Release date: 2018-07-13
Personalized therapy can provide a treatment that is specific to a patient's unique physiology, depending on the patient's condition. This feature also makes personalized therapy a long-term research focus for researchers and doctors. Recently, a new research has been released, dedicated to the use of artificial intelligence technology to provide personalized therapy for patients with neurological diseases.
Researchers from McGill University in Canada have developed a technique called personalized Therapeutic Intervention Fingerprint (pTIF) that targets specific biological factors in the brain (such as brain amyloid/ Drugs that control tau deposition, inflammation, neuronal dysfunction, etc., predict the effects of disease progression in patients.
Using computational brain modeling and artificial intelligence techniques, the researchers analyzed neurological data from 331 patients with Alzheimer's disease and a control group consisting of healthy people. These data include many different modes of positron emission tomography (PET) and magnetic resonance imaging (MRI). Based on these data, the researchers divided patients into different pTIF subtypes based on the effects of specific interventions.
The researchers used a variety of different models of brain images as research data (Source: Yasser Iturria Medina)
By comparing these subtypes to the patient's individual gene profile, the researchers verified the relevance of the subtypes. They found that patients with the same pTIF subtype have similar gene expression, which means that the mechanisms by which genes affect physiological functions are similar. Because drugs that control disease progression must modify both gene expression and brain characteristics, drugs that differ by different pTIF subtypes are more effective than those used to treat all Alzheimer's patients.
This is the first study that directly links patients' brain activity, predictive response, and molecular and cognitive changes. Using data from the pTIF subtype, drugs can be designed for patient-specific gene expression profiles and phenotypic brain features. This marks a major step forward in personalized therapy. If this study is used for patient screening, it can also increase the effectiveness of screening and reduce the cost of clinical drug trials.
"This study can make treatment more effective, while reducing unnecessary side effects, and significantly reduce the cost of drugs and trials associated with clinical trials, thereby accelerating the evaluation cycle of innovative drugs," said the head of the study, McGill University, Neurology Dr. Yasser Iturria-Medina, associate professor of neurosurgery, said: "In the future, our work will focus on the application of PTIF to other neurological diseases and extensively verify it. More importantly, we will develop Analytical tools are available to a wide range of users in the international community through an open access platform."
We hope that this technology will be more widely used in the future, which will benefit patients with neurological diseases.
Source: WuXi PharmaTech AI
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