YYY

RESEARCH PROPOSAL

XXXMASTER OF SCIENCE IN MICROELECTRONIC ENGINEERING

SUPERVISOR: XXX

SCHOOL OF MICROELECTRONIC ENGINEERINGUNIVERSITI MALAYSIA PERLISBlok A, Kompleks Pusat Pengajian Jejawi,Jalan Kangar-Arau,02600 Jejawi, Perlis, MALAYSIA.

1.0INTRODUCTION

Microneedle devices are designed with two purposes; drug delivery to the patient and blood extraction from the patient for biosampling. Microneedles have been fabricated in metals, silicon, silicon dioxide, polymers glass and other materials. To penetrate the stratum corneum of the skin, a minimum length of around 100 m is necessary. Microneedles are known as painless with a maximum size of around 150 m. They are fabricated as solid or hollow needles. Microneedles suppose to be sharp and strong as much as necessary to pierce the epidermis layer.

At present, microneedles are mainly used for biological fluidic extraction and drug delivery on skin. The advantage of microneedle structures is the increase of the permeability of the skin, which increases the delivery of drugs dramatically.

An optimization must be done specifically in order to get the best design of microneedle. There are several methods in optimization such as Genetic Algorithm, Artificial Neural Network, Fuzzy Logic, Particle Swarm Optimization, Evolutionary Algorithm and Cuckoo Search.

2.0OBJECTIVES

The main objective of this project is to optimize the design of two different forms of pyramidal-shaped microneedles which are octagonal and square base for drug delivery system by using Artificial Neural Network and Cuckoo Search approaches. Other than that, there are several more objectives in this project which are:

i. To satisfy the specific range of the parameters which are the height of 200m to 800m, base of 100m, lumens radius of 12.5m and tip angle of 7.16o to 28.08o due to the thickness of human skin and to reduce pain.ii. To demonstrate the fabrication process necessary to construct an array of microneedles containing microchannels.iii. To optimize the microneedles with different pressures range from 1.0MPa to 20.0MPa due to the human skin resistive force of 1.6MPa.iv. To understand the design of microneedle and its application in biomedical field.

3.0LITERATURE REVIEW

Artificial Intelligence (AI) is a multidisciplinary field whose purpose is to computerize activities that currently require human intelligence. It represents humanitys long-time dream of elevating computers beyond the realm of simple machines for the calculation and processing of data. Intelligent behavior of humans includes the capacity for judgment, cognition, observation, learning, comprehension, and theorizing. If computers can display these types of intelligent behavior, they are referred to as having artificial intelligence [1].

More efficient problem solving tools such as Simulated Annealing (SA), Tabu Search (TS), Cuckoo Search (CS), Threshold Accepting (TA), Great Deluge Algorithm (GDA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Neural Network (NN), Evolutionary Algorithm (EA) and Genetic Algorithms (GA) have been applied to solve the design optimization problems. These forms of artificial intelligence have become mainstream methods for solving optimization problems [2].

In order for a microneedle to penetrate the stratum corneum of the skin, a minimum length of around 100 m is necessary. Microneedles are known as painless with a maximum size of around 150 m [3][4]. In general, a microneedle must be able to penetrate into the skin layer at least 40 m so that it can be used effectively as a drug delivery. However, a microneedle must not penetrate far beyond the thickness of the epidermis layer. This is because the layer below the epidermis which is the dermis layer contains blood vessels and nerve pain endings. So, it will feel hurt if the needle penetrates to the dermis layer [5].

Currently, different shapes of microneedles have been developed in MEMS technology using a variety of different materials. Microneedles can be divided into two main groups based on their common design [4]. One is in-plane needles which have shafts that are parallel to the substrate level surface. The second one is out-of-plane needle. The shafts of out-of-plane needles are perpendicular to the substrate surface, so that multiple needles can be fabricated in two-dimensional arrays [1].

There are a lot of microneedles that have been fabricated in various parameters and dimensions. The shape, height, tip angle, base, lumens diameter, material used and number of microneedles array are the most often parameters that designers vary since the past to improve the functionality of microneedle as well as to prevent the failure of the microneedle.

Figure 1: Micro needles developed from single crystal silicon [5].

Artificial Neural Network and Cuckoo Search are two of many artificial intelligence approaches that can be used in microneedle design optimization. Both methods will lead this project in order to get the best design of microneedle.

4.0PROBLEM STATEMENT

The main purpose of this project is to optimize the design variables for microneedle by using one or more methods of artificial intelligence optimization. The important characteristic that needs to be obeyed in this project is to design two different forms of pyramidal-shaped microneedles which are octagonal and square base.

Figure 2: Octagonal micro needle design concept with smooth walled micro channels. (a) and (c) are side views, (b) is an overhead view, (d) is an angled view from above, and (e) is an angled view from underneath.

