First real-time detector for IV drugs may help eliminate medical errors

Sep. 19, 2013 — Today, computerized smart systems can deliver drugs intravenously in exact volumes to hospital patients. However, these systems cannot recognize which medications are in the tubing nor can they determine the concentration of the drug in the tubing. This lack of precise information can lead to medication errors with serious consequences.

Now, a new optical device developed by a team of electrical and computer engineering students at the University of Illinois at Urbana-Champaign (UIUC) can identify the contents of the fluid in an intravenous (IV) line in real-time, offering a promising way to improve the safety of IV drug delivery. The team, led by Prof. Brian T. Cunningham, interim director of the Micro and Nanotechnology Laboratory at UIUC, will present its work at The Optical Society's (OSA) Annual Meeting, Frontiers in Optics (FiO) 2013, being held Oct. 6-10 in Orlando, Fla.

The vulnerability of IV drug-delivery systems due to human error is a chief concern in hospital safety, Cunningham said. Errors can include incorrect dosage, unintentional substitution of one drug for another, and co-delivery of incompatible drugs.

"Up to 61 percent of all life-threatening errors during hospitalization are associated with IV drug therapy," Cunningham said, citing a recent report. "So for all the really good things hospitals can do, the data shows that mistakes can occasionally happen."

To approach this problem, Cunningham and colleagues turned to the very small -- to structures and processes at the nanoscale (one-billionth of a meter), where novel physical and chemical properties arise. The researchers use a technology called Surface-Enhanced Raman Scattering (SERS), a powerful analytical tool prized for its extreme sensitivity in obtaining molecular signals that can be used to identify chemicals. To determine the identity of a particular IV medication, researchers shine laser light onto a nanostructured gold surface that contains millions of tiny "nano-domes" that are separated from each other by as little as 10 nanometers. The nano-domes are incorporated into the inner surface of IV tubing, where they are exposed to drugs that are dispersed in liquid. They capture the light scattered from drug molecules that are in contact with the nano-domes and use SERS to determine the drug's molecular signature. Finally, they match the signature to known signatures for the drug in order to confirm the presence of a specific medication in the IV line.

While other groups have demonstrated excellent nanostructured surfaces for SERS, those developed by the Cunningham group are unique because they are inexpensively produced on flexible plastic surfaces by a replica molding process with nanometer scale accuracy.

Early data show that the Cunningham group's system can identify medications including morphine, methadone, phenobarbital, the sedative promethazine, and mitoxantrone, which is used to treat multiple sclerosis. The system is extremely sensitive: it can detect drugs in amounts 100 times lower than the clinically delivered drug concentrations commonly used. So far, the researchers have also shown their system can sense a two-drug combination, which has its own unique signature.

The next step is further evaluation for combinations of up to ten drugs being delivered at the same time. Computer algorithms are also being developed to automatically interpret the SERS spectra, and Cunningham's team reports that the system is now being evaluated for possible commercialization.

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Beyond peer review: Finding a way to manage errors in research data

Sep. 17, 2013 — Traditional peer review is not enough to ensure data quality amid the recent boom in scientific research findings, according to results of a 10-year collaboration between the National Institute of Standards and Technology (NIST) and five technical journals.

While production of research data is growing about 7 percent annually, about one-third of papers submitted to participating journals contained erroneous or incomplete chemical property data, according to a report by 32 authors from NIST and the collaborating journals. Poor data can lead to mistakes in equipment selection, over-design of industrial plant components, difficulty simulating and discovering new processes, and poor regulatory decisions, the report notes.

The traditional peer-review process is under pressure to work too fast to evaluate fully all new experimental data, the NIST-journal collaboration found. The authors' solution is a set of customized software tools and procedures for validating experimental data and eliminating errors after a paper is approved by peer review, but before a journal formally accepts the paper.

The collaboration focused on thermophysical property data used in chemical process technologies such as distillation, extraction and crystallization.*? Thermophysical properties include boiling and melting points, density, viscosity, solubility and many other physical values related to temperature, including those for mixtures. The study findings also may be of broad value to scientific data publishing in general.

"The solutions we offer, while centered on the field of thermodynamics, should be applicable in principle to other areas of science and engineering," says Michael Frenkel, a co-author of the new paper and leader of NIST's Thermodynamics Research Center.

Managing thermophysical property data is particularly challenging because some 100-year-old data remain useful today for engineering purposes. Efforts to establish data-reporting standards for this field began more than 50 years ago but could not succeed until recently, with the development of specialized computer hardware and software tools.

The collaboration cites a variety of factors contributing to poor data quality. Advances in measurement science have boosted data collection, but increased automation has resulted in the loss of personnel expertise and knowledge required to run manual systems. In addition, equipment manufacturers sometimes make invalid uncertainty claims. And word processing software, with functions such as cut-and-paste and "fill down" in spreadsheets, has led to many published errors. The most common problem found in papers analyzed by the collaboration was missing or underestimated uncertainties for reported data.

After several tries, the collaboration developed a rapid, cost-effective process for identifying and eliminating errors. NIST developed a new online tool (NIST ThermoLit) that allows researchers to generate a literature report containing relevant references retrieved from a NIST database. Researchers can combine this capability with an older experiment planning system (NIST ThermoPlan) at both the conceptualization and publication stages of their work. If the submitted paper passes a journal's peer review, NIST generates a report noting any inconsistencies between the new experimental data and critically evaluated data based on past research. Data are extracted from the submitted paper and validated by NIST's expert software system for data evaluation (NIST ThermoData Engine).

The NIST-journal collaboration plans to continue its work by refining and expanding the modeling and prediction tools in the expert system software.

*The five journals are Journal of Chemical and Engineering Data, Fluid Phase Equilibria, The Journal of Chemical Thermodynamics, the International Journal of Thermophysics and Thermochimica Acta.

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