March 14, 2018
1 pm to 2 pm EDT
A wide spectrum of new cancer treatment paradigms are currently under investigation, poised to compliment or even eclipse traditional cytotoxic strategies associated with radiation or chemotherapy. New and disruptive developing treatment modalities
may take many forms, from small molecules and biologics, perhaps engineered for improved targeting, functionality, or delivery; to cell based therapies, vaccines, gene therapies, and even microbes or associated products. Due to the highly individual
and evolving nature of cancer, patient populations most likely to benefit from such new treatment strategies must be identified using rational selection via biomarkers, and therapies should be rationally applied to compliment current standards
of care and maximize safety and efficacy.
For these reasons, preclinical testing to establish efficacy and proportional benefit has necessarily become more and more a highly customized endeavor. While well-established in vivo and in vitro preclinical translational oncology models continue
to serve as the bedrock of preclinical R&D in oncology, these models can be creatively adapted in a variety of ways to better capture key readouts and primary endpoints, thereby enabling the advancement of innovative new treatments. A diverse
preclinical tool set is now available and can be deployed to address key issues of interest in developing and testing new anticancer therapeutics, be they mechanistic, stratifying, synergistic, scheduling, or purely logistic. Additionally, innovative
new preclinical models are being developed to answer these key questions, probe new potential targets, improve model accuracy, and increase predictive potential.
This webinar will outline Biomodels’ experience and capabilities in conducting highly informative customized preclinical studies in translational oncology. We will discuss how preclinical models and strategies can be tailored to assess specific
readouts in more biologically accurate and clinically recapitulative settings than ever before. Key topics will include model selection, combinations and adjuncts to current therapies, considerations in immunoncology, modeling relapse or resistance,
models of metastasis, targeting tumor microenvironment, imaging modalities, biomarkers, next-generation humanized models, gnotobiotics and microbiome models, and more.
Learn how rational tailoring and customization of preclinical oncology models can be leveraged to advance a diverse range of therapeutic strategies in translational oncology.
Benjamin G Cuiffo, Ph.D.
Principal Scientist, Oncology
Dr. Cuiffo joined Biomodels in 2015 after completing his postdoctoral studies at Beth Israel Deaconess Medical Center and Harvard Medical School, where he was an American Cancer Society Fellow. His postdoctoral work centered upon elucidating the molecular
mechanisms of tumor metastasis in preclinical in vitro and in vivo models. Ben brings additional expertise in the biology of tumor- initiating (cancer stem cells) and invasive phenotypes, oncogenic signaling pathways, and noncoding RNAs in cancer.
He received his Ph.D. in Molecular and Cell Biology from Brandeis University, where he developed novel strategies to target the RAS oncogene in animal models of leukemia. As the Lead Oncology Scientist at Biomodels, Ben’s active collaboration
with clients has optimized the utility, efficiency and translational meaningfulness of a broad range of developing small molecules and immunologically-based therapies.