Innovative Clinical Trial Designs for Dose Optimization: Shaping the Future of Drug Development

Advancement of oncology and hematology drug development has brought many innovative medicines in recent years, such as immuno-therapies and CAR-T therapies. Because of the enormous unmet medical need and severity of the disease burden, oncology drug development has traditionally focused on identifying the maximum tolerated dose (MTD) in phase I and moving quickly to phase III, sometimes utilizing a single arm trial at the MTD for accelerated approval. Recently, regulatory authorities have been emphasizing evaluation of the benefit risk in dose optimization and moving towards minimum effective dose (MED) before entering phase 3 development. In this presentation, we will discuss the challenges in identifying the optimal dose in pivotal trials. We will discuss the idea of evaluating dose optimization using inferential seamless phase II/III adaptive design to accelerate clinical development. In addition, we will highlight a few key issues surrounding the use of biomarkers and quantitative measures of benefit and risk for selecting the optimal dose, the analysis of clinical outcomes based on combined data from both phases II and III, as well as blinding and trial integrity with interim adaptation. 

The FDA initiated the project Optimus and issued the draft guidance for dose optimization. The FDA recommends randomized parallel dose-response cohorts to generate additional data at promising dose levels and implies that different dosages may be needed for different indications. In addition to dose optimization, with the recent advancements in precision medicine and cancer biology, the development of cancer treatments has shifted toward the search for agents targeted to specific molecular profiles that may appear in more than one type of cancer. The basket trial is a novel clinical trial design that enables the simultaneous assessment of a new treatment in multiple indications, defined as baskets. Concerning the dose optimization perspective by the FDA and the recent trend of basket trials in early-phase clinical trials, this paper proposes a dose-ranging basket trial design based on a partial pooling hierarchical Bayesian model considering efficacy and toxicity outcomes, where the indications and dose level define baskets. Our simulation study shows that the proposed approach correctly selected the optimal doses and declared the efficacy at each basket compared to the other approaches.
 

The FDA's Project Optimus has redefined dose optimization by recommending randomized, parallel dose-response trials to compare multiple doses. Traditionally, dose optimization follows a two-stage design: starting with dose escalation to identify the maximum tolerated dose, followed by a randomization stage where patients are assigned to different doses to assess and compare their risk-benefit profiles. However, this method often requires a large sample size, posing a significant limitation.

In this presentation, I will introduce innovative seamless dose optimization designs that incorporate adaptive randomization. These designs aim to reduce sample sizes, shorten trial durations, and improve the accuracy of identifying optimal doses. Additionally, recognizing that different dosages may be required for various indications, I will explore the basket trial design, which allows for the simultaneous assessment of a new treatment across multiple cancer types.