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Idaho State University

Pharmaceutical research at Idaho State University leads to discovery of link between adverse drug events and multidrug therapies

By Lee Ann Hancock, Director of Divisional Marketing | June 11, 2019

Invention of breakthrough computational formula aids in discovery

Pharmaceutical research at Idaho State University leads to discovery of link between adverse drug events and multidrug therapies
A research team at ISU-Meridian, led by Danny Xu (far right) and Vaughn Culbertson (second from right) shows off an award received in 2017.

MERIDIAN – Researchers at the  Idaho State University College of Pharmacy are laying the foundation necessary to diminish adverse drug effects that can occur in patients taking multiple medications.

Pharmacy researcher Vaughn Culbertson and Danny Xu, director of the College of Pharmacy Biomedical and Pharmaceutical Sciences Graduate Programs, used a new computational, large data approach to demonstrate a correlation between patients prescribed multiple medications and those who report adverse effects. Their innovative approach could lead to better outcomes for the large number of patients who require multidrug therapies.

It is relatively common for people to be prescribed a number of medications to target specific diseases or problems. Armed with more than 50 years of experience working in the biomedical and pharmaceutical industries, Culbertson and Xu know that drugs often interfere with each other.

Culbertson says that by using pharmacokinetics, which is simply defined as the study of how the body receives and processes drugs, researchers have already identified thousands of known drug interactions. However, only a handful of drug interactions have been identified based on pharmacodynamic processes, or the study of where and how drugs affect the body.

He said there is no revealing scientific, rigorous, or objective measurement of how drugs from different pharmacodynamic drug classes that often act at the same pharmacodynamic targets may interact in patients that are taking multiple medications.

 “For example antidepressants, anti-seizure, antipsychotics and some pain medications, may have some overlap in the target areas of the body where they act, and could accumulate and essentially result in a higher incidence of adverse drug events,” Culbertson said. “That is the clinical question: ‘how can we measure the effects of two drugs that interact at the same receptor site in the body, and can we actually measure the increased incidence of adverse drug events as a result of that?’”

Drawing on Culbertson’s extensive clinical experience and Xu’s expertise as a computational chemist, the researchers created a formula and methodology to identify and analyze drugs that Culbertson has found in clinical practice to be potentially interactive, in comparison to some of the adverse effects reported by patients.

These side effects include confusion, agitation, diarrhea, and other commonly known side effects. Using a large medical claims database of about 1 million patients for the study, the team assigned a score to the number of pharmacodynamic targets in each patient’s prescribed medication regimen and counted the number of potential adverse effects reported. They found that as they added the score and combinations of drugs, as the score increased, the adverse effects similarly increased.  

Culbertson says the goal of this preliminary study was to determine if an increased number of prescription drug targets indicated an increased number of adverse drug events, and their hypothesis was correct: the answer was yes. The ultimate goal of the researchers is to eventually introduce a system that helps decrease and/or eliminate the prescribing of combinations of drugs with known negative side effects.

Often when a clinician sees a patient, they may be treating what they think is disease or illness, not realizing it's actually an adverse drug effect. Many clinicians know this is a present issue, but currently there is no way to quantitate it or identify risk levels with different drugs and combinations of drugs.

“While we are aware of some adverse interactions between medications, we want to be able to measure exactly how medications will interact based on each individual patient,” Culbertson said.

He believes there is a substantial need for a solution to this issue, stating “over the spectrum there may be millions of patients with undetected cumulative adverse drug effects.”

The team hopes to design a way for pharmacists and physicians to predetermine side effects patients may suffer if taking certain medications, and as a result, prevent that from happening. The hope is to ultimately create a computer program where pharmacists and physicians can input various medications for a patient and it will output scores that indicate whether a patient is at low and high risk for adverse drug effects.

“A database such as this has potential for enormous cost savings, if we can prove drugs are creating adverse effects that have been going undetected or misdiagnose,” Culberston said.

According to a 2012 article in the PharmacoEconomics journal, these preventable adverse effects compose between 43.3% and 80% of all adverse outcomes that lead to hospital visits, therefore increasing healthcare costs.

While this is a preliminary study, Xu and Culbertson say their tests of the concept appear to have potential clinical application and their findings suggest that further research needs to be done. Currently, they are in the process of designing more specific research designs and clinical questions to provide answers to those questions. They’ve began building an evidence base but it will take time. Their findings thus far have confirmed that this is a definite possibility to successfully address the ongoing issue of adverse drugs effects and the team plans to continue to research this exciting potential.

The full original research article was recently published in the Pharmacotherapy Journal produced by the American College of Clinical Pharmacy (ACCP). It can be viewed at https://accpjournals.onlinelibrary.wiley.com/doi/10.1002/phar.2215.

 

 

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