About

Professor David Issadore leads the Issadore Lab, which integrates microelectronics, microfluidics, nanomaterials, and machine learning to address significant challenges in healthcare. The lab focuses on creating miniaturized platforms for disease diagnosis and developing new methods for manufacturing micro and nanomaterials. Their interdisciplinary approach involves collaboration among engineers, scientists, and physicians to leverage engineering expertise for healthcare improvements. The lab is actively engaged in advancing technologies such as single extracellular vesicle platforms for melanoma diagnostics and scalable manufacturing of lipid nanomaterials on microfluidic chips. Professor Issadore's work also extends to combining artificial intelligence with mRNA drug development through initiatives like the NSF-funded AIRFoundry. His research contributions include innovations in graphene Hall sensor arrays, high-throughput droplet digital enzyme-linked immunosorbent assays, and very large scale microfluidics integration for precision particle and nanoparticle production. Beyond research, Professor Issadore serves the scientific community as an associate editor at Science Advances and fosters a collaborative and creative lab environment.

Research topics

• Computer Science
• Nanotechnology
• Materials science
• Biology
• Computational biology
• Physics
• Biomedical engineering
• Biological system
• Neuroscience
• Cell biology
• Engineering
• Pathology
• Medicine
• Telecommunications
• Chemistry

Selected publications

• Scalable flow synthesis of ultrasmall inorganic nanoparticles for biomedical applications via a confined impinging jet mixer

  Scientific Reports · 2026-02-26

  articleOpen access

  Ultrasmall inorganic nanoparticles (sub-5 nm) have unique biomedical advantages due to rapid clearance, enhanced imaging contrast, and potent therapeutic properties. However, current synthesis methods are limited by low throughput, polydispersity, and reliance on harsh conditions such as organic solvents or high temperatures. We report a scalable, single-step aqueous synthesis using a confined impinging jet mixer (CIJM) that produces size-controlled, clinically relevant nanoparticles, including silver sulfide, silver telluride, cerium oxide, and iron oxide, under ambient conditions. The resulting nanoparticles are homogeneous, stable, and preserve their functional biological properties. We demonstrate consistent performance across scales, establishing the CIJM as a versatile and reproducible method for producing ultrasmall inorganic nanoparticles suitable for clinical translation and high-throughput biomedical applications.

  PublisherDOI

• High‐Density and Scalable Graphene Hall Sensor Arrays Through Monolithic CMOS Integration

  Advanced Electronic Materials · 2026-03-28

  articleOpen accessCorresponding

  ABSTRACT Electronic devices made from two‐dimensional materials (2DMs) significantly outperform their silicon counterparts; however, silicon CMOS technology remains commercially predominant as it offers the capability to operate dense arrays of devices in a scalable fashion. In particular, graphene Hall sensors (GHSs) offer great improvements in magnetic field sensitivity and resolution compared to silicon Hall‐effect sensors, making them extremely appealing for magnetic field imaging and biosensing. At present, GHS arrays have limited scalability compared to silicon CMOS since they require planar routing for biasing and multiplexing. In this work, we explore strategies to realize high‐density graphene Hall sensor arrays by vertically connecting GHSs with silicon CMOS biasing and multiplexing circuitry, allowing the routing and circuitry to scale with the array. We investigate the importance of design choices in the chip layout and post‐fabrication process in maximizing the reliability of graphene integration onto mm‐scale CMOS dies. Using this integration process, we show that GHSs and CMOS circuits can be monolithically integrated with high yield, creating high‐density magnetic sensing arrays with vertical biasing and readout connections. We expect that these results will lead to further improvements in magnetic sensing technology and broader advancements in large‐scale heterogeneous 2DM‐CMOS systems.

  PublisherDOI

• Towards clinical translation of nanomedicines: Formulation scale-up and model systems

  Advanced Drug Delivery Reviews · 2026-03-31 · 1 citations

  article
  PublisherDOI

• Author Correction: Elucidating lipid nanoparticle properties and structure through biophysical analyses

  Nature Biotechnology · 2026-01-22

  articleOpen access
  PublisherOA PDFDOI

• Data and code from: Microfluidic nanomagnetically isolated neuron- and astrocyte-derived extracellular vesicles to differentiate Lewy body and Alzheimer’s disease

  DRYAD · 2026-03-03

  datasetOpen accessSenior author

  Identifying plasma-based biomarkers that can accurately differentiate Lewy body disease (LBD) from Alzheimer’s disease (AD) remains a major challenge. Extracellular vesicles (EVs), which carry molecular cargo from their parent cells and can cross the blood-brain barrier, offer a new path forward. We developed the multiplexed Track-Etch magnetic NanoPOre (mTENPO) platform, a highly parallelized microfluidic technology for cell-specific EV isolation, and demonstrated independent enrichment of GluR2+ (neuron-derived) and GLAST+ (astrocyte-derived) EVs from the antemortem plasma of 137 autopsy-confirmed LBD, AD, mixed pathology, and control subjects. By integrating miRNA sequencing of GluR2+ and GLAST+ EV cargo with plasma measurements of Aβ40, Aβ42, tau, p-Tau181, and p-Tau231, we identified a multimodal 15-feature panel that more comprehensively reflects brain pathology than conventional biomarkers. Using 10-fold cross-validation to mitigate overfitting, the panel achieved an accuracy of 0.95 and an area under the curve of 0.96 for distinguishing LBD versus AD.

