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An implantable robot is capable of treating a rare birth defect in infants through tissue stimulation.

 Researchers from the University of Sheffield and Boston’s Children Hospital at Harvard Medical School have created a device designed to aid in treating esophageal atresia, a defect which occurs when the upper and lower parts of the esophagus don’t connect.

The prototype device is a robotic implant that attaches to the patient’s esophagus and stimulates cells by pulling tissue with an incorporated motor. Its function is similar to that of the Foker technique—a correction of esophageal atresia in which doctors manually pull tissue using sutures over an extended period of time.

The implant capable of monitoring and applying appropriate tissue traction using 2 types of sensors to measure tissue tension and displacement. Its power comes from a control unit attached to a vest outside of the patient’s body, allowing doctors to monitor patients at any time.

Common treatment for the defect calls for patient sedation, in order to ensure the applied sutures do not tear. Developers hope the device will free babies to movement and interaction while undergoing treatment, relieving stress for involved family members.

Esophageal atresia currently affects about 1 in every 4,000 babies born in the US and Europe.

Dana Damian, PhD, from the Department of Automatic Control and Systems Engineering (ASCE) at Sheffield, said the Foker procedure is widely accepted for treating the condition, though experts are uncertain how much force should be applied to lengthen tissue.

“Although the technique is one of the best standards, sometimes the sutures surgeons attach to the esophagus can tear which can result in repetitive surgeries or scar tissue can form that can cause problems for the patient in the future,” Damian said.

Such an issue is overcome with the device, as its sensors allows constant monitoring and adjustments to the applied force of tissue lengthening.

Early research has shown that cells multiply in response to the pulling action, giving health care experts a better understanding of mechanical stimulation’s potential for tissue growth. Sheila MacNeil, PhD, Professor of Tissue Engineering in the Department of Materials Science and Engineering at the University of Sheffield, said increased knowledge on the subject has been needed for some time.

“Doctors and researchers understand that tissues will normally grow in response to traction forces, for example this occurs naturally during pregnancy as the growing baby increases the pressure inside the mother, the abdominal wall and skin increase in area to relieve the tension generated from stretching these tissues,” MacNeil said.

MacNeil called the robotic implant a breakthrough in applied tissue-response knowledge. Damian, responsible for designing a functioning robot for a technology-hostile environment, called it the just first step in the field.

“We have made a device that can provide long-term control of the tissue growth using on-board medical expertise,” Damian said. “We further want to look at other tubular tissues, such as the intestine and the vascular system, to see if this sort of technology can be used to help with other conditions, such as Short Bowel Syndrome."

Articles

The robot uses sensors and a motor to control tissue growth in infants.

Robotic Implant Treats Esophagus Birth Defect

Following in the footsteps of GlaxoSmithKline’s rheumatoid arthritis study, another pharmaceutical company is hoping to leverage Apple’s ResearchKit platform for clinical insights, this time on multiple sclerosis (MS).

The Novartis study, dubbed Evaluation of Evidence from Smart Phone Sensors and Patient-Reported Outcomes in Participants with Multiple Sclerosis or elevateMS for short, is intended to help researchers conduct a data-based study of the everyday machinations and effects of multiple sclerosis (MS).

The study will feature a downloadable mobile app, available in the App Store, that will collect patient questionnaire responses, passive and active sensor-based movement data, and performance tasks completed by patients.

Advocates, neurologists and patients were gauged on the app’s interface, utility and intent prior to its release. In an email, Novartis said that the intent of a mobile research study is to develop new patient-centric clinical research endpoints — differing from conventional testing of MS symptom burdens.

“These assessments can feel unrelatable when viewed from most patients’ perspectives,” the company said. “We need to get better at measuring the things that really matter to patients, like how well they can function physically and cognitively during their everyday lives, outside of the clinic.”

The app and study collection is available to both MS patients and non-patients, and participants have the right to leave the study anytime they would like. Though a major focus of the study is to analyze how treatments and medication are affecting actual patients in their daily lives, there’s still importance for civilian input.

“We are hoping that several thousand MS patients participate,” the company said. “We also need people without MS to participate — all of the data helps us. Based on other experiences with the Apple ResearchKit platform, we expect about one-third of the participants to be MS patients.”

Such real-time MS tracking via app has been planned by Novartis for over a year, but the desire to research the day-to-day effects of a neurological condition has been long-held.

“As physicians, we always want to know how our patients with MS are doing on the treatments we prescribe,” Stanley Cohan, MD, PhD, medical director of Providence Multiple Sclerosis Center, Portland, Oregon, said in a statement. “With the elevateMS app, study participants can frequently document their symptoms in a personal health story.”

The company says that user privacy is ensured, as every participant’s data will be delivered under an anonymous, random code.

ResearchKit has been a mixed bag for Apple so far. Released to fanfare, the potential of a mobile research platform is inherent, but interest decay and Apple exclusivity have proved hindrances. The demographics of iPhone ownership often do not represent disease prevalence: while iPhone owners are predominantly white, a 

 the incidence of MS higher in black patients.

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Novartis Launches ResearchKit Study for MS

Influenza is a constantly moving target for vaccination, and it always holds the potential to spread quickly. A new study found that predictive modeling may add a layer of protection against the common, but potentially dangerous, virus.

Using test reimbursement data made available from the Centers for Medicare and Medicaid Services (CMS), researchers — led by Rex Astles, PhD, coordinator at the Center for Disease Control (CDC) Division of Laboratory Systems in Atlanta, GA &mdash; an algorithm that can calculate predicted weekly volumes of both flu tests and diagnoses. The study, presented at the 69th American Association for Clinical Chemistry (AACC) Annual Scientific Meeting & Clinical Lab Expo in San Diego, CA, this week, used Medicare outpatient claims between 2007-2012.

Influenza episodes were defined by increases in predicted volume surpassing a certain standard deviation, followed by similar drops in volume. To compare detected flu episodes with those defined, the team used positive rapid flu test volumes from the CDC’s National Respiratory and Enteric Virus Surveillance System (NREVSS).

In the preliminary data, 67 influenza episodes were detected with the NREVSS. The team’s established algorithm wasn’t far from base — predicted weekly volumes of flu tests caught 64 (95.5%) of the episodes, and predicted weekly volumes of diagnoses caught 60 (89.5%). Additionally, the algorithm-based data was able to identify influenza active about 3 weeks earlier than NREVSS data been.

Though the data was closely accurate, it is only the results of data from 10 monitored states in the study. Researchers noted detection via CMS claims data would be effective in detecting influenza activity in "specific regions of the US."

Astles theorized the newfound approach could help augment the current standard of influenza tracking — not replace it.

“Our work showed that it is theoretically possible to use the simple fact that a test was ordered and performed as a means of detecting early respiratory disease activity,” Astles said.

The hope moving forward for the research is that it could be further implemented by larger healthcare systems with more vast administrative data sets, Astles said.

“This could be especially helpful for other diseases that have less effective surveillance systems,” Astles said. “Comprehensive surveillance has many purposes, only one of which is detection of apparent disease activity. This detection could be a signal that more intensive surveillance, including testing patient specimens to identify the circulating viral or bacterial strain, should be initiated.”

B-085 - Evaluation of the Utility of CMS Claim Data for Early Detection of Increasing Influenza Activity

," was made available on the AACC website, and the team released a 

A version of this story originally appears in 

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Kevin Kunzmann

Articles

Robotic Implant Treats Esophagus Birth Defect

Novartis Launches ResearchKit Study for MS

An Algorithm for Flu Outbreak Detection