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Combination Therapies and Personalized Medicine

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

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Opportunities and Challenges in Precision Neurotherapeutics.

Lilianne R Mujica-Parodi^1,2, Dost Öngür³, R Mark Richardson⁴

¹Department of Biomedical Engineering and Laufer Center for Physical and Quantitative Biology, State University of New York at Stony Brook, Stony Brook, New York, USA;

Annual Review of Biomedical Engineering

|January 16, 2026

Summary

This summary is machine-generated.

Precision neurotherapeutics tailors treatments for neurological disorders using individual patient data. This personalized approach enhances treatment efficacy by moving beyond one-size-fits-all methods.

Keywords:

central nervous system medical device neuroimaging neuromodulatory neurotransmitter pharmaceutical

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Published on: September 27, 2020

Area of Science:

Neuroscience
Pharmacology
Biotechnology

Background:

Traditional treatments for neurological, neurodegenerative, and psychiatric disorders have limited response rates (30-60%).
A paradigm shift towards precision neurotherapeutics is needed, leveraging patient-specific biological, behavioral, and physiological data.
Individual differences in genetics, brain structure/function, and treatment response necessitate personalized strategies.

Purpose of the Study:

To review advances in precision neurotherapeutics across pharmaceutical, neuromodulation, and biomarker domains.
To highlight the potential of personalized interventions for neurological and psychiatric conditions.
To identify challenges and opportunities in developing mechanistically informed biomarkers for personalized mental health care.

Main Methods:

Review of pharmaceutical approaches: fragment-based drug discovery, pharmacokinetic modeling, quantitative systems pharmacology.
Examination of neuromodulation technologies: evolution from open-loop to adaptive closed-loop systems with real-time biomarker feedback.
Analysis of biomarker development: neuroimaging, pharmacogenomics, digital health applications.

Main Results:

Advances in pharmaceutical strategies offer more targeted drug discovery and modeling.
Neuromodulation is evolving towards adaptive, real-time feedback systems for enhanced efficacy.
Biomarker development integrates diverse data sources for a comprehensive patient profile.

Conclusions:

Precision neurotherapeutics offers a transformative approach to treating complex brain disorders.
Integration of AI, computational modeling, and regulatory shifts facilitates personalized mental health care.
Mechanistically informed biomarkers are crucial for guiding individualized treatment strategies.