  PublisherDOI

• High‐Density and Scalable Graphene Hall Sensor Arrays Through Monolithic CMOS Integration

  Advanced Electronic Materials · 2026-03-28

  articleOpen accessCorresponding

  ABSTRACT Electronic devices made from two‐dimensional materials (2DMs) significantly outperform their silicon counterparts; however, silicon CMOS technology remains commercially predominant as it offers the capability to operate dense arrays of devices in a scalable fashion. In particular, graphene Hall sensors (GHSs) offer great improvements in magnetic field sensitivity and resolution compared to silicon Hall‐effect sensors, making them extremely appealing for magnetic field imaging and biosensing. At present, GHS arrays have limited scalability compared to silicon CMOS since they require planar routing for biasing and multiplexing. In this work, we explore strategies to realize high‐density graphene Hall sensor arrays by vertically connecting GHSs with silicon CMOS biasing and multiplexing circuitry, allowing the routing and circuitry to scale with the array. We investigate the importance of design choices in the chip layout and post‐fabrication process in maximizing the reliability of graphene integration onto mm‐scale CMOS dies. Using this integration process, we show that GHSs and CMOS circuits can be monolithically integrated with high yield, creating high‐density magnetic sensing arrays with vertical biasing and readout connections. We expect that these results will lead to further improvements in magnetic sensing technology and broader advancements in large‐scale heterogeneous 2DM‐CMOS systems.

  PublisherDOI

• Microfluidic nanomagnetically isolated neuron- and astrocyte-derived extracellular vesicles to differentiate Lewy body and Alzheimer’s disease

  npj Biosensing · 2026-03-12

  articleOpen accessSenior authorCorresponding

  Identifying plasma-based biomarkers that can accurately differentiate Lewy body disease (LBD) from Alzheimer's disease (AD) remains a major challenge. Extracellular vesicles (EVs), which carry molecular cargo from their parent cells and can cross the blood-brain barrier, offer a new path forward. We developed the multiplexed Track-Etch magnetic NanoPOre (mTENPO) platform, a highly parallelized microfluidic technology for cell-specific EV isolation, and demonstrated independent enrichment of GluR2+ (neuron-derived) and GLAST+ (astrocyte-derived) EVs from the antemortem plasma of 137 autopsy-confirmed LBD, AD, mixed pathology, and control subjects. By integrating miRNA sequencing of GluR2+ and GLAST + EV cargo with plasma measurements of Aβ40, Aβ42, tau, p-Tau181, and p-Tau231, we identified a multimodal 15-feature panel that more comprehensively reflects brain pathology than conventional biomarkers. Using tenfold cross-validation to mitigate overfitting, the panel achieved an accuracy of 0.95 and an area under the curve of 0.96 for distinguishing LBD versus AD.

  PublisherOA PDFDOI

• Insights into mRNA lipid nanoparticle polydispersity and shape using quantitative solution biophysics

  Structural Dynamics · 2025-03-01 · 1 citations

  articleOpen access

  Lipid nanoparticles (LNPs) are the most advanced delivery system currently available for RNA therapeutics. Their development has accelerated rapidly since the success of Patisiran, the first siRNA-LNP therapeutic, and the SARS-CoV-2 mRNA vaccines that emerged during the COVID-19 pandemic. Designing LNPs with specific targeting, high potency, and minimal side effects is crucial for their successful clinical use. However, our understanding of how the composition and mixing methods influence the structure, biophysical properties, and biological activity of the resulting particles remains limited. While microfluidic technologies have significantly improved the speed and uniformity of LNP production, a major challenge that remains is that ~60-80% of mRNA-LNP formulations are unloaded (empty lipid particles). This study tackles this challenge by relating current standard characterization methods with more powerful emerging methods, including 1. multi-wavelength analytical ultracentrifugation (MWL-AUC), 2. In-line multi-angle light scattering (MALS) methods, and 3. synchrotron size-exclusion chromatography in-line with small-angle X-ray scattering (SEC-SAXS) coupled with singular-value decomposition methods (SVD). We will present the strengths and weaknesses of each approach and showcase the increased detail newer advanced methods provide by comparing LNP formulations made using two common small-scale production methods: microfluidic rapid mixing and bulk mixing. The characterization techniques employed here can enhance our understanding of LNP structure-function relationships and enable researchers to define their RNA LNP products more precisely, which can improve LNP quality and potentially accelerate pharmaceutical development.

