High-throughput preparation of hexagonally ordered mesoporous silica and gadolinosilicate nanoparticles for use as MRI contrast agents

Nicholas M K Tse, Danielle F. Kennedy*, Bradford A. Moffat, Nigel Kirby, Rachel A. Caruso, Calum J. Drummond

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The development of biomedical nanoparticulate materials for use in diagnostics is a delicate balance between performance, particle size, shape, and stability. To identify materials that satisfy all of the criteria it is useful to employ automated high-throughput (HT) techniques for the study of these materials. The structure and performance of surfactant templated mesoporous silica is very sensitive to a wide number of variables. Variables, such as the concentration of the structure-directing agent, the cosolvent and dopant ions and also the temperature and concentration of quenching all have an influence on the structure, surface chemistry, and therefore, the performance of the mesoporous silica nanoparticles generated. Using an automated robotic synthetic platform, a technique has been developed for the high-throughput preparation of mesoporous silica and gadolinium-doped silicate (gadoliniosilicate) nanoparticulate MRI contrast agents. Twelve identical repeats of both the mesoporous silica and gadolinosilicate were synthesized to investigate the reproducibility of the HT technique. Very good reproducibility in the production of the mesoporous silica and the gadolinosilcate materials was obtained using the developed method. The performance of the gadolinosilicate materials was comparable as a T 1 agent to the commercial MRI contrast agents. This HT methodology is highly reproducible and an effective tool that can be translated to the discovery of any sol-gel derived nanomaterial.

Original languageEnglish
Pages (from-to)443-450
Number of pages8
JournalACS Combinatorial Science
Volume14
Issue number8
DOIs
Publication statusPublished - 13 Aug 2012
Externally publishedYes

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