Why does it matter?
Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease and is expected to impose an increasing social and economic burden on societies as populations age. According to the European Parkinson’s Disease Association, 1.2 million people in Europe have PD1, while studies indicate that it is expected to reach an increment of 28% by 2020 in the UK. Overall estimates of PD prescription drugs and patient care costs vary from country to country. In the UK, for example, the overall cost has been estimated to be between £449 million and £3.3 billion annually, while it can be even higher when including indirect costs arising from lost productivity and carer burden. Strategies that minimize disease progression and maximize quality of life should help ensure optimal resource utilization in the future.
The core pathological feature of PD is degeneration in midbrain dopamine systems (substantia nigra pars compacta and ventral tegmental area). These systems supply dopamine to the basal ganglia – a set of sub-cortical nuclei critical for motor control – and in particular to the striatum, the main input nucleus therein. However, PD also triggers non-motor symptoms, in which other neurotransmitter systems are involved. Computational models of the basal ganglia have been proposed in the past, targeting mainly high level-action decision making and habitual control. However, these models do not make a direct link to motor behavior via the musculo-motor system in humans, and perforce, cannot be tailored to individual patient actions and movements.
The ultimate vision of NoTremor is to meet this grand challenge and revolutionize the way Parkinson’s disease is treated. The project targets the provision of a patient specific computational model of relevant neurotransmitter systems, the basal ganglia, and the neuromuscular system that will be subsequently used in the context of a simulation-based clinical decision support system to improve the quality of analysis and progression of Parkinson’s disease through a holistic, layered, parametric virtual patient model, describing the neural pathology, coupled with the propagated muscular and motor activity.