4 Ways AI and New Tech Are Transforming Early Detection Diagnostics

Diagnostics researchers with patient Medrio clinical research

While it might sound cliché, there’s still merit to the axiom “an ounce of prevention is worth a pound of cure.” Healthcare systems and clinical researchers worldwide are placing increasing emphasis on developing AI and other treatments and technology based on the logic that some of the best and most reliable ways to support patients are by detecting and treating disease sooner.

Early intervention often gives patients more options. In some cases, it can mean the difference between life and death. Consider this:

• 90% of women diagnosed with breast cancer at the earliest stage survive the disease for at least 5 years, compared to 15% diagnosed later on.
• Since medication tends to be more effective early on, early Alzheimer’s detection means disease progression can be delayed or slowed.

With speed, accuracy, and curing disease as core values here at Medrio, we believe there’s no time to waste when it comes to preventing and treating medical conditions. Therefore, a primary goal in the design of our eClinical software is to help researchers do their jobs in the fastest and most efficient ways possible. However, we’re just working behind the scenes – clinical researchers are the ones breaking ground and expanding the limits of modern medicine. Let’s look at 4 of the most exciting developments in early detection diagnostics:

AI and deep learning for faster and more accurate diagnoses

While physicians have clear systems for identifying illnesses, human error and bias can happen. A recent New York Times article cited that every year millions of Americans leave a doctor’s office with a misdiagnosis – many of which can be harmful.

AI is now showing promise in helping doctors to combat this issue. A group of researchers in China and the US are testing a system that uses AI to associate common illnesses with specific patient information. Here’s how it works:

• Utilizing health record data from more than half a million pediatric patients, this system examines symptoms and clinical data to automatically diagnose common childhood illnesses.
• Although this system needs further testing in clinical trials, it has proven to be highly accurate.
• These researchers are not alone: companies like Google are also developing deep learning systems to improve healthcare.

Breathalyzers for early lung cancer detection

Cancer is a worldwide public health problem and the second leading cause of death in the United States. The World Health Organization cites that every year cancer takes the lives of over 8 million people – the majority of whom are diagnosed at later stages when treatment options are limited.

Diagnostic breathalyzers are an emerging technology that has the potential to revolutionize cancer detection:

• In February 2019, a two-year, 1,500-patient clinical trial was announced for a breath biopsy to test biomarkers known as volatile organic compounds (VOCs) to detect six different types of early-stage cancer.
• This pain-free biopsy would only take 1-10 minutes, and processing would be only 3 days – an improvement over blood biopsies, which can be painful and take weeks for results.

Routine lab tests in minutes instead of days

Lab tests are a standard component of routine checkups, but can be anxiety-inducing if patients are worried about the results. Getting lab results back sooner means putting patients at ease or beginning interventions without delay. A diagnostics company is making this possible:

• A recently finished clinical trial has been successful in reducing the waiting time for lab results from days to minutes.
• These tests can accurately and comprehensively track liver function and check for cancer, hepatitis, and HIV.

FDA breakthrough designation for early Alzheimer’s detection

Alzheimer’s is also getting attention when it comes to early detection. In January 2019, a diagnostics company received breakthrough device designation from the FDA for a blood test that screens for Alzheimer’s:

• It aims to predict the results of PET scans, which can detect the biomarkers of neurodegenerative disease.
• If approved by the FDA, this tool would benefit the efficiency of the diagnostic process and provide more options to patients.

All 4 of these developments shine a light on the expansive possibilities that AI and clinical research are capable of providing for the future of public health. And if anything can be certain about the future of clinical trials, it’s that speed and accuracy will be keys to success. Here at Medrio we stand committed to supporting researchers in conducting the fastest and most seamless trials of their careers. It’s by getting answers to research questions and delivering innovative diagnostic tools sooner that we can reduce human suffering and live healthier lives.