Evidence map›Paper›PMID 32249279›Full record

ArticleLab on a chip2020

Electrostatically gated nanofluidic membrane for ultra-low power controlled drug delivery.

Nicola Di Trani, Antonia Silvestri, Antons Sizovs, Yu Wang, Donald R Erm, Danilo Demarchi, Xuewu Liu, Alessandro Grattoni

Abstract read
In one paragraph

Article in Lab on a chip, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Water-Mediated Ion Selectivity in 2D MXene Channels.Journal of the American Chemical Society · 2026
    Article
  2. Review
  3. Article
  4. Smart closed-loop drug delivery systems.Nature reviews bioengineering · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Nicola Di TraniDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org and University of Chinese Academy of Science (UCAS), Shijingshan, 19 Yuquan Road, Beijing 100049, China.ORCID 0000-0002-4780-7915
Antonia SilvestriDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org and Department of Electronics and Telecommunications, Polytechnic of Turin, Turin, Italy.ORCID 0000-0001-6990-3521
Antons SizovsDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org.
Yu WangDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org.
Donald R ErmDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org.
Danilo DemarchiDepartment of Electronics and Telecommunications, Polytechnic of Turin, Turin, Italy.ORCID 0000-0001-5374-1679
Xuewu LiuDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org.
Alessandro GrattoniDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA. agrattoni@houstonmethodist.org and Department of Surgery, Houston Methodist Hospital, Houston, TX, USA and Department of Radiation Oncology, Houston Methodist Hospital, Houston, TX, USA.ORCID 0000-0001-7888-422X

Funding

A novel nanochannel system for sustained delivery of Tenofovir Alafenamide Fumarate and Emtricitabine for HIV pre-exposure prophylaxisR01AI120749 · NIAID · METHODIST HOSPITAL RESEARCH INSTITUTE · PI GRATTONI, ALESSANDRO · 2016 to 2020
$3.9M
A nanofluidic platform for tunable drug deliveryR01GM127558 · NIGMS · METHODIST HOSPITAL RESEARCH INSTITUTE · PI GRATTONI, ALESSANDRO, LIU, XUEWU · 2018 to 2021
$1.6M
NIAID NIH HHS R01 AI120749NIGMS NIH HHS R01 GM127558
6 · The paper itself

Abstract

Patient-centered therapeutic management for chronic medical conditions is a desired but unmet need, largely attributable to the lack of adequate technologies for tailored drug administration. While triggered devices that control the delivery of therapeutics exist, they often rely on impractical continuous external activation. As such, next generation continuously tunable drug delivery systems independent of sustained external activation remain an elusive goal. Here we present the development and demonstration of a silicon carbide (SiC)-coated nanofluidic membrane that achieves reproducible and tunable control of drug release via electrostatic gating. By applying a low-intensity voltage to a buried electrode, we showed repeatable and reproducible in vitro release modulation of three model analytes. A small fluorophore (Alexa Fluor 647), a large polymer poly(sodium 4-styrenesulfonate) and a medically relevant agent (DNA), were selected as representatives of small molecule therapeutics, polymeric drug carriers, and biological therapeutics, respectively. Unlike other drug delivery systems, our technology performed consistently over numerous cycles of voltage modulation, for over 11 days. Importantly, low power consumption and minimal leakage currents were achieved during the study. Further, the SiC coating maintained integrity and chemical inertness, shielding the membrane from degradation under simulated physiological and accelerated conditions for over 4 months. Through leveraging the flexibility offered by electrostatic gating control, our technology provides a valuable strategy for tunable delivery, setting the foundation for the next generation of drug delivery systems.

Indexed as

Drug Delivery SystemsLab-On-A-Chip DevicesNanotechnologyDrug CarriersDrug LiberationHumansPolystyrenesStatic ElectricityDrug CarriersPolystyrenespolystyrene sulfonic acid

Identifiers

PMID32249279
PMCPMC7249613

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.