Purdue Chemists Divide And Conquer For High-throughput Analysis

An improved method for identifying and investigating the properties of liquid chemicals with nuclear magnetic resonance (NMR) is paying dividends of time and money in the lab of Daniel Raftery. His team runs several small samples through their NMR device in parallel rather than using a single, large sample, cutting both the time and sample quantity required for analysis. The technique could have an economic impact on the many industries that depend on such data.

"This technique should change the way people think about NMR as an expensive, time-consuming technology," said Raftery, who is associate professor of chemistry in Purdue's School of Science. "Users should now be able to consider it a cost-effective way to analyze their samples for faster product development, whether they have only a few compounds or entire libraries of them."

The article on Raftery's technique appeared in Wednesday's (10/1) issue of Analytical Chemistry.

NMR is invaluable to most industries that manufacture products from chemicals – many foods, pharmaceuticals and petroleum distillates are dependent on raw materials whose chemical properties are thoroughly understood on the molecular level. Physicians often base their clinical analyses on NMR data, and a university chemistry experiment generally requires the use of an NMR facility on campus.

"An NMR device is an essential piece of equipment in a modern chemistry lab," Raftery said. "But while they are indispensable, they are also very expensive, costing around $300,000 apiece. This often makes them a bottleneck in the analysis process. A lab frequently can afford only one, and when you have many people waiting to use it, the work can back up very quickly."

A standard NMR test can take two to five minutes and requires about 200 microliters of sample liquid. Raftery's technique cuts the time requirement to 30 seconds and streamlines the process further by using roughly 20-microliter samples.

"Using the parallel analysis technique, we can cut the time and sample requirements by as much as a factor of 10," Raftery said. "This will not only mean that samples can be analyzed more quickly, but that a scientist will not need to produce as much of a compound before it can be tested."

Raftery said these factors could positively impact the pharmaceuticals industry, which must test large batches of samples to find the most promising candidates for drug development.

"This technique could mean that nearly 100 samples could be tested in an hour," he said. "It could allow faster verification of drug products."

Raftery said that while other commercial analysis techniques were improving as well, his group's efforts had potential for additional refinement.

"Our method could be improved upon in additional ways to increase the speed and reduce the sample size further," he said. "We are now exploring these possibilities. The parallel analysis technique has not even been commercialized yet, and I think it has great potential for the future."

This research was funded in part by the National Science Foundation.