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Programming Stimuli-Responsive Behavior into Biomaterials.

Barry A Badeau¹, Cole A DeForest^1,2,3,4

¹Department of Chemical Engineering, University of Washington, Seattle, Washington 98195, USA;

Annual Review of Biomedical Engineering

|March 13, 2019

Summary

This summary is machine-generated.

Stimuli-responsive biomaterials offer advanced diagnostics and personalized medicine by responding to biological or external cues. This review explores synthetic advances, logical operations, and future directions for programmable biomaterials.

Keywords:

biomaterials drug delivery smart materials stimuli-responsive polymers tissue engineering

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Area of Science:

Biomaterials Science
Materials Chemistry
Biomedical Engineering

Background:

Stimuli-responsive materials dynamically alter properties upon exposure to specific environmental cues.
These materials can utilize endogenous biological signals or externally controlled stimuli for targeted applications.
They hold significant promise for next-generation diagnostics and personalized medicine.

Purpose of the Study:

To review synthetic and strategic advancements in creating stimuli-responsive biomaterials.
To categorize these systems based on material type, input number, and response mechanism.
To explore the potential of programmable biomaterials with customizable sensitivity.

Main Methods:

Categorization of responsive biomaterials by input, output, and logic.
Analysis of synthetic strategies for imparting responsiveness.
Examination of signal transduction mechanisms (chemical and physical).

Main Results:

Diverse synthetic and strategic advances enable a wide range of biomaterial responsiveness.
Biomaterials can be engineered to perform Boolean and non-Boolean logical operations.
Customizable sensitivity is achievable through careful design of input-output relationships.

Conclusions:

Programmable stimuli-responsive biomaterials represent a powerful platform for advanced medical applications.
Continued development focuses on enhancing sensitivity, control, and integration with biological systems.
Future research directions include addressing current limitations and exploring novel design paradigms.