Panelists include: 

• Amy Millman, Managing Partner of the StageNext Angel Fund

• Stacey Seltzer, Partner, Gurnet Point Capital

• Zeynep Ilgaz, General Partner, Cross Ocean Ventures

• Stephanie Jacoby, President & Board Chair at Propria Bio

Presenter Order: 

Hong Li, DPhil, Associate Research Scholar in Neuroscience, Yale School of Medicine

Targeting CRIPT to treat cancers

We are developing a gene therapy to treat tumors in various tissues. We identified the first bottleneck protein that controls spindle disassembly during mitosis in human cancer cells called CRIPT. We created a variant form of the protein that can effectively block mitosis of human cancer cells and induce tumor cell death in vitro and in vivo. This protein variant can be produced cost-effectively using genetic material and delivered through various gene therapy methods, including viral vectors, mRNA, and lipid nanoparticles. We plan to develop a series of viral gene delivery system that specifically bring the molecular drug to tumor cells in various tissue types such as breast, lung, liver, brain, etc. Given the potential for CRIPT variant to treat a wide range of cancers, the market size for this drug is potentially huge.

Michelle J. Johnson, PhD, Associate Professor of Physical Medicine and Rehabilitation at the University of Pennsylvania

Rehab CARES--Rehab Community-Based Affordable Robotic Exercise Systems

Stroke is a leading cause of long-term disability and access to affordable rehabilitation intensive care in low resource settings is still difficult. Recupero Robotics LLC is partnering with UPENN and enableGAMES to develop a robot system that is able to be used in low-resource settings. Combing intelligent game-based exercise with reconfigurable robots that are able to be used alone or in connected play.

Ho-Joon Lee, PhD, Research Scientist in Genetics, Yale School of Medicine

EDDIT: Early drug discovery for targeted protein degradation

In drug discovery, accurate prediction of binding affinity of a drug ligand bound to a target molecule is of central importance. Development of computational tools has enabled better prediction of ligand-protein binding affinity for high-throughput virtual screening. Our AI-based technology is designed to maximize the power of existing computational tools in a flexible and synergistic way using a meta-modeling framework to accelerate early drug discovery. We aimed to improve ligand-protein binding affinity prediction by combining structure-based classical scoring functions and sequence-based deep learning models into a single integrative framework of meta-models. Our tool significantly outperforms individual base models and achieves comparable performance to more sophisticated structure-based deep learning models. Our general framework enables the incorporation of either sequence- or structure-based models, as well as physicochemical or molecular features, allowing for the development of flexible and synergistic meta-models leveraging complementary data types and tools. Therefore, this simplicity and flexibility could be disruptive in early drug discovery on a massive scale and provide a foundational framework for universal drug development pipelines. Our particular focus of applications is in the growing field of targeted protein degradation, such as PROTACs and MoDEs, for small-molecule ligand discovery.

Eileen Wang, MD, Professor of Clinical Obstetrics and Gynecology at the University of Pennsylvania

IUDINE, a postplacental IUD retention system

Ensuring optimal interpregnancy intervals is a critical component of maternal health, as short-interval pregnancies (<18 months) are associated with maternal, fetal, and infant risks. Recently imposed abortion restrictions in the US have exacerbated maternal morbidity and mortality. Access to birth control methods immediately after childbirth is a method for reducing the number of short-interval pregnancies and undesired pregnancies. We have developed a novel and temporary, system to improve immediate post-delivery intrauterine device (IUD) performance, by preventing malpositioning and expulsion of the IUD during the postpartum period. With up to 40% of patients unable to attend their postpartum visit, childbirth may represent the only opportunity for a patient to engage in highly effective, reversible contraceptive care. As such, a secured post-delivery IUD in the uterus can limit short-interval pregnancies, reduce undesired pregnancies, and improve overall maternal health outcomes.

Guannan Gong, PhD Associate Research Scientist at Yale University

Accelerating Clinical Trial Recruitment & Feasibility Assessment: Harnessing AI and Real-World Data 

The disparity in trial participation among minority populations impedes research inclusivity and the applicability of findings. Research sites play a crucial role in clinical trials but face challenges in feasibility assessment and patient recruitment due to manual and error-prone methods. To tackle these barriers, our proposal introduces an automated Clinical Trial Patient Matching (CTPM) software. This innovative solution utilizes AI, Large Language Model (LLM), and Natural Language Processing (NLP) to analyze real-time medical data, providing feasibility assessments and screening decisions seamlessly integrated into clinical workflows. Pilot studies at Yale Cancer Center with CTPM version 1.0 demonstrated significant efficiency gains, increased inclusion of underrepresented populations, and high accuracy in patient-trial matching. The software facilitates rapid feasibility assessment, identifies eligible patients (including underrepresented groups), enhances trial awareness among patients and providers, and improves accrual rates.

