Smart machines are reinventing how work is done across all industries. Companies are seeing boosts in process, speed and performance by implementing Artificial Intelligence (AI) technologies. However, many see a significant untapped potential in re-imagining business processes in healthcare—all in real time.
“At Modal Technology Corporation, we feel that Regenerative Medicine (RM) combined with machine learning can be a powerful force towards the goal of healthcare as “precision medicine” to provide medical treatments tailored to the individual characteristics of each patient. This requires finding patterns in clinical data, image data (such as MRIs and x-rays), family history, and other medical records. By training computers to analyze these large treasure troves of information, computers can learn to find patterns that can be difficult for humans to detect, and predictions can then be made based on these patterns,” said Nathan T. Hayes, Chairman, Founder and CEO, Modal Technology.
Visual perception, speech recognition, decision-making, and translation between languages are already commonplace machine learning tools utilized in many corporations, and new uses of this technological advancement promises to impact businesses in healthcare in dramatic and important ways.
Currently only 15 percent of healthcare companies (US payers, providers and pharmacy benefit managers) are applying machine learning across the three dimensions of process, people and data. However, some companies in the healthcare industry are now making large investments in AI and machine learning methods to better understand and address customer needs while improving the bottom line.
“There are various protocols to enact the needs of cellular differentiations in RM, however, the creation of such protocols is extremely complex. An appropriately designed integrated machine learning system will be able to craft and adjust custom protocols for successful stem cells differentiations,” continued Hayes.
Founded in 2016, Modal Technology Corporation is a privately-owned Minnesota corporation that offers new innovative solutions for machine learning. Headquartered in Minneapolis, with a team of four, the company is involved in the development of industry standards in machine learning and has a vision of introducing the benefits of its patented technology to many vertical markets including finance, aerospace, defense and Regenerative Medicine in the healthcare sector.
As one of the few in the world who knows how to apply a relatively new branch of applied mathematics known as modal interval arithmetic to today’s technologies, Mr. Hayes founded two companies leveraging this arithmetic to significantly improve performances in machine learning and computer graphics. First at Sunfish Studio, LLC, Hayes invented the first ever modal interval rendering systems and methods. He is the inventor of patented applications of modal interval arithmetic in key areas of hardware design and software method to improve the speed and quality of computer graphics. Then at Modal Technology Corporation, he developed ALiX™, an artificial intelligence method that offers an optimal machine training result in a single run.
“Currently, machine learning efforts are focused on costly development & adjustment of existing methods that are based on trial and error. For example, if a machine is trained multiple times on the same data, consistent and repeatable results may not be easy to obtain. This can lead to a “crisis of confidence” in believing that the artificial intelligence has been trained to its optimal capability and is making predictions of acceptable quality,” noted Hayes.
He said, “ALiX is the only system and method that reliably finds the best machine training solution without the need to select random parameters, thereby improving confidence in machine answers and optimizing the machine learning processes to reduce cost, effort, and time to market.”
Susan Kaplan, EVP of Operations, explained it this way, “We hear a lot today in the media about the negative implications of AI to humans. At Modal we feel we are building “AI for Good” in healthcare and specifically in RM,” she said, adding, “Modal is engaged in a pilot oncology program with McGill University Health Center in Montreal, Canada where ALiX is used to test “hero” cells in a pancreatic cancer experiment where machine learning is used to make specific predictions about personalized treatments. Using this type of system can not only help with precision medicine for current patients; but also help predict future disease and solution issues for researchers and reduce costs by indicating precise treatments needed for that particular individual.”
“We attended two of the ARMI Summits this year and we were immediately in sync with Dean Kamen when he talked about disruptive technology in the RM sector,” said Hayes continuing, “Our thinking ties directly into ARMI’s goal of creating a whole new industry from scratch. RM is a clean slate and we hope to help educate and work with ARMI members on how to validate and integrate AI into the complex puzzle that is involved in Bio fabrication. We hope that members see Modal as a bridge to optimizing AI in RM on both the cell and manufacturing sides of the equation and we are looking forward to collaborating with others while leaving their own IP intact.”