While tremendous progress has been made using immunotherapies to treat a variety of cancers, it remains a challenge to accurately predict patient response. Part of this challenge is due to the inherent complexity of the tumor microenvironment (TME), including the ability to differentiate various components and accurately identify their interactions, phenotype, and function. Multiplexing spatial imaging technologies can be used to maximize the amount of data collected in the TME, thereby answering more questions from fewer samples. Dr. David Rimm of Yale School of Medicine discusses these approaches and his recent work to improve response prediction to immunotherapy.
CST scientists are biology, application, and therapeutic area domain experts and are here to help you streamline your discovery. Our scientific expertise in oncology therapeutic areas allows us to offer a broad antibody portfolio against key targets and readouts that could lead to new, more efficacious therapies.
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