Project Summary/Abstract
Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers with <9% five-year survival rate and
an estimated 60,000 deaths/year by 2030. PDAC is often diagnosed at an advanced stage thereby precluding
surgical resection for most patients. While new systemic therapy regimens have improved survival, availability
of multiple options, without tools to select an optimal regimen from these (on an individualized basis), has created
a frustrating paradox in clinical decision-making. Due to a lack of personalized predictive tools, current standard
of care treatment strategy is based on prognostic factors such as age, stage, performance status, serum albumin,
etc. There is a critical, urgent and unmet need to develop predictive tools that can identify optimal systemic
therapy regimens and eliminate from consideration ineffective options, on an individualized basis, to improve
quality of life and reduce overtreatment. CerFlux, Inc. is developing such predictive technology with its low-cost
and rapid Personalized Oncology Efficacy Test (POET) to match each patient with the right treatment – before
treatment – to transform pancreatic cancer treatment in the near-term and make a difference in the lives of
patients and providers around the world. Our personalized medicine approach is unique and further enhanced
by a commercial-academic collaboration between CerFlux, Inc. and the O’Neil Comprehensive Cancer Center
at the University of Alabama at Birmingham. The proposed project will build on recent work by our team including
a patented (US 10,114,010B1) biomimetic in vitro platform for pharmacological transport and pancreatic
microtissue tumor models. The commercial goal of this proposal is to identify best practices for using POET in
personalized therapy. Our hypothesis is that response to treatment observed in POET will approximate the
response in the corresponding patient. Our objective is to predict both effective and ineffective treatments for
each patient prior to initiating treatment. We propose the following aims to achieve our objective:
Aim 1: Calibrate and optimize POET for evaluating therapeutics using human PDAC cell-line xenografts for
subsequent testing with patient tissue.
Aim 2: Evaluate efficacy of various systemic therapy agents in POET on an individualized basis to establish
protocols and best practices for using POET in personalized therapy.
We envision substantial continuing commercial-academic collaboration between CerFlux, Inc. and the O’Neil
Comprehensive Cancer Center at the University of Alabama at Birmingham including the integration of machine
learning to derive a “POET Score” – a personalized quantitative efficacy score – based on a combination of
factors. Data from POET and the POET Score will help clinical teams rank treatments for individual patients
before the first drug infusion. If successful, this SBIR-driven study has the potential to transform pancreatic
cancer treatment in the near-term and make a positive impact around the world.
