A genetic algorithm–based area coverage approach for controlled drug delivery using microrobots

Tao, Weimin; Zhang, Mingjun

doi:10.1016/j.nano.2004.11.006

Cited by 18 publications

(11 citation statements)

References 11 publications

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“…The new solution might then be accepted with a probability that depended both on the di®erence between the corresponding objective values and also on the function of time. The Genetic Algorithm (GA), a heuristic search that mimics the process of natural evolution, was proposed by Tao and Zhang 10 for online and o®line path planning based on area coverage. In recent years, algorithms based on swarm intelligence have been applied to solve the path¯nding problem.…”

Section: Introductionmentioning

confidence: 99%

“…Chemical and biochemical sensors 1,3,10 can be used to sense the environment and detect the target cells and obstacles. The sensors detect changes in volume, concentration, displacement and velocity, pressure, or temperature of cells to identify the target.…”

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confidence: 99%

“…An alternative is to create a microrobot that can anchor itself to a blood vessel for easier surgical removals. 3,10,33 However, in order to design the microrobot for the simulation, the mathematical model used to simulate the movement of a microrobot and the mechanism used to recognize the obstacles must be described. The following subsections provide the model and the methods to support these requirements.…”

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confidence: 99%

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Drug Delivery Based on Swarm Microrobots

Banharnsakun

Achalakul

Batra

2016

Int. J. Comp. Intel. Appl.

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Advances in the development of technology have led to microrobots applications in medical elds. Drug delivery is one of these applications in which microrobots deliver a pharmaceutical compound to targeted cells. Chemotherapy and its side e®ects can then be minimized by this method. Two major constraints, however, must be considered: the robot's onboard energy supply and the time needed for drug delivery. Furthermore, a microrobot must avoid biological restricted areas which we treat as obstacles in the path. The main objectives of this work were tō nd optimal paths to targeted cells and avoid collision with obstacles in the paths under a dynamic environment. In this study, we controlled motion of microrobots based on the concept of swarm intelligence. Arti¯cial Bee Colony (ABC), the Best-so-far ABC, and the Particle Swarm Optimization (PSO) methods were employed to implement the collision detection and the boundary distance detection modules. Forces that drove or resisted blood°ow as well as pressure in blood vessels were considered to approximate the e®ects of the environment on the microrobots. Numerical experiments were conducted using various obstacle environments. The results con¯rm that the proposed approaches were successful in avoiding obstacles and optimizing the energy consumption used to reach the target.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Drug Delivery Based on Swarm Microrobots

Banharnsakun

Achalakul

Batra

2016

Int. J. Comp. Intel. Appl.

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“…It has been successfully applied for a wide range of real-world problems of significant complexity (McCall, 2005). Tao and Zhang (2005) have proposed a genetic algorithm-based area coverage approach for controlled drug delivery using micro robots. Their proposed GA approach had advantages of reducing computational costs.…”

Section: Introductionmentioning

confidence: 99%

Preparation of agar nanospheres: Comparison of response surface and artificial neural network modeling by a genetic algorithm approach

Zaki

Varshosaz

Fathi

2015

Carbohydrate Polymers

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“…Many researchers consider the idea of nanorobots to use in targeted drug delivery [1,2,[4][5][6][7][8][9]. Targeted drug delivery is one of the therapy methods where the delivery of the medication causes higher local drug concentration in some parts of the body [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Chemical robotics — chemotactic drug carriers

Lagzi

2013

Open Medicine

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AbstractIn this review we show and describe a concept of designing autonomously moving artificial cells (chemical robots) carrying drugs and having tactic behavior based on artificial chemotaxis. Such systems could help to provide new and more efficient drug delivery applications. Chemical robot can be constructed based on the self-organization — natural “bottom-up” way — of fatty acid or lipid molecules into ordered nano- or micrometer size objects that have the ability to move and respond to environmental stimuli. The idea of using tactic carriers in drug delivery applications can be justified by the fact that cancer sites in the living body have different physiological characters (lower pH and higher resting temperature) compared to normal cells. The proposed “bottom-up” design method for self-propelled objects at small scales for targeted drug delivery applications could realize the original designation of nanoscience proposed 50 years ago by Richard Feynman.

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A genetic algorithm–based area coverage approach for controlled drug delivery using microrobots

Cited by 18 publications

References 11 publications

Drug Delivery Based on Swarm Microrobots

Drug Delivery Based on Swarm Microrobots

Preparation of agar nanospheres: Comparison of response surface and artificial neural network modeling by a genetic algorithm approach

Chemical robotics — chemotactic drug carriers

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