UCL invest in Postnova Analytics fractionation system to develop nanoscale drug delivery vehicles

Postnova Analytics reports on the recent investment by the Department of Chemistry at University College London (UCL) in an AF2000 Field Flow Fractionation System to assist them in their development of novel nanoscale vehicles for drug delivery.

Postnova Analytics AF2000

UCL has pioneered the engineering of novel nanoscale drug delivery vehicles which can be tuned to release a range of cargos. The drug delivery system is based upon the synthesis of self-assembled spherical polymer vesicles known as polymersomes. Polymersomes are biocompatible and stable making them ideal for the development of drug delivery systems.

Paul Clarke, Managing Director of Postnova Analytics (UK) Ltd. said "Researchers at UCL purchased the Postnova AF2000 system to work on the purification and characterisation of polymersomes being synthesised for the treatment of several diseases including cancer, infections and neurological disorders.

The project is part of a multidisciplinary effort aimed toward the design of personalised nanomedicines. We are delighted to provide UCL with an analytical tool that will assist them in their ground breaking work".

Having identified Field Flow Fractionation as the best technique to purify and characterise polymersomes we elected to purchase an AF2000 system from Postnova as it allows us to quantify the materials both in terms of size as well as shape. Such an effort is critical to both elucidate important structure/function relation as well as to expedite the necessary quality control associated with clinical translation."

Guiseppe Battaglia, Professor of Molecular Bionics, Chemistry Department, UCL


The Postnova AF2000 is a high performance Field Flow Fractionation (FFF) platform for separation of proteins, macromolecules and nanoparticles. Modular in design, the AF2000 incorporates the combined experience, expertise and technological advances from Postnova Analytics' nearly two decades of leadership in FFF.

Incorporating a range of FFF modules in a single integrated system to provide universal separation, the AF2000 offers more flexibility, better performance and more robust results than any system before.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Postnova Analytics. (2019, June 19). UCL invest in Postnova Analytics fractionation system to develop nanoscale drug delivery vehicles. News-Medical. Retrieved on November 21, 2024 from https://www.news-medical.net/news/20161205/UCL-invest-in-Postnova-Analytics-fractionation-system-to-develop-nanoscale-drug-delivery-vehicles.aspx.

  • MLA

    Postnova Analytics. "UCL invest in Postnova Analytics fractionation system to develop nanoscale drug delivery vehicles". News-Medical. 21 November 2024. <https://www.news-medical.net/news/20161205/UCL-invest-in-Postnova-Analytics-fractionation-system-to-develop-nanoscale-drug-delivery-vehicles.aspx>.

  • Chicago

    Postnova Analytics. "UCL invest in Postnova Analytics fractionation system to develop nanoscale drug delivery vehicles". News-Medical. https://www.news-medical.net/news/20161205/UCL-invest-in-Postnova-Analytics-fractionation-system-to-develop-nanoscale-drug-delivery-vehicles.aspx. (accessed November 21, 2024).

  • Harvard

    Postnova Analytics. 2019. UCL invest in Postnova Analytics fractionation system to develop nanoscale drug delivery vehicles. News-Medical, viewed 21 November 2024, https://www.news-medical.net/news/20161205/UCL-invest-in-Postnova-Analytics-fractionation-system-to-develop-nanoscale-drug-delivery-vehicles.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
White Paper: Separation and characterization of viruses and antibodies