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Introducing Certara IQ, an AI enabled modeling platform for scaling and democratizing QSP modeling. Certara IQ offers various workflows to help jump start model building to answer key questions.
In this video, we are joined by Mache Squat, principal QSP scientist who has designed and implemented the recommended phase two dose or RP two d workflow in Certara IQ. We’re talking about recommended phase two dose, a critical step in determining a safe and effective dose for phase two studies. So, Marcie, I want to start by asking you, what is a recommended phase two dose workflow used for?
The recommended phase two dose workflow is based used to support our modelers team in predicting the optimal dose to be used in a phase two of clinical trials.
Typically, a QSP project is based on a complex fit for purpose mechanistic model created to mimic the biological subsystem of the human body in which the client’s compound is acting.
By varying various physiological and or biochemical parameters of this model, a so called virtual population is created which is then used to simulate the drug combinations and treatments for which no data is available.
That way we can help the pharmaceutical company to identify early the therapeutical window, suggesting new doses and dose combinations for the phase two trial.
To achieve that, we provide tools to allow for an in-depth analysis of the simulated cohort for a given treatment and or dose sequence.
They are implemented in Python, which can be used as a compete template or can be treated as a library of analysis items used in isolation for a specific task.
Can you talk to us about some of the main components of this workflow?
Given a calibrated virtual relation, we can not only analyze it using various computational and graphical methods, but we can also use it for hypothesis testing. The first version of the workflow focused on immuno oncology project, but not not limited to, consists of three parts: the response, biomarkers, and survival.
The response part is a collection of measures to evaluate the response of a tumor to treatment. The most relevant system to assess solid tumor response is the RASIST one point one standard based on which the response part of the workflow is built. The modeler can quickly analyze the response status of each subject in terms of complete response, partial response, stable disease, progressive disease, the time evolution of the response status and their best overall response.
On the population level, one can estimate the objective response rate, disease control rate and others.
A useful, a very useful tool to compare different doses is the ORR plot for all treatments in question. The biomarkers part is a collection of methods to assess the impact of biomarkers on the response.
The user has here the following options. First, we will visualize the biomarker time courses and the baseline.
Second, subgroup analysis in various forms such as Kaplan Meier and forest plots for low and high baseline biomarkers.
And third, testing biomarker baselines for their predictive power with respect to the tumor response, ROC curve, dog spots and others. The last part of the workflow is the survival notebook. It’s a collection of tools to analyze time to event endpoints such as duration of response, time to progression, time to response.
Furthermore, a prediction a prediction of one of the most important endpoints, the progression free survival, PFS, can be obtained by superimposing simulated depth or progression events on the simulated virtual population. This can happen when experimental event data is available or by assuming appropriate event thresholds. For each of the time to event endpoints, Kaplan Meier plots and histograms are generated.
Moreover, an overview table is generated for all endpoints.
Thank you very much.
Thank you.
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