Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies

Area of Science:

• Neuroscience
• Pharmacometrics
• Systems Biology

Background:

• Quantitative systems pharmacology (QSP) applications in neuroscience lag behind oncology and immunology due to brain complexity.
• Recent technological and methodological progress enhances understanding of brain function, disease, and drug effects.
• Pharmacometricians may require expanded mathematical and statistical toolkits to utilize novel neuroscience data.

Purpose of the Study:

• To review recent advancements in quantitative and systems neuroscience presented at the American Conference on Pharmacometrics (ACoP10).
• To explore how these advancements can be integrated with QSP modeling to improve understanding of neurological diseases.
• To highlight novel data types and methodologies for enhancing preclinical-to-clinical translation of therapeutics.

Main Methods:

• Overview of technological advancements including microphysiological systems with human induced pluripotent stem cells (hiPSCs).
• Discussion of digital biomarkers and large-scale imaging for generating clinically relevant datasets.
• Integration of network neuroscience methodologies with QSP models for neurodegenerative diseases, incorporating neural connectomics.

Main Results:

• Microphysiological systems, digital biomarkers, and advanced imaging provide enhanced data granularity and clinical relevance.
• Network neuroscience approaches combined with QSP models can link molecular alterations to clinical endpoints via connectomics.
• Emerging areas like neuroimmunology, microbiome research, single-cell transcriptomics, and digital device biomarkers show promise.

Conclusions:

• Leveraging new technologies and methodologies with QSP modeling is crucial for advancing neurological disease research.
• These integrated approaches can significantly improve the translation of therapeutics from preclinical studies to clinical application.
• Continued expansion of modeling toolboxes is essential to fully capitalize on novel neuroscience data.