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Basket and Umbrella Clinical Trials – What Are They and How Can They Be Optimized

Basket and Umbrella Clinical Trials – What Are They and How Can They Be Optimized
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In recent years, the landscape of clinical trials has evolved significantly, particularly in oncology research. Two innovative trial designs that have gained prominence in Phase II are the basket and umbrella designs. These approaches, coupled with the use of patient-derived xenograft (PDX) mouse models, are revolutionizing the way we conduct early-stage clinical research.

Basket Trials: Targeting Mutations Across Cancer Types

Basket trials, also called bucket trials, are designed to test a single drug or combination therapy across multiple cancer types that share a common genetic mutation or biomarker. This approach allows researchers to:

  • Evaluate treatment efficacy in rare cancers
  • Identify potential new indications for existing drugs
  • Accelerate drug development by testing in multiple cancer types simultaneously

For example, a basket trial might investigate a BRAF inhibitor in patients with the BRAF V600 mutation, regardless of their specific cancer type.


Umbrella Trials: Multiple Treatments for a Single Cancer Type

In contrast to basket trials, umbrella trials focus on a single type of cancer but test multiple treatments based on specific genetic alterations.

Key features of umbrella trials include:

  • Use of a multiplex assay to determine treatment arm eligibility
  • Evaluation of several biomarker-guided therapies within one trial
  • Potential for randomization within each treatment arm

The Lung-MAP study is a well-known example of an umbrella trial in non-small cell lung cancer.

Advantages and Considerations

Both basket and umbrella trials offer several advantages:

  • Increased efficiency in drug development
  • Potential for faster patient accrual
  • Ability to study rare cancer subtypes or mutations

However, these designs also present challenges:

  • Complex statistical analysis and interpretation
  • Potential for insufficient sample sizes in some subgroups
  • Need for robust biomarker assays

Mouse Clinical Trials: Mimicking Clinical Trials

Mouse Clinical Trials (MCT), or PDX Clinical Trials (PCT), use Patient-Derived Xenografts (PDX) to incorporate patient tumor diversity into drug development. These trials implant patient tumors into immunocompromised mice, preserving key tumor characteristics.

MCTs act as human surrogate trials, using PDX cohorts in a randomized, controlled, and statistically powered setting. Each PDX model behaves as a patient avatar, representing the diversity of the human population. This method helps identify responders and non-responders, guiding clinical strategies and patient stratification.

MCTs can test various hypotheses, targeting either single mutations across cancer types or different mutations in a single cancer. Choosing the right MCT design is essential, as each type has specific benefits and limitations.

  • Indication-Driven MCT This type tests an agent in a single cancer type, identifying responders and non-responders. It also assesses the impact of a specific target, especially in target-negative PDX models.

  • Target-Driven MCT This type tests a target across cancer types, providing target validation and exploring resistance mechanisms in target-positive PDX models where expected activity is absent.

Summary

The landscape of early-stage clinical trials, especially in oncology, has advanced with innovative designs like basket and umbrella trials, which leverage genetic insights to accelerate drug development. Basket trials explore therapies across different cancer types with shared mutations, while umbrella trials test multiple treatments within a single cancer type, guided by specific genetic alterations. Complementing these designs, Mouse Clinical Trials (MCT) using patient-derived xenograft (PDX) models offer a powerful platform to mimic human responses, providing predictive data that helps refine clinical strategies. Together, these approaches enhance our understanding of treatment efficacy and pave the way for more personalized, targeted cancer therapies.

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