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The current gold standard for the diagnosis of genetic disorders and infectious diseases involves the use of molecular methods for target gene detection through DNA/RNA amplification techniques. However, this requires a critical upstream step of extracting purified nucleic acid (NA) material from a variety of collected patient samples. This step can be easily performed through magnetic-based NAs extraction techniques which have recently replaced traditional spin-column approaches in diagnostic testing labs in the world. This is due to their enhanced capacity for directly isolation NAs from crude samples such as blood, stool, tissue homogenates, and cell culture media, without the need for additional pre-purification or centrifugation steps, and their amenability for high throughput automated sample processing. However, magnetic-based techniques required the preparation of superparamagnetic iron oxide particles, which currently require long synthesis protocols with low throughput and costly reagents. These and other Green chemistry considerations make them costly and difficult to produce on a large scale. Herein we propose the use of a microwave promoted syntheses in combination with Galenvs’ proprietary Machine Learning algorithms to generate a highly optimized synthesis route, and a post chemical functionalization of MNPs optimized for NAs extraction from different matrices using Galenvs buffer formulations.
Scott Bohle
Benita Kapuku
Galenvs
Chemistry
Professional, scientific and technical services
McGill University
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