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Tandem mass spectrometry is a powerful analytical tool used to characterize complex mixtures in drug discovery and other fields.
Now, Purdue University innovators have created a new method of applying machine learning concepts to the tandem mass spectrometry process to improve the flow of information in the development of new drugs. Their work is published in Chemical Science.
“Mass spectrometry plays an integral role in drug discovery and development,” said Gaurav Chopra, an assistant professor of analytical and physical chemistry in Purdue’s College of Science. “The specific implementation of bootstrapped machine learning with a small amount of positive and negative training data presented here will pave the way for becoming mainstream in day-to-day activities of automating characterization of compounds by chemists.”
Chopra said there are two major problems in the field of machine learning used for chemical sciences. Methods used do not provide chemical understanding of the decisions that are made by the algorithm, and new methods are not typically used to do blind experimental tests to see if the proposed models are accurate for use in a chemical laboratory.
“We have addressed both of these items for a methodology that is isomer selective and extremely useful in chemical sciences to characterize complex mixtures, identify chemical reactions and drug metabolites, and in fields such as proteomics and metabolomics,” Chopra said.
The Purdue researchers created statistically robust machine learning models to work with less training data—a technique that will be useful for drug discovery. The model looks at a common neutral reagent—called 2-methoxypropene (MOP) – and predicts how compounds will interact with MOP in a tandem mass spectrometer in order to obtain structural information for the compounds.
“This is the first time that machine learning has been coupled with diagnostic gas-phase ion-molecule reactions, and it is
AURORA, Colo. (KDVR) — The University of Colorado Anschutz Medical Campus in Aurora announced Tuesday the addition of new technology that researchers say could cut the screening time for new drug therapies in half.
Researchers say the new robotic screening and imaging technology could speed up the development of treatments for COVID, cancer or other diseases, while putting Colorado on the map in this field.
“Similar technologies exist on the coasts in academic institutions, but nothing in this region,” said Dr. David Ross, an associate dean at the CU Skaggs School of Pharmacy and Pharmaceutical Sciences.
He and his colleagues say the machine can take a library with thousands of compounds and quickly screen them against targets in a disease.
“If the disease model took two weeks to screen, we can now screen it in a couple of days,” said Dr. Dan LaBarbera, a researcher who will be using the equipment.
That speed could assist in the development of new therapies for cancer, cardiovascular disease, diabetes, Alzheimer’s and more.
“With this machine we can assist in the development of new therapies against COVID targets,” said Ross.
A new Center for Drug Discovery will be created at CU Anschutz and will focus on speeding up the research into new drugs and therapies.
Researchers say they are excited.
“It allows us to do innovative drug discovery right here in Colorado that rivals that of the big pharmaceutical companies,” LaBarbera said.
The technology is expected on campus by early next year. It was funded by the ALSAM Foundation.
Northwestern University researchers are casting a net for nanoparticles.
The team has discovered a new, rapid method for fabricating nanoparticles from a simple, self-assembling polymer. The novel method presents new possibilities for diverse applications, including water purification, diagnostics and rapidly generating vaccine formulations, which typically require many different types of molecules to be either captured or delivered at the same time.
Using a polymer net that collapses into nanoscale hydrogels (or nanogels), the method efficiently captures over 95% of proteins, DNA or small molecule drugs—alone or in combinations. By comparison, loading efficiency is typically between 5% and 20% for other nanoparticle delivery systems.
“We use a polymer that forms a wide net throughout an aqueous solution,” said Northwestern’s Evan A. Scott, who led the study. “Then we induce the net to collapse. It collects anything within the solution, trapping therapeutics inside of nanogel delivery vehicles with very high efficiency.”
“It works like a fishing net, which first spreads out due to electrostatic repulsion and then shrinks upon hydration to trap ‘fish,'” added
India’s drug authority last month approved a paper-strip test for Covid-19 that shows results in less than an hour, the head of the government institute that invented the test told CNN on Monday.
The test, called FELUDA—an acronym for FNCAS9 Editor-Limited Uniform Detection Assay—was named after a popular Indian fictional detective. It intends to “address the urgent need for accurate mass testing,” according to a statement from TATA Sons, which manufactured the test.
The kit could be manufactured for self-testing in the future, according to Agarwal, but the prototype being developed currently is only intended for testing in labs.
The FELUDA test follows a similar rapid test kit developed in the US this spring. Both tests use a gene-editing technology called CRISPR to detect the virus in a patient’s RNA. The US Food and Drug Administration approved the emergency use of the SHERLOCK test kit in May, developed by the Massachusetts Institute of Technology.
The test received approval for commercial launch by the Drugs Controller General of India, the country’s drug authority, on September 19. It had a 96% sensitivity and 98% specificity for detecting the novel coronavirus, meeting the Indian Council of Medical Research’s (ICMR) quality benchmark, according to a statement from the Ministry of Science and Technology. A test’s sensitivity indicates the likelihood of false negative results; its specificity indicates the likelihood of false positive results.
“This marks a significant achievement for the Indian scientific community, moving from R&D to a high-accuracy, scalable and reliable test in less than 100 days,” the Ministry of Science and Technology statement said.
The test “is simple to administer and easy to interpret, enabling results to be made available to the medical fraternity in relatively lesser time
VIENNA (Reuters) – India and South Africa want the World Trade Organization (WTO) to waive intellectual property rules to make it easier for developing countries to produce or import COVID-19 drugs, a letter https://docs.wto.org/dol2fe/Pages/SS/directdoc.aspx?filename=q:/IP/C/W669.pdf&Open=True to the WTO shows.
In their letter dated Oct. 2 the two countries called on the global trade body to waive parts of the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS), which governs patents, trademarks, copyright and other intellectual property rules globally.
“As new diagnostics, therapeutics and vaccines for COVID-19 are developed, there are significant concerns (over) how these will be made available promptly, in sufficient quantities and at (an) affordable price to meet global demand,” the letter posted on the Geneva-based WTO’s website says.
The two countries said that developing nations are disproportionately affected by the pandemic and that intellectual property rights, including patents, could be a barrier to the provision of affordable medicine.
The letter asks that the WTO’s Council for TRIPS recommends a waiver to the General Council, the WTO’s top decision-making body in Geneva, “as early as possible”. It does not say how much support India and South Africa have from other countries.
A draft General Council decision text submitted with the letter says the waiver should last an as yet unspecified number of years and be reviewed annually.
(Reporting by Francois Murphy; Editing by David Goodman)
Copyright 2020 Thomson Reuters.