MICAT: A Melanoma Collaborative Trial Platform for the Future

Melanoma International Collaboration for Adaptive Trials (MICAT), a collaborative platform trial using adaptive trial design to test new agents and combinations in biomarker defined treatments for post-PD-1 treated metastatic melanoma, is transforming the development of melanoma therapies.

Building on Advances from I-SPY 2

I-SPY 2 is a Phase II screening trial that accelerates identification of active agents or combinations of drugs, and predictive biomarkers in the neo-adjuvant breast cancer treatment setting.

MICAT is a global academic-industry collaboration with advocacy and regulatory participation which will test multiple lines of therapy. MICAT will use adaptive statistical methods to enhance strategic decisions in Phase II and Phase III oncology trials. This patient-centric trial will bring effective therapies to the market sooner.

The MICAT Collaboration

MICAT Collaborators graphic

AIM at Melanoma (AIM), International Melanoma Working Group (IMWG), Berry Consultants, and TechAtlas, a division of RA Capital Management are the key participants responsible for establishing MICAT.

The MICAT collaborative platform is designed to increase the speed of decision-making about:

Specific drug or combination of compounds
Relevant biomarkers
Disease progression
Optimal intervention strategies related to patient subpopulations

MICAT Research Goals

Concurrent evaluation of multiple candidate drugs
Efficiency through use of single reference arms with multiple investigational arms
Response adaptive allocation: assigns patients in each subpopulation to treatment based on Bayesian probability
Tests treatment interaction with established and emerging biomarkers
Drops or graduates candidate treatments based on posterior probabilities of success in Phase III
Addresses key questions about the impact of the order in which treatments are given

Identify therapies most likely to increase progression-free survival in advanced melanoma
Test multiple regimens, including combinations
Test sequencing of therapies
Identify biomarker signatures to predict outcomes
Accelerate key development decisions

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