Delineation of the intra-tumor microenvironment in a dynamic, spatiotemporal setting is critical for investigating the activity and efficacy of candidate oncology drugs. The majority of solid cancers contain unorganized, highly complex microenvironments wherein a dysregulated phenotype impacts treatment outcomes at a personalized level.
Press Release – updated: Oct 1, 2018 08:00 EDT
TORONTO, October 1, 2018 – Join this live webinar upcoming on Thursday, Oct. 11, 2018, at 11 a.m. EDT (4 p.m. BST/UK) to learn about a clinically validated and fully human ex vivo platform technology which uses fresh patient material (tumor, autologous ligands and immune cells) to explore the mechanism of, and predict efficacy for, clinically directed compounds across several drug classes.1
The platform affords many drug development and discovery applications, including:
- Optimal combination therapies – the prediction outcome system provides a standardized approach to the prioritization of the combinatorial strategies tested
- Mechanism of action – integrated phenotypic outcome and subsequent omic data can shed light on the potential mechanisms of action that underlie a response of interest
- Drug impact – the platform’s preservation of the tumor microenvironment, including the tumor immune compartment, can help hone immunomodulatory strategies
- Biomarker discovery – the tool’s predictive power can be leveraged to identify biomarkers that distinguish populations of responders from non-responders
- Indication prioritization – prioritization algorithms can be used to determine which tumor types will be best addressed by a lead candidate
- Parallel clinical trials – a flexible platform can be harnessed to rapidly assess differential response and resistance profiles within a patient population
Drugs that modulate the immune system have been shown to be very effective in some patients. In general, tumor-infiltrating lymphocytes are required for the function of these drugs. A case study on the use of this ex vivo platform technology to understand the role of functional immune phenotypes when using a checkpoint inhibitor on patient tumor samples will be presented.
During the presentation, Stefan Jellbauer, Ph.D., Technical Liaison at Mitra Biotech, will explore how this platform can better enable translational efforts (including mechanism of action and efficacy) and aid in advancing the highest potential candidate into successful clinical trials with high confidence.
For more information about this complimentary event, visit A Better Predictive Model for Oncology Drug Development Beyond Traditional Platforms.
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1 Majumder B et al. Nature Comm., 6:6169:1-14 2015
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