IBM has introduced machine learning (ML) to the diagnostics field in the hopes that one day these technologies may assist in the creation of stable and effective diagnostic tests for early-onset Alzheimer's. On Monday, the tech giant said ML and artificial intelligence (AI) can be exploited to replace invasive and expensive tests for the disease. A paper documenting the research, conducted by IBM's Australian team, has been published in Scientific Reports. Alzheimer's is currently incurable and can only be treated by palliative means. Symptoms for the disease include the gradual degradation of memory, confusion, and difficulty in completing once-familiar daily tasks.
Previous attempts to find a cure for Alzheimer's ended up in failure, but a new study out of IBM Research has the potential to spark a major breakthrough. A group of IBM researchers have harnessed the powers of machine learning to figure out a way to detect a biological marker associated with the disease -- a peptide called amyloid-beta -- with a simple blood test. The solution they came up with can even detect an individual's risk for Alzheimer's earlier than a brain scan can and way before symptoms start showing up. It can arm doctors with the ammo they need to be able to take better care of their patients. According to a study published in 2017, the concentration of amyloid-beta in a person's spinal fluid starts changing decades before the first signs of the disease show up.
Alzheimer's disease is a terminal neurodegenerative disease that has historically been diagnosed based on observing significant memory loss. There is currently no cure or disease-modifying therapy for this terminal illness, despite hundreds of clinical trials. It is thought these trials may have a high failure rate because the people enrolled are in the latest stages of the disease, likely already suffering a level of brain tissue loss that cannot easily be repaired. Thus, researchers have put their mind to how to detect this disease earlier, while a chance may still exist to slow its progression. Recent research has shown a biological marker associated with the disease, a peptide called amyloid-beta, changes decades before any memory-related issues are apparent.
Nobel Prize winner Koichi Tanaka says the predictive blood test for Alzheimer's disease he and colleagues spent almost a decade developing is a double-edged sword. Without medications to stave off the memory-robbing condition, identifying those at risk will do nothing to ease the dementia burden and may fuel anxiety. But if used to identify the best patients to enroll in drug studies, the minimally invasive exam could speed the development of therapies for the 152 million people predicted to develop the illness by 2050. "We must be cautious on how the test is used because there's no curative treatment," Tanaka said in an interview at Kyoto-based Shimadzu Corp., where he's worked for 36 years. The 59-year-old engineer, who shared the Nobel for chemistry in 2002, said he hopes the test he helped pioneer will one day be administered routinely, but right now it belongs in the hands of drug developers and research laboratories.
A revolutionary blood test could predict 20 years in advance if a person will develop Alzheimer's disease. Scientists hope the breakthrough could prevent victims having to reach an advanced stage before they are diagnosed. It may also help middle-aged people determine their risk of the devastating condition. The German researchers claim their test can identify the proteins involved with the disease as they seep into the blood stream. Known as amyloid-beta peptides, these misshapen strings clump together in the brains of people with Alzheimer's, slowly killing off the surrounding cells.