16-18 July 2018 | Boston


Day One
Wednesday July 19, 2017

Day Two
Thursday July 20, 2017

Networking & Coffee

Chair’s Opening Remarks

Clinical Findings & Experimental Platforms to Identify Effective IO Combinations

Advanced PDX Tumor Biology Platforms for Drug Advancement

  • Neal Goodwin VP, Corporate Research Development, Champions Oncology


  • An expansive PDX platform for modeling solid tumor and hematology oncology malignancies including AML and ALL has been implemented from Personal Oncology Solutions patient cohorts and from an extensive clinical trial center collaboration network
  • This clinical focus and medical affairs infrastructure has allowed for the PDX platform to be seamlessly expanded for use in co-clinically modeling Phase 1-Phase 3 trials for both solid tumor oncology and hematology oncology
  • Advances in PDX modeling including human immune system (HIS) modeling and systems for high-throughput screening and Big Data collection will be presented

Evaluating Preclinical Predictions for the Development of Combinations with Targeted Therapies & Immunotherapies

  • Andrew Rhim CPRIT Scholar in Cancer Research, Associate Director for Translational Research in Pancreatic Cancer Research, Assistant Professor of Internal Medicine in , Gastroenterology, Hepatology & Nutrition, MD Anderson Cancer Center


  • Describing models used and key considerations for experimental design
  • Model responses and predictability of combination efficacy

A Novel Phenotypic Platform for Predicting Tumor Response

  • Mark Paris PhD. Associate Director, Translational Applications, Mitra Biotech


  • Showcasing a novel platform to study and characterize immune cell interactions in response to therapies
  • How can this platform advance preclinical predictions for IO therapies?

Networking & Morning Refreshments

Chair: Leigh Ellis, Member of Faculty, Department of Oncologic Pathology, Dana-Farber Cancer Institute

11.10 Reverse Translation: Evaluating the Predictability of Preclinical Models Through Correlation Analysis of Clinical Data for Targeted Therapies

  • Discussing early clinical data and analysis into the correlation of preclinical predictions from models with clinical data
  • Addressing how clinical insights are optimizing preclinical studies for future therapies or combination therapies

Christopher Murriel, Senior Scientist II, OncoMed Pharmaceuticals

11.40 Modeling Development of a Gene Expression Signatures of Response & Resistance to Proteasome Inhibitors

  • Demonstrate the use of cell line models to develop a gene expression signature that predicts response or resistance to proteasome inhibitors in myeloma
  • Demonstrate gene signatures can be validated in stratification of clinical trial outcomes.
  • Show how gene expression signatures of therapeutic response can be applied in single cells to identify tumor heterogeneity in patients
  • Show how computational approaches to identify predictive signatures can be used using national data bases

Brian Van Ness, Professor, Department of Genetics, Cell Biology & Development, College of Biological Sciences, University of Minnesota Cancer Center

12.10 Addressing the Woodchuck Model for Hepatitis B Related HCC

  • Using the woodchuck model in the preclinical development of therapies for Hepatitis B related HCC
  • Discussing the high translatability of the preclinical insights gained from the woodchuck model into the clinic

Renuka Iyer, Section Chief GI Medical Oncology, Roswell Park Cancer Institute

12.40 Networking lunch

Addressing Preclinical Model Advancements: Optimizing In Vitro Models

13.40 Advances in In Vitro Model Development for Oncology Drug Discovery

  • Utilizing 3D models to understand the tumor microenvironment and interactions with immune cells
  • Addressing preclinical strategies to enhance the translation between in vitro and in vivo preclinical studies

Serena Silver, Senior Investigator, Group Leader, Oncology, Novartis Institutes for Biomedical Research

14.10 Accelerating Prediction of Tumor Vulnerabilities Using Next-Generation Cancer Models

  • It is now possible to generate cell models at scale for many tumor types; in-line genomics is required to iteratively improve methods
  • Understanding the cancer cell model genomic stability across passages is critical for profiling the small molecular and genetic screens
  • We aim to expand the knowledge of cancer dependency map by adding the next generation cancer models

Moony Tseng, Research Scientist II, Cancer Cell Line Factory Project Lead, Broad Institute

14.40 Modeling Tumor Microenvironment using Microfluidic Systems

  • Utilizing microfluidic platforms to study cancer cell-immune cell Interaction
  • In vitro system to study the mechanobiology of immune cell in the tumor microenvironment
  • Developing microfluidic platforms for testing immunotherapy

Ran Li, Postdoctoral Scientist, Roger Kamm’s Lab, Department of Biological Engineering & Mechanical Engineering, MIT

15.10 Circulating Tumor Cell (CTC) Analysis in Preclinical Models of Cancer Metastasis

  • Although a number of quantitative tools have been previously developed to study in vivo metastasis, the detection and quantification of rare metastatic events has remained challenging
  • To discuss the use of circulating tumor cell (CTC) analysis as an effective means of tracking and characterizing metastatic disease progression in preclinical mouse models of breast and prostate cancer
  • In particular, the use of clinically-relevant CTC technologies such as the Parsortix platform (ANGLE plc) to enhance the translation of cancer biology and new cancer therapies from animal to patient

