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Novel Concept of Micro Patterned Micro Titer Plates Fabricated via UV-NIL for Automated Neuronal Cell Assay Read-Out

  • Micro Resist Technology GmbH
  • Joanneum Research
  • Innoprot SL

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

11 Citas (Scopus)
4 Descargas (Pure)

Resumen

The UV-nanoimprint lithography(UV-NIL) fabrication of a novel network of micron-sized channels, forming an open channel microfluidic system is described. Details about the complete manufacturing process, from mastering to fabrication in small batches and in high throughput with up to 1200 micro titer plates per hour is presented. Deep insight into the evaluation of a suitable UV-curable material, mr-UVCur26SF is given, presenting cytotoxic evaluation, cell compatibility tests and finally a neuronal assay. The results indicate how the given pattern, in combination with the resist, paves the way to faster, cheaper, and more reliable drug screening.
Idioma originalInglés
Número de artículo902
Páginas (desde-hasta)902
Número de páginas1
PublicaciónNanomaterials
Volumen11
N.º4
DOI
EstadoPublicada - 1 abr 2021

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

  1. ODS 9: Industria, innovación e infraestructura
    ODS 9: Industria, innovación e infraestructura

Palabras clave

  • Nanoimprint lithography
  • R2R UV-NIL
  • Neuronal cell assay

Project and Funding Information

  • Project ID
  • info:eu-repo/grantAgreement/EC/H2020/646260/EU/Large scale micro-and nanofabrication technologies for bioanalytical devices based on R2R imprinting/R2R Biofluidics
  • info:eu-repo/grantAgreement/EC/H2020/862092/EU/Next generation test bed for upscaling of microfluidic devices based on nano-enabled surfaces and membranes/NextGenMicrofluidics
  • Funding Info
  • This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement NO. 646260. The research was also partially supported by NextGenMicrofluidics project under HORIZON2020 with grant agreement no 862092.

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