Akhila Mallavarapu, Postdoctoral Researcher at the Kagan Research Group, Department of Electrical and Systems Engineering (ESE) & Internet of Things for Precision Agriculture (IoT4Ag) Engineering Research Center, University of Pennsylvania

Biodegradable optical sensors for precision agriculture

Leaf conditions inform overall crop health. Current remote sensing methods such as hyperspectral imaging and LIDAR cannot directly detect plant stressors such as humidity, leaf temperature, and transpiration rate. Current leaf sensors are typically battery powered and expensive which limits the #sensors/acre that can be deployed. We have developed low-cost, biodegradable optical sensors capable of sensing changes in canopy microclimate to help mitigate crop stress. This technology can improve crop models and enable precision agriculture, thereby enabling higher crop yield with reduced water and fertilizer usage.

Lea Winter, PhD, Assistant Professor of Chemical & Environmental Engineering, Yale School of Engineering

Highly efficient removal and recovery of nitrate contaminants using electrified membranes

The release of nitrate to the environment from wastewater effluent and agricultural runoff contributes to groundwater contamination, harmful algal blooms, and disruption of biogeochemical nitrogen flows. Nitrate conversion via electrochemical reduction can eliminate the production of concentrated waste streams by generating either harmless N2 or ammonia for fertilizer and fuel. However, major challenges for nitrate removal from water via electrochemical conversion involve reducing the use of expensive precious metal electrocatalysts while also improving the reaction activity, selectivity, stability, and mass transport of nitrate to electrocatalyst active sites.

Raghavi Sudharsan  PhD, Research Assistant Professor of Experimental Ophthalmology, University of Pennsylvania

Targeting PRLΔE1: A Novel Gene-Agnostic Strategy for Retinal Degeneration Therapy

Inherited retinal degenerations, such as retinitis pigmentosa, pose a significant threat of blindness to millions, yet no universal cure is available. Our pioneering research has uncovered PRLΔE1, a novel isoform specifically expressed in diseased rod photoreceptors, as a highly promising target for a broad-spectrum, gene-agnostic therapy. In diverse canine models, knocking down PRLΔE1 has shown remarkable preservation of rod photoreceptors, demonstrating its potential to slow or even halt disease progression. Early trials using shRNA against PRLΔE1 have confirmed its protective effects, and we are now refining our approach to enhance efficacy while minimizing risks. This breakthrough could lead to a transformative treatment capable of addressing multiple forms of retinal degeneration with a single, scalable solution, addressing a critical unmet medical need.

Christine Ko, MD, Professor of Dermatology and Pathology, Yale School of Medicine

Harnessing p53beta as a medical treatment for skin cancer

P53 is the guardian of the genome and mutated in almost all cancers but is difficult to target as an anticancer therapy due to its complex interactions. There are at least 12 isoforms of p53, including p53beta, which can induce terminal differentiation. P53beta is targetable, and our early data has shown that manipulating this pathway causes skin differentiation. Inducing skin differentiation should lead to skin cancer regression in the case of squamous cell carcinoma. Inducing differentiation would also be a potential treatment of actinic keratosis, a precursor lesion of skin cancer. P53beta is an exciting, novel target in cancer therapy.

Avery Posey, PhD,  Assistant Professor in the Department of Systems Pharmacology and Translational Therapeutics at the University of Pennsylvania
Immunocytokines to Enhance CAR T-cell Efficacy

CARmor Therapeutics has developed antibody-cytokine conjugates (immunocytokines) that bind specifically to a molecule called the chimeric antigen receptor (CAR). CAR molecules are engineered into immune cells, such as T-cells, NK-cells, and macrophages, and they work to target the immune system to eliminate cells, such as tumor cells. There are six FDA approved engineered immune cell therapies that are used to treat blood cancers, and there are hundreds of new therapies are under development worldwide to treat other cancers. CAR T-cells have yet to demonstrate robust potency in solid tumors, and their efficacy in blood cancers and solid tumors relies upon their ability to persist and overcome the tumor microenvironment. CARmor's immunocytokines help CAR T-cells overcome the tumor microenvironment and enhance their persistence through specific delivery of potent cytokines. This technological advancement overcomes hurdles of specific cytokine delivery to tumor-reactive immune cells and has the potential to significantly improve patient outcomes.

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ABOUT INNOVATORS IGNITE

Innovators Ignite is hosted by amplifyHERscience, a Yale Ventures program dedicated to supporting and promoting diversity, equity, and inclusion for Yale scientists with entrepreneurial pursuits. The Fall 2024 Innovators Ignite brings together aspiring and diverse academic entrepreneurs from University of Pennsylvania and Yale to present their promising technologies to a panel of industry experts. The pitch event aims to coach, mentor and spotlight under represented academic innovators by harnessing the combined strengths and networks of both institutions.

Leading up to the event, organizers will match the innovators with expert mentors to help them best position their technologies and prepare their presentation for an expert panel of judges. This event is for spotlights innovations across the university that address a market unmet need. These innovations may come from medicine, public health, engineering, environmental sciences.  

The Innovators Ignite pitch event provides the platform, connections, and personalized mentorship needed to take ideas to the next inflection point to positively impact society.