Ivan Kairatov is a Biopharma expert with deep knowledge of technology and innovation in the industry, with experience in research and development. Today, we discuss the recent FDA approval of adaptive deep brain stimulation (aDBS) as a new treatment option for Parkinson’s disease.
Can you explain what adaptive deep brain stimulation (aDBS) is and how it differs from continuous deep brain stimulation (cDBS)?
Adaptive deep brain stimulation (aDBS) is an advanced form of treatment for Parkinson’s disease that involves an implanted device that continuously monitors brain activity for patterns indicating Parkinson’s symptoms. When these patterns are detected, the device delivers precise electric pulses to mitigate the symptoms. Unlike continuous deep brain stimulation (cDBS), which provides constant stimulation, aDBS adjusts the stimulation based on real-time monitoring of brain activity, offering a more dynamic and responsive approach to managing symptoms.
How does the aDBS device monitor brain activity and detect Parkinson’s symptoms?
The aDBS device monitors brain activity by focusing on the subthalamic nucleus. It detects specific patterns of neuronal activity associated with the onset of Parkinson’s symptoms. When these patterns are recognized, the device responds by delivering calibrated electrical stimulation to counteract the symptoms before they fully develop.
What are the two treatment algorithms covered by the FDA approval, and how do they work differently?
The FDA approval includes two treatment algorithms used in aDBS. The first is the “fast” algorithm, which instantly detects patterns related to Parkinson’s symptoms and immediately suppresses them. The second is the “slow” algorithm, which maintains brain activity within an optimal range to minimize symptoms, providing a more consistent therapeutic effect over time.
Can you tell us more about the fast algorithm and how it immediately suppresses symptoms?
The fast algorithm was designed to detect symptom-related brain activity patterns quickly and deliver immediate electrical stimulation to counteract them. This rapid response helps to prevent the symptoms from manifesting fully, providing immediate relief.
How does the slow algorithm help maintain brain activity within a range that reduces symptoms?
The slow algorithm operates by delivering continuous but adjustable stimulation to maintain brain activity within a therapeutic range. This approach helps to stabilize brain activity at levels that reduce the likelihood of symptoms occurring, providing a more steady and long-term management solution.
Who developed the fast algorithm, and what was the basis for its development?
The fast algorithm was developed by neurologist Simon Little, MBBS, PhD, at UC San Francisco in 2013, based on research he conducted at Oxford University with Peter Brown, MBBS. The development was driven by the need for a more responsive and adaptive approach to managing Parkinson’s symptoms that could provide immediate relief.
What are the main advantages of aDBS over cDBS for patients with Parkinson’s disease?
The main advantages of aDBS over cDBS include its ability to adapt to changes in a patient’s brain activity, providing more tailored and effective symptom management. aDBS can smooth out fluctuations in brain activity caused by medication or other factors, reducing both the peaks and valleys of symptom manifestation. This leads to a more consistent control of symptoms and potentially fewer side effects.
How does aDBS respond to changes in a patient’s brain activity throughout the day?
aDBS continuously monitors the patient’s brain activity and adjusts the level of stimulation in real time. This constant adjustment allows the device to respond to the natural fluctuations in brain activity that occur throughout the day, such as those influenced by medication intake or daily activities, providing continuous and personalized symptom management.
How can patients and healthcare providers choose between the fast and slow algorithms?
Patients and healthcare providers can choose between the fast and slow algorithms based on the patient’s specific symptoms and how they respond to each algorithm. The device’s software allows for easy switching between algorithms via Bluetooth, enabling providers to test both options and determine which one offers the best symptom control for the patient.
Are there any plans to develop more adaptive algorithms for aDBS, and if so, what symptoms might they target?
Yes, there are ongoing plans to develop more adaptive algorithms for aDBS. Future algorithms may target not only motor symptoms like stiffness and tremors but also non-motor symptoms such as mood dysfunction, insomnia, and other issues commonly experienced by people with Parkinson’s disease.
What research has been conducted at UCSF to further develop aDBS algorithms since your arrival in 2019?
Research at UCSF since 2019 has focused on developing and testing newer aDBS algorithms for both motor and non-motor symptoms of Parkinson’s. This includes studying brain signals in different regions, like the cerebral cortex, and designing algorithms that can better improve symptoms with reduced side effects compared to traditional DBS.
Can you elaborate on the new algorithm that monitors brain signals in the cerebral cortex?
The new algorithm developed at UCSF monitors brain signals in the cerebral cortex, a different region than the subthalamic nucleus targeted by the current FDA-approved algorithms. This new approach has shown improved symptom management and fewer side effects, providing a promising direction for future aDBS treatments.
What were the outcomes of the double-blind trial conducted by UCSF using this new algorithm?
The double-blind trial conducted by UCSF demonstrated that the new algorithm could significantly improve the quality of life for Parkinson’s patients. The trial showed reduced symptoms and side effects, with participants experiencing better overall management of their condition, including cases like a former pro skateboarder who could return to his sport.
How did UCSF’s double-blind trial improve the quality of life for Parkinson’s patients, including the example of the former pro skateboarder?
The trial improved the quality of life for participants by providing more effective symptom control with fewer side effects. The advanced algorithm allowed a former pro skateboarder to regain his mobility and engage in activities he previously enjoyed, highlighting the potential of aDBS to significantly enhance daily living for Parkinson’s patients.
How do you foresee artificial intelligence playing a role in the future development of aDBS technology?
I foresee artificial intelligence playing a significant role in customizing and optimizing aDBS algorithms. AI can analyze large amounts of brain activity data to identify patterns and make precise adjustments in real time, leading to highly personalized and effective therapies tailored to individual patient needs.
Which other non-motor symptoms of Parkinson’s disease might future aDBS technology address?
Future aDBS technology could address a range of non-motor symptoms, including depression, sleep dysfunction, cognitive impairments, and other mood-related issues. By targeting these symptoms, aDBS could provide more comprehensive care for patients, improving both their physical and mental well-being.
How might today’s FDA approval impact the development of DBS treatments for conditions such as depression, chronic pain, and obsessive-compulsive disorder?
Today’s FDA approval could accelerate the development of DBS treatments for other conditions like depression, chronic pain, and obsessive-compulsive disorder. As researchers gain more insights into adaptive stimulation and refine algorithms, the principles and technologies used in aDBS could be adapted to treat these additional conditions effectively.
What are the potential benefits of providing round-the-clock personalized DBS therapy for patients with Parkinson’s disease?
Providing round-the-clock personalized DBS therapy could lead to more consistent and effective symptom management for Parkinson’s patients. This continuous and adaptive approach can address symptom fluctuations throughout the day, reduce side effects, and improve overall quality of life by offering tailored treatment based on each patient’s unique brain activity.
Are there any known side effects or risks associated with using aDBS?
While aDBS offers many benefits, there can still be potential side effects or risks, such as infections related to the implanted device, hardware malfunctions, or unintended stimulation of brain regions that could lead to adverse effects. However, the adaptive nature of aDBS aims to minimize these by providing more precise and responsive treatment.
How do you see the future of Parkinson’s treatment evolving with advancements in aDBS and related technologies?
I see the future of Parkinson’s treatment becoming more personalized and effective through advancements in aDBS and related technologies. Continuous monitoring and adaptive algorithms will likely lead to better symptom control, reduced side effects, and improved quality of life for patients. Additionally, integrating AI and targeting both motor and non-motor symptoms could revolutionize how we manage and treat Parkinson’s disease in the coming years.