  PublisherDOI

• Automated and Parallelized Microfluidic Generation of Large and Precisely Defined Lipid Nanoparticle Libraries

  ACS Nano · 2025-12-26 · 3 citations

  articleSenior authorCorresponding

  Lipid nanoparticles (LNPs) are being developed for a broad set of therapeutic applications by changing both the structures of the lipids used to formulate each LNP and their relative proportions. Because lipid synthesis and in vivo screening have been parallelized using combinatorial chemistry and LNP barcoding, respectively, the manual and sequential microfluidic formulation of LNPs remains the primary rate-limiting step during early-stage discovery. In this work, we present a parallelized, automated microfluidic platform capable of generating large, precisely defined LNP libraries in parallel, with throughput on the order of 1000 distinct formulations per hour. Each formulation is defined by varying the reagent flow ratios into one of eight microscale mixers using lithographically encoded fluidic resistors and dynamically controlled external pressure supplies. The microfluidic chip is integrated with custom robotic plate handling for the rapid collection of each distinct formulation. To evaluate this platform, we characterized 96 formulations generated on-chip in terms of both physicochemical properties and transfection efficiency in vitro. We further validated our lead candidate against the state of the art in vivo. We demonstrate the ability to rapidly discover a formulation and scale its production to liters per hour under identical mixing conditions, bridging from early discovery to manufacturing through microfluidic parallelization.

  PublisherDOI

• Extracellular Vesicles for Clinical Diagnostics: From Bulk Measurements to Single-Vesicle Analysis

  ACS Nano · 2025-07-28 · 51 citations

  reviewOpen access

  Extracellular vesicles (EVs) play a crucial role in intercellular communication, signaling pathways, and disease pathogenesis by transporting biomolecules such as DNA, RNA, proteins, and lipids derived from their cells of origin, and they have demonstrated substantial potential in clinical applications. Their clinical significance underscores the need for sensitive methods to fully harness their diagnostic potential. In this comprehensive review, we explore EV heterogeneity related to biogenesis, structure, content, origin, sample type, and function roles; the use of EVs as disease biomarkers; and the evolving landscape of EV measurement for clinical diagnostics, highlighting the progression from bulk measurement to single vesicle analysis. This review covers emerging technologies such as single-particle tracking microscopy, single-vesicle RNA sequencing, and various nanopore-, nanoplasmonic-, immuno-digital droplet-, microfluidic-, and nanomaterial-based techniques. Unlike traditional bulk analysis methods, these methods contribute uniquely to EV characterization. Techniques like droplet-based single EV-counting enzyme-linked immunosorbent assays (ELISA), proximity-dependent barcoding assays, and surface-enhanced Raman spectroscopy further enhance our ability to precisely identify biomarkers, detect diseases earlier, and significantly improve clinical outcomes. These innovations provide access to intricate molecular details that expand our understanding of EV composition, with profound diagnostic implications. This review also examines key research challenges in the field, including the complexities of sample analysis, technique sensitivity and specificity, the level of detail provided by analytical methods, and practical applications, and we identify directions for future research. This review underscores the value of advanced EV analysis methods, which contribute to deep insights into EV-mediated pathological diversity and enhanced clinical diagnostics.

  PublisherDOI

Recent grants

• A nanomagnetic platform technology to characterize traumatic brain injury using brain derived extracellular vesicles

  NIH · $414k · 2018–2020

• NIH Grant R21CA18233601A1

  NIH · $231k · 2017

• Spatially-targeted heating of magnetic nanoparticles

  NIH · $411k · 2018–2021

• CAREER: Time-domain encoded optofluidics for highly multiplexed pathogen detection

  NSF · $510k · 2016–2022

• NIH Grant R21CA182336

  NIH · $433k · 2018

Frequent coauthors

• Ralph Weissleder

  Center for Systems Biology

  93 shared

• Jina Ko

  University of Pennsylvania

  76 shared

• Hakho Lee

  Massachusetts General Hospital

  68 shared

• Huilin Shao

  Institute of Molecular and Cell Biology

  51 shared

• Erica L. Carpenter

  50 shared

• Sagar Yadavali

  Halo Labs (United States)

  48 shared

• Jaehoon Chung

  LG (South Korea)

  43 shared

• Stephanie S. Yee

  University of Pennsylvania

  40 shared

Labs

• Issadore LabPI

Education

• Ph.D., Materials Science and Engineering

  University of Pennsylvania

  1997

• M.S., Materials Science and Engineering

  University of Pennsylvania

  1993

• B.S., Materials Science and Engineering

  University of Pennsylvania

  1991