Automation in biotechnology – active ingredient analysis on brain tissue

Automation in biotechnology – active ingredient analysis on brain tissue Purpose – Introduction of an automated laboratory system for a new field of laboratory operation, namely cultivation and handling of live brain tissue. Design/methodology/approach – The company's expertise in manual throughput was transferred to automatable methods. Processing data is used for scheduling purposes to yield efficient production of results. Findings – Automated process has comparable survival rates and high reproducibility. Time tolerance is lower than for manual operation. Research limitations/implications – Several bottle necks of the system have been identified and are to be improved upon in future research. These are especially “handling of membrane inserts” and slow‐running procedures. Practical implications – Cataloging of activity data (timestamps, parameters, etc.) allows for much easier statistical analysis and data‐mining than with manual operation data. Originality/value – Tissue‐based, high‐throughput screening is a seminal field in laboratory automation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sensor Review Emerald Publishing

Automation in biotechnology – active ingredient analysis on brain tissue

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Publisher
Emerald Publishing
Copyright
Copyright © 2005 Emerald Group Publishing Limited. All rights reserved.
ISSN
0260-2288
DOI
10.1108/02602280510620835
Publisher site
See Article on Publisher Site

Abstract

Purpose – Introduction of an automated laboratory system for a new field of laboratory operation, namely cultivation and handling of live brain tissue. Design/methodology/approach – The company's expertise in manual throughput was transferred to automatable methods. Processing data is used for scheduling purposes to yield efficient production of results. Findings – Automated process has comparable survival rates and high reproducibility. Time tolerance is lower than for manual operation. Research limitations/implications – Several bottle necks of the system have been identified and are to be improved upon in future research. These are especially “handling of membrane inserts” and slow‐running procedures. Practical implications – Cataloging of activity data (timestamps, parameters, etc.) allows for much easier statistical analysis and data‐mining than with manual operation data. Originality/value – Tissue‐based, high‐throughput screening is a seminal field in laboratory automation.

Journal

Sensor ReviewEmerald Publishing

Published: Dec 1, 2005

Keywords: Automation; Robotics; Biotechnology

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