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Updated: Feb 28, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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Model-based optimization approaches for precision medicine: A case study in presynaptic dopamine overactivity.

Kai-Cheng Hsu1, Feng-Sheng Wang2

  • 1Department of Neurology, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan.

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Summary

Precision medicine uses individual data to predict disease and optimize treatments. This study developed model-based approaches for accurate diagnosis and targeted therapies for presynaptic dopamine overactivity.

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Area of Science:

  • Biomedical Engineering
  • Computational Biology
  • Pharmacogenomics

Background:

  • Precision medicine aims to tailor disease treatment to individual variability.
  • Accurate diagnosis, effective therapy, and minimized adverse effects are key goals.
  • Presynaptic dopamine overactivity presents complex challenges for personalized treatment.

Purpose of the Study:

  • To introduce model-based precision medicine optimization approaches.
  • To address pathogenesis, biomarker detection, and drug target discovery for presynaptic dopamine overactivity.
  • To enhance diagnostic accuracy and therapeutic efficacy.

Main Methods:

  • Pathogenesis modeling identified enzyme defects (one-hit and two-hit) causing disease states.
  • Cluster analysis and support vector machines selected biomarkers for etiological discrimination.
  • Fuzzy decision-making identified common and specific drug targets.

Main Results:

  • Accurate diagnoses correlated with higher satisfaction grades and reduced enzyme targets.
  • Specific drugs yielded higher satisfaction than common drugs.
  • Common drugs offered broad applicability across different etiologies.

Conclusions:

  • Model-based approaches enhance precision medicine for presynaptic dopamine overactivity.
  • Biomarker discovery and targeted drug development are crucial for personalized treatment.
  • A balance between drug specificity and broad applicability optimizes therapeutic outcomes.