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Docbot CEO highlights how AI can be applied to gastrointestinal image analysis

Docbot CEO Andrew Ritter talked about how the predictive analytics business seeks to shake up how clinicians diagnose gastrointestinal disease by changing the way medical images are analyzed.

In an interview, Docbot CEO Andrew Ritter talked about how the predictive analytics business seeks to shake up how clinicians diagnose gastrointestinal disease by changing the way medical images are analyzed.

Why did you start this company?

The original co-founder, Andrew Ninh started the company because he experienced a collapsed lung which caused him to miss his high school graduation. During this time, he saw that healthcare desperately needed IT systems that are safer for patients, physicians and nurses. He later met Dr. William Karnes, a leading gastroenterologist at UC Irvine, who explained the current standard of care for colonoscopies. Together, they started Docbot, a predictive artificial intelligence (AI) technology company focused on gastrointestinal disease diagnosis. 

Docbot’s mission is to provide powerful AI-assisted image analysis solutions to revolutionize GI care. In 2013, co-founders Andrew Ninh, Tyler Dao, and Dr. William Karnes, teamed up to create a web interface for Karnes’ large polyp/colonoscopy quality database that he had painstakingly collected over a 10-year period.

Andrew Ritter

His background in bioinformatics and natural language processing led them to believe they could leverage the data to generate AI algorithms to automate the detection of polyps and other lesions and report colonoscopy quality. The result was the UltivisionAI™ Platform. The team officially launched the company in 2016 and raised its seed financing round in 2019 through the prestigious Y Combinator accelerator program.

We recently closed a $4 million Series A round led by Khosla Ventures, bringing out total amount raised to $8.5 million. 

What need/problem are you seeking to address in healthcare?

Docbot is applying artificial intelligence to improve the detection and diagnostic accuracy of gastroenterologists during gastrointestinal (GI) endoscopy procedures.  The UltivisionAI software platform is being trained to be able to be applied to the entire GI tract. While primarily focused on polyp detection for colon cancer prevention, detection algorithms for Barrett’s esophagus dysplasia and Ulcerative Colitis, among other indications are in development. 

What does your product do? How does it work?

UltivisionAI™ applies machine learning and computer vision to highlight areas on the screen that the AI predicts to be suspicious, thereby pointing the gastroenterologist to inspect certain areas of the colon more closely with the goal of detecting lesions that would otherwise have been missed.

Is this your first healthcare startup? What’s your background in healthcare?

I was recently appointed as CEO at Docbot, as I previously built and sold a pharmaceutical company in the GI space. I was previously co-founder and CEO of Ritter Pharmaceuticals, Inc., a leading biotech company developing gut microbiome therapies to treat gastrointestinal diseases. 

I led the company from proof-of-concept through late-stage Phase 3 clinical development. Along the way, I helped steer the company’s public listing onto the NASDAQ, raised over $100 million in institutional capital and led its successful acquisition by Qualigen Therapeutics. 

What is your company’s business model?

Docbot’s mission is to provide the most powerful AI-assisted image analysis solutions to revolutionize GI care. UltivisionAI™ is an intuitive software platform that provides actionable real-time computer vision detection, automated reporting, and data-driven analytic tools to improve patient care and clinical workflows.

UltivisionAI was developed to empower physicians, healthcare providers, and life sciences companies to make more reliable data-driven decisions. The platform alleviates the over $1 billion in treatment and maintenance costs associated with colorectal cancers that are directly caused by missed polyps.

Healthcare is moving towards value-based care and Docbot plans on structuring its revenue models and target initial adopters whose interests are aligned with Docbot’s preventive value-added features.

Who is your customer? 

Our customers are healthcare facilities that perform colonoscopies, such as outpatient surgery centers and hospitals. Life science companies looking for more objective diagnostic methods for digestive diseases, are also potential customers. 

How do you generate revenue?  

We plan on charging a subscription on a per endoscopy room per month basis.

Do you have clinical validation for your product?

We are currently undergoing a clinical trial to prospectively validate our technology.

Featured picture: ipopba, Getty Images


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