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breast cancer (2)

Gold Level Contributor

Jacob Bell / BioPharma Dive

The latest batch of breakthrough device designations from FDA support an array of medtech innovations, from a novel treatment for sleep apnea to a tissue regeneration technology designed to aid spinal cord injury patients. Several technologies designated within the past month are diagnostics, with two targeting breast cancer and one designed to improve the diagnosis of a deadly gastrointestinal condition in premature infants. 

FDA's Breakthrough Devices Program aims to speed development and review of technology that could offer a better treatment for life-threatening or debilitating disease.

D Path last week said it received a breakthrough designation for a computer-aided diagnostic platform that uses digitized histopathology images to better determine breast cancer characteristics such as invasiveness and grades. The software-as-a-medical-device platform is designed to make clinical grade predictions from breast biopsy and resection images to improve diagnostic accuracy.

According to the Newton, Massachusetts-based company, the device reduces the error rate on biopsies obtained before surgery from 20% to less than 5%. The technology incorporates statistical physics and tumor biology to identify digital cancer biomarkers, aiding in treatment selection.

On the same day that 4D Path announced its breakthrough device designation, Lumicell, a fellow Newton medtech, said it received FDA's drug center's fast-track designation for its LUM imaging system to detect and remove cancerous tissue in the treatment of breast cancer. Lumicell said it received the special status with rolling review by FDA, augmenting its previously granted breakthrough device designation for breast cancer and all solid tumors.

The system allows surgeons to see and remove residual cancer in real-time, focusing on the cells left behind in the surgical cavity rather than on the lumpectomy specimen, with the aim to reduce the risk of second surgeries and cancer recurrence. Lumicell said it is continuing enrollment in its breast cancer pivotal trial and, with rolling review, will be able to submit modules for a New Drug Application with FDA as they are ready.

Also in mid-November, Louisiana State University announced that a technology to diagnose necrotizing enterocolitis, an often fatal condition in premature infants, gained a breakthrough device designation. Called NECDetect and invented by professor Sunyoung Kim, the noninvasive biomarker test is performed on stool samples. There is no clinical test that has been established as the gold standard to diagnose NEC. The new test identifies 93% true positives and 95% true negatives, according to LSU. Kim has started a spinout company to further develop and commercialize the product.

Originally published by
Susan Kelly | November 24, 2020
Medtech Dive

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Silver Level Contributor

Toronto-based Perimeter Medical Imaging wants to make breast conservation surgeries more efficient by combining an optical coherence tomography device with an AI engine to reduce the number of repeat surgeries required.

The possibility of repeat surgeries to remove cancer from women diagnosed with breast cancer is a reality of breast conservation surgery. In the U.S. about 25 percent of women need additional surgery after a lumpectomy, which is done to preserve breast tissue after an initial breast cancer diagnosis.

This is because, following a lumpectomy after which the patient is sent home, a pathologist’s report days or weeks later may find cancer at the margins of the excised breast tissue. And that positive margin means the patient has to undergo another surgery to fully remove cancer or undergo a full mastectomy. All of which is emotionally taxing for patients.

“They trust their surgeon that they are going to remove it and it’s a very difficult phone call that the surgeon has to make to the patient to say ‘I missed some of the cancer, so you have to come back for a surgery.'” said Andrew Berekely, co-founder of Perimeter Medical Imagine a Toronto startup that is developing an AI-powered solution to the problem of repeat breast cancer surgery. “That’s not a phone call that surgeons like to make.”

Perimeter Medical went public in a reverse takeover of a public company this week and is expected to start trading on the TSX Venture Exchange in Canada on July 6. The company raised private capital of C$10 million (about $7.3 million) from investors including Roadmap Capital, shareholders of the public company it took over and high net worth people. Perimeter Medical has also received a $7.4 million grant from the Cancer Prevention and Research Institute of Texas, according to Berkeley. The company has its U.S. offices in Dallas.

The technology that Perimeter hopes to commercialize includes a medical device that can perform optical coherence tomography (OCT) on excised breast tissue and then feed that imaging data into its AI engine to determine whether the margin is positive – in other words, does the tissue in the margins contain cancer. That real-time information can help to determine whether the surgeon needs to take out more of the breast tissue thereby perhaps reducing the chance of another surgery down the road.

“The OCT is used to scan the back of your eye which is a 1 cm area. We have adapted the technology to scan very large complex surfaces like a removed tissue specimen in a very fast amount of time and give information back in the operating room where it is a time-sensitive situation …,” Berkeley said.

That fast turnaround will be powered by the AI engine.

“We have custom-built machine learning algorithms specifically for OCT that are specifically trained on breast tissue and this is years worth of working and selecting clinical data. What we do is that we image the tissue and then we take the post-operative pathology – what the pathologist looks at under the microscope — and we do what’s called a correlation,” he explained. “So we take the exact same area [that a pathologist finds] when they see tissue under the microscope, [and] we can go back to the same area in the images and we label in our images what disease looks like and we feed that into the ML algorithm and the more we do that the better it gets at identifying new diseases.”

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Originally published by
Arundhati Parmar | July 2, 2020
MedCity News

 

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JAAGNet MedTech Trends

LSI 2021 EMERGING MEDTECH SUMMIT

MedTech Strategist - Innovation Summit Dublin

BIOMEDevice - Boston 2021

  • Description:

    BIOMEDevice - Boston 2021
    https://biomedboston.com/

    Rescheduled to May 2021

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  • Created by: Kathy Jones
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MED-TECH INNOVATION SUMMIT

  • Description:

    MED-TECH INNOVATION SUMMIT
    https://med-techexpo.com/event/en/page/home

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