Featured Research

from universities, journals, and other organizations

Predicting serious drug side effects before they occur

Date:
March 29, 2011
Source:
Inderscience Publishers
Summary:
All medications have side-effects from common aspirin to herbal remedies and from standard anticancer drugs to experimental immunosuppressants. However, predicting important side effects, serious adverse drug reactions, ADRs, is with current understanding almost impossible. However, a neural network technology trained with past data could give drug companies and healthcare workers a new tool to spot the potential for ADRs with any given medication.

All medications have side-effects from common aspirin to herbal remedies and from standard anticancer drugs to experimental immunosuppressants. However, predicting important side effects, serious adverse drug reactions, ADRs, is with current understanding almost impossible. However, a neural network technology trained with past data could give drug companies and healthcare workers a new tool to spot the potential for ADRs with any given medication.

Related Articles


Writing in the International Journal of Medical Engineering and Informatics, a team from the University of Medicine and Dentistry of New Jersey, has developed a new model that tests show is 99.87 percent accurate in predicting adverse drug reactions among 10,000 observations and 100 percent for non-serious ADRs.

Peng-fang Yen and colleagues Dinesh Mital and Shankar Srinivasan explain how obligatory warning labels on medication packaging often serve only to cause concern among patients, while products withdrawn from the market because of repeated ADRs repeatedly undermine the pharmaceutical industry. From the medical industry's point of view and the perspective of patients, this is a growing concern that might be remedied with new technology, saving lives, reputations and healthcare costs.

The Food Drug Administration (FDA) in USA and the World Health Organization (WHO) monitor the safety of medications continuously. However, technology that could identify possible ADRs at the earliest possible stage of drug development, licensing and marketing is urgently needed, especially given the potential risks to patients in emerging areas of healthcare and the potential risks to shareholder confidence.

The team's artificial neural network is a mathematical model of the biologic neural network embedded in computer software. It is trained by feeding in structural and physical data associated with known pharmaceutical products and any ADRs. A feedback loop discards those connections where a wrong prediction of a known outcome is made and as data are added the ANN builds up a network of correct "predictions." After sufficient training, the ANN can then be tested on another set of pharmaceuticals and outcomes checked against known ADRs. If confidence is sufficiently high, the ANN can be used to predict ADRs for new drugs.

The team has demonstrated an accuracy of 95 percent in preliminary tests and is now using a much larger data set of 10,000 drug molecules and ADR observations to train the ANN to a much more refined level.


Story Source:

The above story is based on materials provided by Inderscience Publishers. Note: Materials may be edited for content and length.


Journal Reference:

  1. Peng fang Yen, Dinesh P. Mital, Shankar Srinivasan. Prediction of the serious adverse drug reactions using an artificial neural network model. International Journal of Medical Engineering and Informatics, 2011; 3 (1): 53 DOI: 10.1504/IJMEI.2011.039076

Cite This Page:

Inderscience Publishers. "Predicting serious drug side effects before they occur." ScienceDaily. ScienceDaily, 29 March 2011. <www.sciencedaily.com/releases/2011/03/110328101313.htm>.
Inderscience Publishers. (2011, March 29). Predicting serious drug side effects before they occur. ScienceDaily. Retrieved December 18, 2014 from www.sciencedaily.com/releases/2011/03/110328101313.htm
Inderscience Publishers. "Predicting serious drug side effects before they occur." ScienceDaily. www.sciencedaily.com/releases/2011/03/110328101313.htm (accessed December 18, 2014).

Share This


More From ScienceDaily



More Health & Medicine News

Thursday, December 18, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Kids Die While Under Protective Services

Kids Die While Under Protective Services

AP (Dec. 18, 2014) As part of a six-month investigation of child maltreatment deaths, the AP found that hundreds of deaths from horrific abuse and neglect could have been prevented. AP's Haven Daley reports. (Dec. 18) Video provided by AP
Powered by NewsLook.com
UN: Up to One Million Facing Hunger in Ebola-Hit Countries

UN: Up to One Million Facing Hunger in Ebola-Hit Countries

AFP (Dec. 17, 2014) Border closures, quarantines and crop losses in West African nations battling the Ebola virus could lead to as many as one million people going hungry, UN food agencies said on Wednesday. Duration: 00:52 Video provided by AFP
Powered by NewsLook.com
When You Lose Weight, This Is Where The Fat Goes

When You Lose Weight, This Is Where The Fat Goes

Newsy (Dec. 17, 2014) Can fat disappear into thin air? New research finds that during weight loss, over 80 percent of a person's fat molecules escape through the lungs. Video provided by Newsy
Powered by NewsLook.com
Why Your Boss Should Let You Sleep In

Why Your Boss Should Let You Sleep In

Newsy (Dec. 17, 2014) According to research out of the University of Pennsylvania, waking up for work is the biggest factor that causes Americans to lose sleep. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:

Strange & Offbeat Stories


Health & Medicine

Mind & Brain

Living & Well

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins