David Issadore

6.7k total citations · 3 hit papers
101 papers, 5.1k citations indexed

About

David Issadore is a scholar working on Biomedical Engineering, Molecular Biology and Electrical and Electronic Engineering. According to data from OpenAlex, David Issadore has authored 101 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Biomedical Engineering, 40 papers in Molecular Biology and 27 papers in Electrical and Electronic Engineering. Recurrent topics in David Issadore's work include Microfluidic and Capillary Electrophoresis Applications (28 papers), Microfluidic and Bio-sensing Technologies (26 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (24 papers). David Issadore is often cited by papers focused on Microfluidic and Capillary Electrophoresis Applications (28 papers), Microfluidic and Bio-sensing Technologies (26 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (24 papers). David Issadore collaborates with scholars based in United States, South Korea and Switzerland. David Issadore's co-authors include Daeyeon Lee, Heon‐Ho Jeong, Sagar Yadavali, Jina Ko, Ralph Weissleder, Michael J. Mitchell, Sarah J. Shepherd, Hakho Lee, Jaehoon Chung and Huilin Shao and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and Angewandte Chemie International Edition.

In The Last Decade

David Issadore

100 papers receiving 5.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Microfluidic formulation of nanoparticles for biomedical applications

2021 274 citations Sarah J. Shepherd, David Issadore et al. profile →
Scalable mRNA and siRNA Lipid Nanoparticle Production Using a Parallelized Microfluidic Device

2021 222 citations Sarah J. Shepherd, Sagar Yadavali et al. profile →
Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines

2023 68 citations Sarah J. Shepherd, Xuexiang Han et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David Issadore United States	40	3.1k	2.0k	825	606	583	101	5.1k
Amir Sanati‐Nezhad Canada	44	2.9k 0.9×	1.6k 0.8×	866 1.0×	290 0.5×	715 1.2×	140	5.2k
Alexander Revzin United States	44	4.2k 1.4×	3.6k 1.8×	1.0k 1.3×	289 0.5×	426 0.7×	160	7.8k
Tza‐Huei Wang United States	46	4.8k 1.6×	4.2k 2.1×	1.2k 1.4×	585 1.0×	748 1.3×	220	8.6k
Zeyu Wang China	36	2.7k 0.9×	1.4k 0.7×	634 0.8×	621 1.0×	284 0.5×	137	4.6k
Kan Liu China	31	2.3k 0.7×	1.3k 0.6×	565 0.7×	427 0.7×	460 0.8×	168	4.2k
Lu Gan China	47	2.4k 0.8×	3.3k 1.6×	603 0.7×	1.2k 2.0×	1.3k 2.2×	182	7.0k
Jie Chen China	50	3.2k 1.0×	3.6k 1.8×	401 0.5×	601 1.0×	1.5k 2.6×	271	8.3k
Hanry Yu Singapore	50	4.4k 1.4×	2.8k 1.4×	339 0.4×	267 0.4×	969 1.7×	253	9.6k
Yanling Song China	49	4.0k 1.3×	5.2k 2.6×	704 0.9×	640 1.1×	292 0.5×	184	7.6k
Todd Sulchek United States	40	2.0k 0.7×	1.3k 0.7×	622 0.8×	112 0.2×	481 0.8×	118	5.3k

Countries citing papers authored by David Issadore

Since Specialization

Citations

This map shows the geographic impact of David Issadore's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Issadore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Issadore more than expected).

Fields of papers citing papers by David Issadore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Issadore. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Issadore. The network helps show where David Issadore may publish in the future.

Co-authorship network of co-authors of David Issadore

This figure shows the co-authorship network connecting the top 25 collaborators of David Issadore. A scholar is included among the top collaborators of David Issadore based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Issadore. David Issadore is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Issadore, David, et al.. (2025). High-throughput platforms for machine learning-guided lipid nanoparticle design. Nature Reviews Materials. 11(1). 50–64. 2 indexed citations

Shepherd, Sarah J., Rakan El‐Mayta, Thomas F. Anderson, et al.. (2025). Automated and Parallelized Microfluidic Generation of Large and Precisely Defined Lipid Nanoparticle Libraries. ACS Nano. 20(1). 772–789.

