Korea has emerged as a "technology powerhouse" as the nation is seeing new innovative startups that are working on visualizing the once futuristic technology to real life. Korea Biomedical Review met with innovative CEOs from various healthcare startups to hear about their company and what they believe is going on in Korea's dynamic healthcare startup scene. The first guest is Kim Sun-woo, CEO of Deep Bio. – Ed.

 

Korea’s artificial intelligence-based medical equipment manufacturers have increased their global presence based on superior technologies.

Many companies use AI platforms to diagnose cancer. However, Deep Bio wants to set it apart by diagnosing prostate cancer using AI for the first time in Korea.

In April last year, Deep Bio became the first company to receive approval from the Ministry of Food and Drug Safety for an AI-based medical device that diagnosis prostate cancer -- DeepDx-Prostate. This in-vitro diagnostic software helps doctors diagnose prostate cancer.

Deep Bio was the first AI medical device maker that diagnoses cancer with biopsy images in the pathology department. There are no AI medical devices diagnosing prostate cancer that has received approval from the FDA. However, with a high unmet need in the field, Deep Bio’s technology has already received recognition worldwide, according to the company.

The company has participated in the United States and Canadian Academy of Pathology (USCAP) every year since 2018 and published papers each year. This year, the company has published four articles.

Korea Biomedical Review met with Deep Bio CEO Kim Sun-woo to learn more about DeepDx-Prostate and its plans.

 

Deep Bio CEO Kim Sun-woo explains how his company’s devices help doctors make quicker and more accurate diagnoses in a recent interview with Korea Biomedical Review at the company’s headquarters in Guro-gu, Southwestern Seoul.
Deep Bio CEO Kim Sun-woo explains how his company’s devices help doctors make quicker and more accurate diagnoses in a recent interview with Korea Biomedical Review at the company’s headquarters in Guro-gu, Southwestern Seoul.

 

Question: A solution for diagnosing prostate cancer with digital images seems unusual. Please explain how DeepDx Prostate operates.

Answer: To diagnose prostate cancer, hospitals conduct prostate-specific antigen (PSA) testing.

Suppose the patient has a high PSA level and the physician gives an opinion of prostate cancer. In that case, the hospital removes the tissue with a needle biopsy. The pathologist observes the cells to confirm whether it is cancer or not. If it is cancer, they indicate the severity according to the Gleason Score.

However, there is a limit to what pathologists can do due to the size of the data.

DeepDx Prostate, developed by learning the images diagnosed by a pathologist, is prostate cancer diagnosis assistance software.

It analyzes whole slide imaging of digitized H&E-stained prostate needle biopsy specimens to determine the presence of cancer, and the severity of cancer with Gleason scores 3-5.

The company has verified the performance of DeepDx Prostate through various angles, and our product has proven very good performance compared to the reference standards made by pathologists at multiple hospitals, including the Seoul National University Hospital.

Last year, DeepDx Prostate became the first AI medical device in Korea to obtain a grade 3 in vitro diagnostic medical device approval from the Ministry of Food and Drug Safety as auxiliary software for cancer diagnosis through artificial diagnosis.

In developing the software, the company used thousands of sheets at the time of approval, and we are still adding more data.

As of June this year, the company has also added more than 500,000 core images from the U.S. as quality control.

 

Q: What advantages does DeepDx Prostate have over conventional prostate cancer screening? Are treatment methods and options also provided?

A: Currently, pathologists conduct prostate cancer diagnosis by looking at the tissue under a microscope to find out how much cancer is in the entire tissue.

When they find cancer, they divide it into a score of 1-5 according to the cancer pattern and calculate the Gleason score.

The Gleason score is the sum of the two patterns occupying the most and the next largest portion of cancer tissue. As patterns one and two are similar to normal cells, hospitals usually consider patterns above three significant.

However, the treatment method is still different for patterns 3-5.

Therefore, it is important to measure the Gleason grade accurately. However, unlike X-rays, which have a size of 1000x1000, the pathological image is very large, with an area of ​​150,000x100,000.

Observing this image with the naked eye through a microscope takes a long time and is difficult to distinguish clearly, so different pathologists sometimes diagnose the same cancer tissue differently.

Since the treatment method may be different in each case, there was a high unmet need for an additional diagnostic tool to increase the agreement between pathologists.

The company believes that artificial intelligence can be the solution to these problems.

We are currently conducting a related study with a medical school in the U.S., and the results are coming out that our AI measures more accurately than the naked eye.

In terms of treatment, the company plans to conduct global clinical trials in the future.

 

Q: Is DeepDx Prostate being used in the US? What is the FDA approval timeline?

A: Currently, several CLIA (Clinical Laboratory Improvement Amendments) laboratories in the United States have been using DeepDx Prostate d for quality control since last year.

Notably, the company has signed a commercial partnership with Lumea, a digital pathology solution company in the U.S., and has provided products since March of this year.

We have also been receiving commercial rights for image use and are using them for product development.

Analyzing pathological images using AI is a new field, and no company has yet received FDA approval.

Therefore, we are preparing the process by carefully organizing the data, and we plan to submit the licensing data to the FDA within this year. If that happens, I think the licensing schedule will become visible sometime next year.

 

Q: Have you received any feedback from pathologists who have used DeepDx Prostate?

A: In the U.S., DeepDx Prostate provides metrics such as the presence or absence of cancer, the Gleason grade, the percentage of cancer, and the size of the tissue and cancerous tumor.

Many researchers have evaluated this as very useful and reducing the burden of a diagnosis. For example, it can show cancer that occupies a small area of large size of the entire pathology image with a single click, thereby reducing errors that individuals miss while observing with the naked eye.

 

Q: Are there any additional products under development after DeepDx Prostate?

A: We are developing an AI software for diagnosing breast and bladder cancer.

Notably, for breast cancer, we are developing a product that detects lymph node metastasis. When performing breast cancer surgery, hospitals check for metastases in the nearby sentinel lymph node, and if there are metastases, they remove them altogether.

We are also expanding our product portfolio for prostate cancer.

The company has developed software that detects cancer by analyzing samples collected through transurethral resection of the prostate, performed on patients with benign prostatic hyperplasia at a commercial level, and is preparing for licensing procedures.

Also, the software related to whole-mount specimen analysis is showing good performance, so it is in the process of commercialization.

 

Q: What are the short- and long-term goals for Deep Bio?

A: The short-term goal is to generate meaningful revenue by successfully commercializing DeepDx Prostate in the U.S. market.

The long-term goal is to provide a companion diagnostic tool for disease prognosis and treatment through pathological image analysis.

We will provide opportunities for high-risk patients through active treatment while helping improve patients' quality of life by avoiding overtreatment and reducing side effects for low-risk patients.

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