SAN DIEGO, CA / ACCESSWIRE / October 4, 2021 / Diagu, a MedTech startup, is building the next generation of medical testing solutions, and investors are taking notice. The firm recently announced a $2 million funding round led by Airspeed Equity and FasterCapital.
Under the leadership of founder and CEO Anna Rybka-Krysiak, Diagu develops neural networks and machine learning algorithms that speed the analysis of blood and urine samples to support accurate, actionable interpretations of test results and medical records. Its solution offers unprecedented speed, accuracy, and context to situations where every second counts and accurate diagnoses are absolutely critical. Diagu has already signed several sales agreements, and its hospital and laboratory partners perform more than 60 million blood tests each year. Each of those tests represents a potential point of sale. "We are pursuing deals to include our reports with more and more lab results," says Rybka-Krysiak.
Dr. Alexsander Nawrocki, CEO of Airspeed Equity, believes that he has seen the future of medical testing: not in grand promises and unproven technologies but in the more straightforward proposition that the more doctors know, and the sooner they know it, the better they can serve their patients. "The Diagu project has a real impact on improving the situation in medical facilities," he notes. "The solution provides support for doctors while making a diagnosis and interpreting medical data. This saves their time and has a positive impact on doctor-patient relationships."
Diagu's solution evaluates the results of laboratory tests against each patient's complete medical history. It then generates a comprehensive yet easily digested report that includes suggested diagnoses and recommendations for treatment. The report can be sent directly to the doctor's preferred platform through a flexible API. The patient's doctor always makes the final call; Diagu simply gives doctors more information, more quickly and more usably, than they have ever had before. The real magic lies in how Diagu produces such a remarkably useful set of data so quickly.
The system relies on an array of machine learning algorithms to accept and process patient information and relate it to test results and disease descriptions following ICD10, ICD11 and SNOMED standards. This information is processed by a sophisticated neural network powered by Microsoft and Amazon. The network draws on tens of millions of tests performed each year at laboratories and hospitals around the world that have partnered with Diagu. Doctors receive a report that reflects not only the full details of each patient's case and the results of each test, but also the actual results of millions of similar tests and diagnoses from hospitals, taking into account all information that can be correlated with a given test.
Hesham Zreik, CEO of FasterCapital, agrees with his counterpart at Airspeed Equity. He is especially encouraged by the partnerships Diagu has already struck, and by the field-tested results its engineers have already delivered. Zreik sees special potential in the firm. "The team at Diagu is establishing a trustworthy basis of research and dedicated work to make Diagu the best solution out there. The MedTech market is an especially competitive market, but it is also an ever-growing space with a huge demand for new and smart technologies. We are glad to be collaborating with the team and are looking forward to leaving a positive impact."
While Diagu stands alone in its particular niche, Zreik makes a solid point about the size and growth of the healthcare sector. Most developed countries spend at least 10% of their GDP on healthcare, and the United States is project to spend 18% of its GDP on healthcare in 2021. In the US and elsewhere, the healthcare sector employs more people than any other.
The blood-testing market is growing even more quickly than the broader healthcare sector. Shorter hospital stays and more support for outpatient services has increased the demand for diagnostic testing, as have increasing rates of diabetes and cardiovascular disease across the globe. Advances in blood-testing technology have allowed laboratories to test for a wider variety of adverse health conditions than ever, including many forms of cancer and an increasing range of prenatal issues. Grand View Research recently projected the global blood-testing market to exceed $140 billion by 2028, representing an annual growth rate of 8.3%.
Diagu enters the field with an unprecedented solution just as artificial intelligence is being accepted into the medical mainstream. Modern hospitals are typically built with space reserved to support robot-assisted surgical procedures. Rybka-Krysiak believes that AI-assisted test analysis is the next step forward.
"Interpreting test results is a time-consuming challenge," she notes, "and physicians still often find themselves with less information than they'd prefer. We developed our neural network to solve those problems, and the results to date show that we've built something truly special."
Having proved its solution on a focused range of test types, Diagu plans to invest millions of dollars toward expanding the range of tests it assesses. After that, says Rybka-Krysiak, the sky is the limit.
"Our first concern is for patients, and we serve them by supporting physicians," she observes. "But we also foresee significant opportunities to support other industries. Data drives knowledge, and knowledge is power. When properly anonymized, the data at our disposal will help insurers hold the line on medical costs and pharmaceutical companies focus their R&D efforts in response to epidemiological patterns."
Diagu plans to significantly expand its partnerships with diagnostic laboratories around the world toward joint commercialization of its solution, with medical equipment providers, and with teaching hospitals. With proven technology delivering a unique solution, a large network of partners, and a growing client list, Diagu seems poised to reward investors who support its growth into some of the market's most reliably profitable sectors.
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