Padilla, Marshall S., Sarah J. Shepherd, Martin Kurnik, et al.. (2025). Elucidating lipid nanoparticle properties and structure through biophysical analyses. Nature Biotechnology. 1 indexed citations

Rodriguez‐Rivera, Gabriel J., Amy Perry, Lindsay Riley, et al.. (2025). Microgel Aspect Ratio Influences Injectable Granular Hydrogel Scaffold Pore Structure and Cellular Invasion for Tissue Repair. Advanced Science. 12(43). e11513–e11513. 2 indexed citations

Jang, Bian, Ahmad Amirshaghaghi, Jeongmoon J. Choi, et al.. (2025). Enhanced Accumulation and Penetration of Magnetic Nanoclusters in Tumors Using an 8-Magnet Halbach Array Leads to Improved Cancer Treatment. ACS Nano. 19(1). 1794–1808. 7 indexed citations

Yang, Zijian, et al.. (2024). Ultrasensitive quantification of PD-L1+ extracellular vesicles in melanoma patient plasma using a parallelized high throughput droplet digital assay. Lab on a Chip. 24(14). 3403–3411. 5 indexed citations

Yang, Zijian, Youtao Lu, Hua Zhu, et al.. (2024). Single-mitochondrion sequencing uncovers distinct mutational patterns and heteroplasmy landscape in mouse astrocytes and neurons. BMC Biology. 22(1). 162–162. 3 indexed citations

Johnson, A. T. Charlie, et al.. (2024). Mitigation of Device Heterogeneity in Graphene Hall Sensor Arrays Using Per-Element Backgate Tuning. ACS Applied Materials & Interfaces. 16(30). 39761–39770. 1 indexed citations

Shepherd, Sarah J., Xuexiang Han, Alvin J. Mukalel, et al.. (2023). Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines. Proceedings of the National Academy of Sciences. 120(33). e2303567120–e2303567120. 68 indexed citations breakdown →

10.

Wu, Jingyu, David Issadore, & Daeyeon Lee. (2023). Patterning Wettability on Solvent-Resistant Elastomers with High Spatial Resolution for Replica Mold Fabrication of Droplet Microfluidics. ACS Applied Materials & Interfaces. 15(7). 10212–10218. 9 indexed citations

11.

Oh, Min Jun, Alaa Babeer, Yuan Liu, et al.. (2022). Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth. ACS Nano. 16(8). 11998–12012. 39 indexed citations

12.

Qazi, Taimoor H., Jingyu Wu, Victoria G. Muir, et al.. (2021). Anisotropic Rod‐Shaped Particles Influence Injectable Granular Hydrogel Properties and Cell Invasion. Advanced Materials. 34(12). e2109194–e2109194. 122 indexed citations

13.

Wu, Jingyu, Sagar Yadavali, David Issadore, & Daeyeon Lee. (2021). Ultrahigh Throughput On‐Chip Synthesis of Microgels with Tunable Mechanical Properties. Advanced Materials Technologies. 7(5). 13 indexed citations

14.

Wu, Jingyu, Sagar Yadavali, Daeyeon Lee, & David Issadore. (2021). Scaling up the throughput of microfluidic droplet-based materials synthesis: A review of recent progress and outlook. Applied Physics Reviews. 8(3). 31304–31304. 64 indexed citations

15.

Yang, Zijian, Michael J. LaRiviere, Jina Ko, et al.. (2020). A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosis and Staging of Pancreatic Ductal Adenocarcinoma. Clinical Cancer Research. 26(13). 3248–3258. 87 indexed citations

16.

Lan, Yang, Jingyu Wu, Sagar Yadavali, et al.. (2020). Scalable Synthesis of Janus Particles with High Naturality. ACS Sustainable Chemistry & Engineering. 8(48). 17680–17686. 27 indexed citations

17.

Ko, Jina, Neha Bhagwat, Taylor A. Black, et al.. (2018). miRNA Profiling of Magnetic Nanopore–Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer. Cancer Research. 78(13). 3688–3697. 70 indexed citations

18.

Jeong, Heon‐Ho, et al.. (2018). Moldable Perfluoropolyether–Polyethylene Glycol Networks with Tunable Wettability and Solvent Resistance for Rapid Prototyping of Droplet Microfluidics. Chemistry of Materials. 30(8). 2583–2588. 19 indexed citations

19.

Mealy, Joshua E., Jennifer Chung, Heon‐Ho Jeong, et al.. (2018). Injectable Granular Hydrogels with Multifunctional Properties for Biomedical Applications. Advanced Materials. 30(20). e1705912–e1705912. 281 indexed citations

20.

Jeong, Heon‐Ho, Sagar Yadavali, David Issadore, & Daeyeon Lee. (2017). Liter-scale production of uniform gas bubbles via parallelization of flow-focusing generators. Lab on a Chip. 17(15). 2667–2673. 38 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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