3Scenario B-Retrospective use of data

Scenario B
Objective	A researcher wants to define if a gene expression signature can be used to predict the toxic effects (grade 3 (G3) or more) of an investigational class of drugs (e.g. mAb, TKI) used in the neoadjuvant treatment of a specific breast cancer subtype.
Steps	The researcher logs into the system. The researcher filters by type of cancer (i.e. breast), the treatment setting (i.e. neoadjuvant), the selected class of treatment and the toxicity (i.e. G3 or more). The researcher selects for the following outputs; gene expression data, type of drug, toxicity type and grade, clinical trial and patients baseline characteristics. The researcher either downloads the results on his computer (i.e. an excel file in csv format) and the gene expression data in the relevant format or works directly on the INTEGRATE platform using the provided tools.
Results	The researcher analyses gene expression data and tries to confirm his hypothesis: “A gene signature can predict the toxicity of a class of drugs”.

Table Scenario B-Retrospective use of data

The objective of this study is slightly changed compared to the previous one, but the overall prediction framework remains the same. As in previous scenarios, the researcher logs into the INTEGRATE platform and exports the examined dataset which consists of patients with breast cancer, treated by an investigational class of drugs with a specific toxicity type and grade per drug, under neoadjuvant therapy. All available patients that received the investigational drug are dichotomised into two classes based on the toxicity grade of the drugs; a class with high grade (grade 3 or more) and a class with low grade toxic effect. The overall dataset enters the prediction model as in Figure and the researcher can get access to the results by an excel file with all the available information as mentioned in the description of the previous scenario (chapter 6.2).