Historically, the dosing strategy for oncology drugs focused on the maximum tolerated dose. This has resulted in drugs’ pharmacokinetic (PK) profiles, pharmacokinetic/pharmacodynamic (PK/PD) relationships, and clinical target inhibition largely being ignored. Thus, cancer patients often struggle to tolerate their medication doses long-term, requiring dose modifications including dose reductions and holidays.
Project Optimus was initiated by the FDA’s Oncology Center of Excellence (OCE) earlier this year to encourage sponsors to further characterize the dose and schedule of administration of investigational drugs to optimize efficacy while reducing toxicity.
Under this new environment, it becomes critical to understand the available clinical endpoints, when to use them, and how to analyze the data for optimizing dosing for clinical stage oncology therapeutics.
The FDA’s Project Optimus initiative encourages sponsors to collect efficacy and safety data across a range of doses to establish dose- and exposure-response relationships and emphasizes the value of a model-informed drug development (MIDD) approach to increase the knowledge of the potential drugs, referring to three specifics guidances. MIDD is a quantitative framework for prediction and extrapolation of pharmacokinetics and pharmacodynamics, which is centered on knowledge and inference.
Leveraging MIDD to better understand the relationships between dose or exposure and biomarkers, pharmacodynamics, and safety can assist in narrowing the dose range for further exploration by developing mathematical models quantifying the relationship between the drug administration and its pharmacological and/or clinical effect. In the early stage of development, models can help formalize the mechanism of action and quantify the pharmacological activity of the investigational molecule to relate it to clinical effect. In later stage development, characterizing these relationships between dose and exposure to clinical endpoints is critical to determining the optimal dose for registrational studies and eventually regulatory approval.
In this webinar, Drs. Julie Bullock, Vincent Duvall, Adekemi Taylor, and Italo Poggesi will explain how clinical pharmacology and pharmacometric approaches can improve dose optimization decision making by:
Increasing understanding of the available endpoints and when they are best leveraged for your dose justification story
Outlining the opportunities and limitations for the available pharmacometric approaches leveraged for oncology therapeutics at different stages of development
Providing examples of successful quantitative approaches used for dose optimization.
Using simulations to investigate alternative dosing regimens.
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