09:00 - 17:30 EST | 6.00 - 14.30 PST
* Please note that the following agenda timings are Eastern Standard Time.
For full agenda session details and Pacific Standard Times, please download the full event guide here
8:20 am Chair’s Opening Remarks
Assessing Current Modelling Limitations & Emerging Trends to Drive Clinical Success
8:30 am Combination of a Multimeric Anti-DR5 IgM Antibody with Targeted Agents Induces Synergistic Tumor Cytotoxicity in Vitro & in Vivo
Synopsis
- Death receptor 5 (DR5) is activated upon receptor trimerization and induces cell death. IGM-8444 is a multivalent IgM antibody that efficiently clusters DR5 to induce potency tumor cytotoxicity
- IGM-8444 has a good preclinical safety profile, enabling opportunities for rational combinations with targeted agents
- Synergistic combinations were identified in vitr
9:00 am Reserved for the Jackson Laboratory
9:30 am Translatability at a Glance: Combined Gene Edited & Engineered Cellular Therapies for Solid Tumors
Synopsis
- Creating and characterizing cellular therapies for targeting multiple cell surface receptors on tumor cells and TME
- Testing the efficacy of targeted cellular therapies in translatable tumor models
- Defining a roadmap towards clinical translation
10:00 am Patient-Derived Cell (PDC) Models as a Tool to Assess Cancer Therapeutic Efficacy Across the Drug Development Life Cycle
Synopsis
- PDC model development and characterization
- Clinical response predictivity
- HTS/HCI applications to assess cancer therapeutic efficacy, mechanism of action and patient stratification
10:30 am Morning Break & Structured Networking
Drug Discovery
Optimizing Technologies to Support Pre- Clinical Models
11:15 am Panel Discussion: Utilizing RNA-Seq for Better Pre-Clinical Predictions & Patient Identification
Synopsis
- Screening for actionable targets based on targeted RNA-sequencing to make a more accurate prediction of drug efficacy
- How to preserve the complexity of tumor biology in models?
- Can we use RNAseq to understand MoA?
- Can we use baseline RNAseq readouts as patients selection? Is this practical with a gene signature, or do we need to limit this to 1-2 genes to make this practical in clinical trials?
11:45 am Humanized Mouse Model as a Translational Tool for Immunotherapy in Oncology
Synopsis
- Engineering human target in huPBMC GvHD model to construct a clinic translational model
- Deepen understanding of tumor biology and therapeutic response of multiple specific Nanobodies
- Donor selection and HLA match for improving treatment response
Drug Development
Exploring Approaches to Dosing & Combination Administration Methods
11:15 am Targeting c-MET in Combination with Radiation is Effective in MET-Fusion Driven High- Grade Glioma
Synopsis
- Inhibitor and radiation regimen selection for combinatorial in vivo trials
- Validating preclinical results in multiple mouse models
- Complementing in vivo data with PK and in vitro analyses
11:45 am Combination Therapy to Outsmart RASAddicted Cancer – Informing Clinical Strategy with Preclinical Modeling
Synopsis
- Identify biomarkers that can help direct the “right combination regimen” to the “right patients”
- Define upfront combination regimens that can prevent/ delay emergent resistance mechanisms to RevMed RAS(ON) inhibitors
- Understand if/how we can translate learnings between distinct RAS mutations and cancer histotypes
12:15 pm Networking Lunch
1:15 pm Session Reserved for genOway
Tackling Metastasis: Modelling, Prevention & Treatment
1:45 pm Modeling Bone Metastasis of Prostate Cancer
Synopsis
- Develop mouse models to understand the way tumors metastasize and respond to therapy
- What determines metastatic competency? Can we predict this by studying primary tumors?
- What is the role of biomarkers to predict disease progression?
2:15 pm Session Reserved for Labcorp
2:30 pm Afternoon Break
3:00 pm Session Reserved for GemPharmatech
3:30 pm Developing Clinically Translatable Models that Accurately Represent Patient Metastasis
Synopsis
- Understanding physiological routes of metastasis
- Identifying factors that influence dissemination
- Understanding how the microenvironment contributes to metastasis