Alison Allan, Associate Professor, Departments of Anatomy & Cell Biology & Oncology Schulich School of Medicine and Dentistry, Western University – In collaboration with Angle

Chair: Edward Rosfjord, Senior Principal Scientist, Pfizer

11.10 Highlighting Clinical Outcomes of CAR-T Therapies to Enhance Translational Insights from Preclinical Models

  • Harnessing valuable clinical insights to advance preclinical translation for future therapies
  • How have clinical learnings advanced preclinical studies to better present the patient population

David Teachey, Associate Professor of Pediatrics, Divisions of Hematology & Oncology, Children’s Hospital of Philadelphia, University of Pennsylvania School of Medicine

11.40 BPM 31510, A Clinical Stage Candidate, Demonstrates Potent Anti-Tumor Effect by Modulating Metabolism of Immune Cells

  • By improving the metabolic activity of immune-cells we can improve the Immunotherapies.
  • BPM31510 is a metabolic modulator
  • BPM31510 demonstrates potent anti-tumor efficacy in syngenic models
  • BPM31510 modulates the level of tumor infiltrating cells in a dose-dependent manner

Shiva Kazerounian, Senior Scientist, Berg Pharma

12.10 Comparative Oncology to Inform Clinical Translation of Immunotherapies

  • Overview and attributes of the Comparative Oncology approach
  • Utility of Comparative Oncology to facilitate clinical translation of Oncolytic virus and other immunotherapies
  • Currently available tools and development of new tools in development to facilitate immunotherapy development (e.g. biomarkers, imaging, genomics)

Shruthi Naik, Research Associate, Department of Molecular Medicine, Mayo Clinic

12.40 Networking lunch

Clinical Learnings from Immunotherapies to Drive Preclinical Predictions

13.40 Harnessing Humanized Mice to Improve Preclinical Predictions for Immuno Therapy and Nano Technology Approaches to Treat Cancers

  • Acknowledging and understanding the limitations of humanized mouse models
  • What does the perfect humanized model look like for ex vivo applications?

Vinagolu Rajasekhar, Senior Research Scientist, Memorial Sloan Kettering Cancer Center

14.10 Influence of Microenvironment in Primary & Bone Tumor Breast Cancer Models

  • Hormonal influence in orthotopic breast cancer tumor model
  • Bone microenvironment and breast cancer tumor growth
  • Immuno-oncology: tumor, bone and immune system in humanized mice

Jenni Bernoulli, COO, Pharmatest Services

14.25 Biological Advances to Help Navigate the Nonclinical Safety Assessment Strategy in Cancer Immunotherapy

  • Highlighting the unique challenges in preclinical safety assessment for the development of cancer immunotherapeutics which may not be optimally characterized using conventional toxicology models or strategy
  • Discussing the opportunities of modifying the conventional toxicology models or developing novel approaches to support clinically relevant hazard identification and risk assessment

Robert Li, Toxicologist, Pharmacology SubTeam Leader Safety Assessment, Genentech

14.55 Characterization & Application of the Triple Immunodeficient R2G2 (Rag2/Il2rg Double Knockout) Mouse

  • Overview of the of the new R2G2 model characteristics
  • Comparative analysis of the R2G2 and NSGTM immune systems
  • Factors that contribute to differential radiation sensitivity between the Rag2 and SCID models, and the impact of radiosensitivity on experimental design

Lee Coney, Chief Scientific Officer, Biologics, Envigo 


Next Generation Model Development: Harnessing CRISPR Precision Gene Editing

Networking & Afternoon Refreshments

CRISPR Genome Editing & Mouse Models of Cancer

  • Sidi Chen Assistant Professor, Genetics, Yale University


  • Harnessing CRISPR for the precise development of physiologically relevant preclinical in vivo models for target discovery
  • Developing knock out models that are personalized to individual tumor types

Exploring Tumor Initiation & Progression of Colorectal Cancer Using Flexible Genetic Models

  • Luke Dow Assistant Professor of Biochemistry in Medicine, Weill Cornell Medicine


  • Using engineered organoids for the production of tailored pre-clinical models of disease
  • Bypassing the limitations of existing transgenic systems, through orthotopic organoid transplantation
  • Engineering complex tumor genotypes using multiplexed CRISPR/Cas9 genome editing

Combining CRISPR/Cas9 Gene Targeting & Single-Copy Somatic Transgenesis for Preclinical Brain Tumor Research

  • Joshua Breunig Assistant Professor, Board of Governors Regenerative Medicine Institute, Department of Biomedical Sciences, Cedars-Sinai Medical Center


  • Overview of novel genetic methodologies for rapid, autochthonous tumor modeling
  • Using patient mutations in mouse models to accurately model clinical tumor subtypes in a “personalized” manner
  • Examples of preclinical studies investigating strategies to impede tumor growth and development by immunotherapy, metabolic targeting, and therapeutic mimicry
  • Employing CRISPR/Cas9 to enable rapid genetic manipulation of patient tumor cells for investigating the mechanisms of tumorigenesis and subsequent recurrence

Chair’s Closing Remarks

Close of the 5th Annual Tumor Models Boston 2017