Prof Agus Kartono Paves the Way for Early Diagnosis of Parkinson-Alzheimer’s Through Biophysical Modeling
Declines in memory and motor skills are often considered a natural part of the aging process. However, the situation is not always that simple. The distinction between age related changes and early symptoms of neurodegenerative diseases can be identified through patterns of neuronal activity.
This is the approach developed by Prof Agus Kartono, a full professor at the Faculty of Mathematics and Natural Sciences (FMIPA) at IPB University, through biophysical modeling for the diagnosis and treatment of Parkinson’s and Alzheimer’s diseases.
In his IPB University Full Professor Inaugural Lecture (8/20), Prof Agus explained that biophysical modeling was developed to understand changes in the patterns of neuronal electrical activity while also helping to determine more precise treatment strategies.
His interest stemmed from the growing body of research on Parkinson’s and Alzheimer’s. While discussing research findings with master’s students during a seminar, he became increasingly aware that these two diseases are actually quite prevalent in people’s lives.
“During that seminar, one of the moderators mentioned that her mother had Alzheimer’s. Then another audience member said her mother and grandmother were also experiencing similar conditions. That’s when I realized these diseases are actually quite common around us,” he said.
According to him, one of the key challenges is distinguishing between age-related changes in bodily function and neurodegenerative disorders. Biophysical modeling is then used to simulate neuronal activity and observe the patterns of neural stimulation that occur.
Prof Agus explained that simulations can also be used to test dosing regimens for Parkinson’s medication, particularly Levodopa. The modeling results showed that administering 125 mg four times a day produces a pattern of neural activity that closely approximates normal conditions. Conversely, administering larger doses less frequently can result in changes in neural activity frequency that deviate further from normal conditions.
“The ideal approach is to take small, continuous doses so that the medication is always present in the body to bridge the gap between those two neurons,” he explained.
In addition to drug therapy, modeling is also being developed to simulate immunotherapy. In Parkinson’s disease, this approach is used to explore the possibility of restoring neural electrical activity patterns through modulation of the immune system. Meanwhile, in Alzheimer’s disease, modeling is used to understand how drugs interact with amyloid-beta plaques that inhibit communication between nerve cells.
Prof Agus also sees opportunities for biophysical modeling to support earlier diagnosis. In the future, data from medical devices such as Deep Brain Stimulation (DBS) will be compared with simulation results to determine whether specific patterns of neural activity can serve as early indicators of Parkinson’s or Alzheimer’s.
“This is still a work in progress. We’ve only been taking a serious approach to Parkinson’s for about two to three years. Next, we’ll try to combine data from DBS systems in hospitals with the simulations we’ve developed,” he said.
According to Prof Agus, a similar approach has previously been developed for diabetes. That experience serves as a foundation for expanding biophysical modeling to neurodegenerative diseases.
He emphasized that biophysical modeling is not intended to replace the role of doctors, but rather to provide scientific information that can help inform more evidence based medical decision making. With further development and validation of clinical data, this technology is expected to open up opportunities for earlier diagnosis while supporting more precise therapies for patients with Parkinson’s and Alzheimer’s. (IAAS/WSG)
