Jun 15 2020
Webinar Description:
The rapid development of immuno-oncology (IO) therapies has transformed the cancer treatment landscape and brightened the long-term outlook for many patients with advanced cancer. Among these, checkpoint inhibitors represent a promising therapeutic approach for a wide range of cancers. For instance, PD-1/PD-L1-targeted monoclonal antibodies (mAbs) are now the standard of care for 16 different types of cancer and tissue-agnostic indications. Among them, Pembrolizumab is the most prescribed.
Unfortunately, the response rate for PD-1 monotherapies is insufficient and synergetic strategies are the next logical step to overcome anti PD-1 resistance and address this unmet need. As of end of 2019, up to 2975 combination trials of anti PD1/PD-L1 agents were under way in combination with 295 targets. This trend is led by combinations of chemotherapies with PD-1 and angiogenesis inhibitors with PD-1. This high number of clinical trials highlights a high potential utility from this combination strategy. There is a real need for a suitable and efficient in vivo model able to screen a wide variety of drug combinations before clinical trials – given the high time and cost of each combination.
During the webinar Dr Yan Wang will discuss:
– Benefits of setting up an early in vivo efficacy evaluation to optimize probability of success for synergistic Immuno-oncology drug candidate
– Learn about chicken embryo model
– Understand the interest of xenograft on chicken embryo model
– Chicken embryo in vivo model for early efficacy and toxicity evaluation of Immuno-oncology drug candidates
– Understand pros and cons of chicken embryo model vs mouse model in Immuno-oncology
– Case studies
Learning Objectives:
– Benefits of setting up an early in vivo efficacy evaluation to optimize probability of success for synergistic Immuno-oncology drug candidate
– Chicken embryo in vivo model for early efficacy and toxicity evaluation of Immuno-oncology drug candidates
– Understand pros and cons of chicken embryo model vs mouse model in immuno-oncology
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