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CtrlTrial presented at the Yale New Haven Health Innovation Award

Yale New Haven Health Center for Health Care Innovation Celebrates Impactful Innovations at Virtual Pitch Event

Tuesday, May 14, 2024

The Yale New Haven Health (YNHHS) Center for Health Care Innovation (CHI) celebrated impactful innovations at a two-hour virtual pitch on April 30. Established in 2019 as a joint initiative between YNHHS and Yale University, CHI champions innovation and leads the implementation of novel solutions to transform healthcare delivery. The YNHHS Innovation Awards seek to provide needed resources to YNHHS employees and Yale University faculty working on promising ideas with potential near-term commercial impact. The top five teams selected in this competition will receive grants of $100K to advance their innovations.

This year’s call for proposals, the second cycle since the launch of the awards in 2022, was marked by 30 percent growth in the total number of submissions and characterized by a robust, diverse pool and strong collaboration between teams from both the health system and university. Eligible focus areas included big data, care anywhere, generative artificial intelligence (AI), health equity and new care delivery models. After initial review, 11 semi-finalist teams were invited to pitch their idea to a distinguished panel of judges at the virtual event. The judging panel was comprised of strategic investors, venture capitalists and clinicians including Josh Flum, managing partner, LRVHealth; Kip McCoy, vice president, Innovation Studio at OSF HealthCare; Kaakpema “KP” Yelpaala, senior fellow and lecturer at Yale School of Public Health, faculty director InnovateHealth Yale; Navin Goyal, managing partner, Loud Capital;and Carrie Williams partner, McKesson Ventures. Over 150 health system staff, university faculty and senior leaders joined the event.

Maxwell Laurans, MD, senior vice president, Neurosciences, Orthopedics and Surgical Services, Yale New Haven Hospital and assistant professor of Neurosurgery, Yale School of Medicine, kicked-off the event and introduced the judges and semi-finalist teams to the audience. Pitching began and each semi-finalist team delivered a five-minute pitch followed by three minutes of Q&A from the judges. Each semi-finalist team was evaluated based on key criteria including: 1) unmet medical need, 2) likelihood of technical success, 3) novelty, 4) business model and competitive landscape, and 5) team composition and skills/background.

The semi-finalist teams included:

Clinical Trial Patient Matching (CTPM): CTPM system to tackle patient matching in clinical trials – Lead: Guannan Gong, PhD; Team: Neil Fischbach, MD, Patricia LoRusso, Pamela Kunz, MD, Ian Krop, MD, PhD.

Accurate detection of cardiovascular disease with AI-assisted technology: Innovative computer vision methods and extensive AI toolkit of proprietary software solutions for the efficient screening of under-recognized cardiomyopathies directly from point of care Ultrasound – Lead: Rohan Khera, MD; Team member: Evan Oikonomou, MD, DPhil.

AI Clinical Decision Support to Detect Urinary Tract Infections (UTIs) in the Emergency Department (ED): AI-driven and electronic health record-embedded clinical decision support (CDS) tool to augment ED clinicians’ reasoning in the diagnosis of UTIs – Lead: Mark Iscoe, MD; Team member: Richard Andrew Taylor, MD.

Algorithm for Drug Diversion: Algorithms to rapidly detect discrepancies to identify and signal diversion of Controlled Substance infusions to mitigate drug diversion – Lead: Kim Walter, PharmD; Team members: Davis Darsh, Daniel Hinkelmann, Andrew Loza, Jaganmohan Rao Narayanam, PhD, Ju-Sung Song, PharmD, Prem Thomas, MD, LeeAnn Miller, PharmD.

Computational Optimization of DNA Activity: Platform to create synthetic gene promoters to existing or in-pipeline therapies that could be improved by having fewer off-target effects – Lead: Steven Reilly, MD.

Hematopoietic cell transplantation (HCT) AI Prediction: AI model that can accurately predict the of outcomes of allogeneic HCT – Lead: Lakshmanan Krishnamurti, MD; Team member: Michael Kane, PhD.

JuniHealth AI-platform for Radiology: Comprehensive AI platform to support radiology practices in streamlining tedious parts of common workflows through advanced natural language technologies – Lead: Sophie Chheng, MD; Team members: Arman Cohan, PhD, Lorenzo Flores, Ryan Martin, Kyle Tegtmeyer, MD.

LLM to predict Gastrointestinal Bleeding: LLM-powered EHR algorithm to identify patients with recurrent bleeding and capturing incremental revenue to support accurate coding data for GIB patients – Lead: Dennis Shung, MD, PhD; Team members: Ohm Deshpande, MD, Yuan Pu, Hamita Sachar, MD.

Machine Learning to identify Post-Acute Infection Syndromes (PAIS), including Long COVID: ML to create first diagnostic tool, trained on Long COVID multi-modal datasets, which will identify PAIS patients with autoantibody-driven pathology – Lead: Smita Krishnaswamy, MD; Team members: Dhananjay Bhaskar, PhD, Nicole Darricarrere, MD, Akiko Iwasaki, MD.

NeuroProbe Monitoring System: Single brain implantable multi-sensor device with array of multimodal sensors for rapid, sensitive, co-localized, in vivo measurement of brain physiology – Lead: Hitten Zaveri, MD; Team members: Emily Gilmore, MD, Dennis Spencer, MD.

Virtual Reality (VR) Simulated Psychedelic Experience: VR simulated psychedelic experience as a novel non-pharmacological and broadly accessible treatment for patients with depressive disorders and suicidal ideation – Lead: Mohini Ranganathan, MD; Team members: Jose Cortes-Briones, PhD, Kimberly Hieftje, PhD, Asher Marks, MD.


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