The tenet of personalized treatment is largely seen as the future solution to stubborn conditions like Alzheimer’s and other neurological disorders. But for some reasons, (i.e. inability to accurately interpret the brain’s fingerprint) we were unable to reach there.
Thanks to technological advancement as that might change. From recent findings, it is now possible to think of personalized treatment for patients with certain neurological conditions. The concept capitalizes in reading the brain’s fingerprint.
This tech can be used to better group patients with neurological diseases so as to put them in line with the most effective therapeutic solutions based on their specific needs.
Targeting Specific Biological Aspects
The technique is called pTIF (personalized Therapeutic Intervention Fingerprint) and it revolves around predicting the effectiveness of targeting specific biological aspects, such as brain amyloid/tau deposition, neuronal, functional dysregulation, and inflammation — with the sole intent of managing how a patient’s disease evolves.
This treatment option capitalizes on modern technologies, artificial intelligence, and computational brain modeling.
Student researchers from Montreal Neurological Institute and Hospital of McGill University (The Neuro) in conjunction with the Ludmer Center for Mental Health (Neuroinformatics) managed to develop the pTIF system, which deploys machine learning technology, and as reported also in the journal NeuroImage, this might pave a way to personalized treatment for neural complications.
Yasser Iturria-Medina led his fellow researchers to analyze the collected neurological data harvested from 331 Alzheimer’s patients, and from healthy controls. This encompassed various modes of positron emission tomography and magnetic resonance imaging (PET & MRI).
Put into the algorithms, the scholars were able to categorize patients according to their pTIF subtypes, based on their potentially and the most helpful, factor-specific interventions.
These subtypes were then analyzed and compared with each patient’s individual genetic profile. Where it was established that patients with similar pTIF subtype had the same gene expression.
This confirmed the way genes affect their physiology is similar in the specific category. Usually, the drugs used to control disease progression work by having to modify gene expression and complicated of all– the brain properties.
However, with drugs specifically tailored to pTIF subtypes, the researchers say treatment would be much more effective. This is because, with the former, drugs are designed to treat all patients with Alzheimer’s, contrary to the latter, which focuses on what might work best on one patient.
The Research is One of a Kind
The interesting part is that this is the only study that has ever unmasked a direct link between brain dynamics, molecular and cognitive alterations and predicted therapeutic responses in patients.
Meaning, experts can now use subtypes to design drugs that do best with the particular patient, based on their phenotypic brain characteristics and their unique gene expression profile.
Something the researchers stated is a major milestone in personalized medicine. And could immensely improve the effectiveness of treatment.
Top on that this will cut the budget for clinical drug trials because scientists will be able to select patients without guesswork.
Why Personalized Medicine?
While this may be among the few endeavors to try out personalized medicine in neural disorders, researchers have since believed that for stubborn conditions like cancer, custom-made treatment might be the remaining hope for patients.
Previous findings also state that personalized drugs will help in reducing undesired side effects, and could make therapeutic care less complicated. It is believed that this will make clinical trials and associated cost of research overly less expensive.
However, there are also concerns that this will require doctors to be retrained, to be able to handle patients based on their specific needs.
“We expect that the framework we’ve introduced will lead to more effective medical care. This might as well reduce pharmaceutical costs substantially – and may quicken the creation-evaluation of cycle of new therapeutic agents,” explained Iturria-Medina.
The technology is still within the confines of vetting and as projected, the work and the tools will expand to target a broader category of neurological disorders.