Evidence map›Paper›PMID 41453807›Full record

ArticleACS nano2026

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

Andrew R Hanna, Sarah J Shepherd, Gregory A Datto, Rakan El-Mayta, Taigh Anderson, Isabel B Navarro, Adele S Ricciardi, Marshall S Padilla, Neha Srikumar, Shuran Zhang and 6 more

Abstract read
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In one paragraph

Article in ACS nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Andrew R HannaDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.ORCID 0009-0009-3220-4378
Sarah J ShepherdDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Gregory A DattoDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Rakan El-MaytaDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Taigh AndersonChildren's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, United States.
Isabel B NavarroDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Adele S RicciardiDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Marshall S PadillaDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.ORCID 0000-0003-3607-790X
Neha SrikumarDepartment of Biochemistry and Biophysics, Philadelphia, Pennsylvania 19104, United States.
Shuran ZhangDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Hannah M YamagataDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.ORCID 0000-0002-9525-7102
Nova Y MengDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Joshua R BuserConsonant Systems, LLC, Philadelphia, Pennsylvania 19129, United States.
Mohamad-Gabriel AlamehChildren's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, United States.ORCID 0000-0002-5672-6930
Michael J MitchellDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.ORCID 0000-0002-3628-2244
David A IssadoreDepartment of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.ORCID 0000-0002-5461-8653

Funding

Advanced Training at the Interface of Engineering and Oral-Craniofacial SciencesT90DE030854 · NIDCR · UNIVERSITY OF PENNSYLVANIA · PI Hyun Koo, Kathleen J Stebe · 2021 to 2026
$1.4M
NIDCR NIH HHS T90 DE030854Wellcome Trust 2145491
6 · The paper itself

Abstract

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.

Indexed as

LipidsMicrofluidic Analytical TechniquesMicrofluidicsNanoparticlesAnimalsAutomationHumansLab-On-A-Chip DevicesLiposomesLipid NanoparticlesLipidsLiposomesautomated screeninghigh-throughput formulationlipid nanoparticlesmicrofluidicsnanomedicine discoveryparallelized mixing

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.