SCIENCE

In this preprint and accompanying NIH 3D Exchange repository, we address a real-world translational challenge exposed by COVID-19: severe supply-chain disruptions that created critical shortages in personal protective equipment (PPE), even at well-prepared medical centers. The work focused on developing a pragmatic strategy for emergency response manufacturing: instead of 3D-printing entire large volume PPE (often too slow), use additive manufacturing to rapidly produce small, low-cost adapters that repurpose existing components. As a case study, we describe a simple, inexpensive adaptation of elastomeric half-mask respirators for emergency clinical use in high-risk settings, highlighting how fast, locally deployable engineering solutions can help buffer healthcare systems against future supply shocks.

Breast cancer is highly heterogeneous, yet systemic therapy is still too often selected using generalized clinical factors rather than patient-specific evidence, leaving many patients exposed to rounds of ineffective treatment and avoidable toxicity. Through our BCRFA-supported work, CerFlux is advancing its Personalized Oncology Efficacy Test (POET®)to help bridge this gap by testing a patient’s own tumor tissue ex vivo against multiple therapeutics in parallel, before treatment begins. The goal is straightforward: identify which options are most likely to work for an individual tumor - and which are unlikely to benefit - so care teams can move faster toward effective therapy while reducing the burden of failed treatment. By bringing actionable efficacy insight closer to the start of care, this approach is designed to improve decision-making, conserve precious time, and support more personalized treatment pathways.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers, and clinicians still lack predictive tools to determine which systemic therapy is most likely to benefit an individual patient, often leading to trial-and-error care and unnecessary toxicity. In this grant-supported effort, CerFlux is advancing its Personalized Oncology Efficacy Test (POET®) to help match patients to the right regimen before treatment begins. Building on a patented biomimetic in-vitro platform for pharmacologic transport and pancreatic tumor microtissue modeling, the project aims to identify both effective and ineffective options for each patient in advance of clinical decision-making. The work is strengthened through a commercial–academic collaboration with The Ohio State University’s James Comprehensive Cancer Center, including planned machine learning to generate a quantitative “POET Score” that helps rank therapies for each patient.

This JMIRx Med short paper examines whether per-capita COVID-19 testing can mislead policy decisions by ignoring population density (how closely people live and interact). Using publicly reported data for all 67 Alabama counties, the authors compare tests-per-capita against cases and find only a weak relationship (reported correlation r=0.28), while new cases concentrate more heavily in denser areas even when those areas have relatively lower testing when viewed through a density lens. The paper argues that density-agnostic reporting can create a false sense of securityand recommends realigning testing allocation toward higher-density regions to better match transmission risk.

Surface tension is what lets small insects seem to “walk on water”—and in electrohydrodynamic atomization (EHDA), the same physics strongly shapes droplet formation. In this paper, we present an in situ method to estimate surface and interfacial tension (S/IFT) directly within EHDA workflows (eg, electrospinning/electrospraying), where conventional techniques (pendant drop, ring/plate) are often impractical to apply. Our approach uses signal-processing algorithms to extract droplet frequency/periodicity in EHDA microdripping mode and maps those measurements to computational fluid dynamics (CFD) solutions to infer S/IFT during operation. We validate the method against published ranges across multiple reference interfaces and show it captures expected trends such as reduced surface tension with increasing surfactant concentration, while explaining offsets relative to traditional methods. Overall, this provides a practical measurement workflow for tuning EHDA-based processes relevant to microphysiological systems and drug-delivery manufacturing.

In this paper, we describe a growing gap in cancer care between low- and middle-income countries (LMICs) and high-income countries (HICs): LMIC settings often lack basic preventive and diagnostic services for early cancer, while HICs have greater access to novel diagnostic and therapeutic modalities. We argue that narrowing this disparity will require innovative technology, knowledge sharing, and sustained public–private partnerships that can bridge geographic and resource constraints. A key emphasis is the value of onsite and online training programs to strengthen regional capacity and translate modern oncology practices into routine care. We also share case studies illustrating practical ways these collaboration and training models can help close the gap.

This issued patent describes a biomimetic apparatus configured to simulate physiological conditions by providing configurable barrier and transport interfaces within a closed-loop fluid-flow assembly. The modular cassette-based architecture enables controlled flow and transport across an engineered interface to better approximate in vivo dynamics where barrier function matters. Designed to be reconfigurable and scalable, the platform supports human-relevant experimental workflows such as transport studies and compound/therapeutic evaluation in systems that depend on realistic interface behavior.

In this publication, we introduce a new class of biomimetic microphysiological systems that addresses a fundamental shortcoming of conventional lab-on-chip platforms: the absence of tissue-relevant porous barriers that govern real biological transport and interface behavior. By integrating electrospun nanofibrous porous scaffolds directly into microfluidic systems, we developed a lab-on-a-brane (LOB) architecture that more faithfully reproduces key structural and functional features of native extracellular matrix. This platform enables more realistic investigation of molecular transport, air–liquid interfaces, and tumor progression, establishing a scalable and versatile foundation for advanced disease modeling and translational research. The work underscores the CerFlux approach to building physiology-first systems designed to push beyond incremental improvements and redefine what predictive models can achieve.