Same Names, New Way to Create Drugs
Producing a drug that can be tested on humans can take decades and cost billions, and finding a potential candidate to test that drug can take just as long. What would be the odds that a process for tackling those tasks much more efficiently would be devised by two identically named, yet unrelated, people? As unlikely as that sounds, tech startup twoXAR fits that bill.
twoXAR Inc. is developing an algorithm that can search through the multitudes of drug candidate data, an IEEE Spectrum article reports. The company was founded by Andrew A. Radin, CEO (left), and Andrew M. Radin, chief business officer (right). The biotech company has been working with research institutions and biopharma companies to determine what drugs are most likely to be successful in testing as specific disease therapies, Spectrum reports.
Instead of selling their software to pharma companies, they are building their own repository of drug candidates. “Drug discovery to date has been the reverse of Moore’s Law; it is becoming logarithmically more difficult to find a new drug and the costs keep going up,” Andrew A. told Spectrum.
Add A Pinch of Bone for the Perfect Mix
If you were wondering, the perfect mixture for creating the framework for filling in missing bone is at least 30 percent pulverized natural bone; throw in manmade plastic and a 3-D printer and you have the ideal bone replacement, according to a Johns Hopkins Medicine news release.
A reported, 200,000 people require replacement bones in the head or face each year, and the most common treatment involves removing a portion of the patient’s fibula, cutting it to shape and implanting it. Not only does this damage the leg, but the fibula can’t be perfectly shaped to fit the curves of the face, Johns Hopkins reports.
These 3-D printed versions are made using a fascinating formula but, just so you know, the pulverized bone is made of porous bone from inside cows' knees, stripped of all cells. You can’t say health care isn’t creative.
Anything Your Machine Can Do, Mine Can Do Better
Researchers may be gloating about the intelligence of their machines since Cincinnati Children’s Hospital Medical Center started using “machine-learning” tech to teach computers to predict if patients will partake in clinical trials, ScienceDaily reports.
Participant recruitment is a challenge that often impacts clinical trial results and puts a stop to some studies completely. The automated algorithm is expected to boost clinical trial acceptance rates from 60 to 72 percent.
“The ultimate goal of our research is to impact patient recruitment strategies to increase participation in clinical trials, and to help ensure that studies can be completed and the data are meaningful,” said Yizhao Ni, lead author and researcher in the Division of Biomedical Informatics at Cincinnati Children’s.
Look Ma, No Wires
Wireless tech is everywhere, and the hospital is no exception. EarlySense, a sensor about the size of a magazine can be tucked under a patient’s bed padding or in a seat cushion to wirelessly monitor signals from the body.
For example, the device can detect the vibrations when a patient’s heart contracts; the accompanying patient monitor interpolates that as a cardiac cycle then tracks motion levels.
EarlySense makers say it could be especially helpful for caregivers in rehab centers and skilled nursing facilities.
Company President Tim O’Malley says cllnical evidence shows that continuous monitoring by devices like his and others are useful in monitoring medical conditions and preventing falls.
