A Droplet based Multi-Drug Screening System Controlled with Electrostatic Microvalves

Date

2012-10-28

Author

Yıldırım, Ender
Külah, Haluk

Metadata

Show full item record

Item Usage Stats

165
views

0
downloads

This paper presents a droplet-based drug effect analysis system utilizing electrostatically-actuated normallyclosed microvalves to screen the effect of multiple drugs on a single type of cell. Proposed system minimizes the need for off-chip equipment by utilizing parylene based electrostatic microvalves. Prototypes of the system were fabricated and tested using colored DI water and 3 μm diameter micro beads, emulating drugs and cells respectively. During the tests, micro beads could be successfully entrapped in 137 pl droplets. Tests carried out with yeast cells also yielded successful encapsulation of the cells. It was shown that, switching between the drugs could be achieved by applying 200 V dc to operate the microvalves.

Subject Keywords

Electrostatic, Microvalve, Multi-drug screening, Parylene

URI

https://hdl.handle.net/11511/73239

Conference Name

16th International Conference on Miniaturized Systems for Chemistry and Life Sciences (28 Ekim - 01 Kasım 2012)

Collections

Department of Mechanical Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

A MEMS based drug effect analysis system utilizing droplet microfluidics Özkan, Metin Dündar; Külah, Haluk; Yıldırım, Ender; Department of Electrical and Electronics Engineering (2018) This thesis proposes a fully integrated lab-on-a-chip system designed for drug effect analysis based on the droplet microfluidics. It is mainly designed for screening multi-drug responses of cells in an automated operation. The distinguished feature of the drug screening system is that it includes droplet-based single cell encapsulation. The system includes two main subsystems which are parylene-based and normally closed electrostatic microvalves and droplet generation system. The integration of microvalves...
A microfluidic device enabling drug resistance analysis of leukemia cells via coupled dielectrophoretic detection and impedimetric counting Demircan Yalçın, Yağmur; Töral, Taylan Berkin; Sukas, Sertan; Yıldırım, Ender; Zorlu, Özge; Gündüz, Ufuk; Külah, Haluk (2021-12-01) We report the development of a lab-on-a-chip system, that facilitates coupled dielectrophoretic detection (DEP-D) and impedimetric counting (IM-C), for investigating drug resistance in K562 and CCRF-CEM leukemia cells without (immuno) labeling. Two IM-C units were placed upstream and downstream of the DEP-D unit for enumeration, respectively, before and after the cells were treated in DEP-D unit, where the difference in cell count gave the total number of trapped cells based on their DEP characteristics. Co...
A Bayesian modeling and estimation framework for pharmacogenomics driven warfaring dosing Öztaner, Serdar Murat; Taşkaya Temizel, Tuğba; Erdem, Remzi; Department of Medical Informatics (2014) Recent studies have shown that the incorporation of genomics information into the drug dosing prediction formulations increases the accuracy of the drug dosing while decreasing the frequency of adverse drug effects. The current clinical approaches for drug dosing which are supported by the best pharmacogenomics algorithms explain only some percentage of the variance in dosing. The main objective of this study is to enhance the accuracy and efficacy of the warfarin dosing algorithms by using advanced methods...
Predicting the binding affinities of drug-protein interaction by analyzing the images of binding sites Erdaş, Özlem; Alpaslan, Ferda Nur; Büyükbingöl, Erdem; Department of Computer Engineering (2013) Analysis of protein-ligand interactions plays an important role in designing safe and efficient drugs, contributing to drug discovery and development. Recently, machine learning methods have been found useful in drug design, which utilize intelligent techniques to predict unknown protein-ligand interactions by learning from specific properties of known protein-ligand interactions. The aim of this thesis is to propose a novel computational model, Compressed Images for Affinity Prediction (CIFAP), to predict ...
A Hybrid geo-activity recommendation system using advanced feature combination and semantic activity similarity Sattari, Masoud; Toroslu, İsmail Hakkı; Department of Computer Engineering (2013) In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...

Citation Formats

E. Yıldırım and H. Külah, “A Droplet based Multi-Drug Screening System Controlled with Electrostatic Microvalves,” presented at the 16th International Conference on Miniaturized Systems for Chemistry and Life Sciences (28 Ekim - 01 Kasım 2012), Okinawa; Japan, 2012, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73239.