Figure 3: Square micro needle design concept with smooth walled lumen. (a) and (c) are side views, (b) is an overhead view, (d) is an angled view from above, and (e) is an angled view from underneath.

Furthermore, the design should satisfied the specific range of the parameters which are the height of 200m to 800m, base of 100m x 100m, lumens radius of 12.5m and tip angle of 7.16o to 28.08o. Finally, optimize the microneedles with different pressures, ranges from 1.0 MPa up to 20.0 MPa. Table 1 shows the design variables that are considered for the microneedle optimization.

Table 1: Design variables of microneedle optimization.SHAPEHEIGHT (m)TIP ANGLE ()LUMENS DIAMETER (m)PRESSURE (MPa)

SQUARE20028.08251.0MPa to 20.0MPa

40014.2525

6009.5225

8007.1625

OCTAGONAL20028.08251.0MPa to 20.0MPa

40014.2525

6009.5225

8007.1625

5.0METHODOLOGY

The propose optimization method to be used in this project are Artificial Neural Network and Cuckoo Search. Artificial Neural Networks are connectionist models that attempt to solve computational tasks based on a network of simple computational units (i.e., neurons). Neurons are basic computational units that when combined with appropriate weights between neurons have been shown to solve a variety of problems ranging from classification and pattern recognition to function approximation.

Neural network architectures can be feed forward or recurrent [6]. Cuckoo Search is a heuristic search algorithm inspired by the cuckoo bird breeding behavior [7][8]. The cuckoo breeding analogy is used for developing new design optimization algorithm. The quality of solutions is improved by generating a new solution from an existing solution by modifying certain characteristics [9].

For the design of microneedle, the propose software to be used is ANSYS, while the coding for the optimizer will be done in Matlab software. ANSYS is a finite element analysis (FEA) code generally used in the computer-aided engineering (CAE) field. ANSYS software allows engineers to construct computer models of structures, machine components or systems, apply operating loads and other design criteria and study physical responses, such as stress levels, temperature distributions and pressure [10].

MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical computation. By using MATLAB, one can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran [11]. Both softwares will be combined in order to get the best solution for the microneedle design variables.

Figure 4: Process flow chart.

6.0GANTT CHART

Figure 5: Gantt Chart for the research planning

7.0CONCLUSIONMicro fabricated needles have the potential for inexpensive drug delivery without pain. The results of this research will benefit the medical community, administrators as well as patients, in the ongoing pursuit of improving medical treatments and assuaging the pain typical of hypodermic injections.

A microneedle must be designed with the ability to puncture the skin easily. This includes having a relatively sharp tip and a needle with a fairly high aspect ratio as well as a lumen positioned correctly so that it doesn't plug up during skin penetration. This includes having a relatively sharp tip and a needle with a fairly high aspect ratio as well as a lumen positioned correctly so that it doesn't plug up during skin penetration. The shape of a micro needle must not be determined by fabrication techniques alone but also by considerations of interaction with the skin.

8.0REFERENCES

[1] Hsien-tang Wu, W.-t. H.-t.-m. (July 2011). Application of Genetic Algorithm to the Development of Artificial Intelligence Module System.[2] Glover, F. and Kochenberger, G. A. Handbook of Metaheuristics. Kluwer Academic Publishers, Massachusetts, 2003.[3] J.C. Morrison, C.G. Moore, Microneedle for injection of ocular blood vessels, Patent US 5, 364,374.[4] J. Toon, Taking the ouch out of needles arrays of micron scale microneedles offer new technique for drug delivery, Georgia Tech News, June, 1998.[5] Michael S. Diehl, Design and Fabrication of out of plane Silicon Micro needles with integrated Hydrophobic Micro channels, Department of Mechanical Engineering, Brigham Young University, Dec 2007[6] Karthik Ganesan Pillai, J. W. (2011). Overlapping Swarm Intelligence for Training Artificial Neural Networks.[7] X. S. Yang and S. Deb, "Engineering optimization by cuckoo search", Int. J. of Mathematical Modeling and Numerical Optimisation, vol. 1, no. 4, pp. 330-343, 2010.[8] X. S. Yang and S. Deb, "Cuckoo search via Lvy flights," in World Congress on Nature & Biologically Inspired Computing, Coimbatore, India, pp. 210214, 2009.[9] Anil Kumar, S. C. (2011). Design optimization using Genetic Algorithm and Cuckoo Search.[10] ANSYS Software. (n.d.). Retrieved October 5, 2011, from JLR.com: http://www.jlrcom.com/ansys-software.htm[11] Matlab - Product Description. (n.d.). Retrieved October 5, 2011, from MathWorks: http://www.mathworks.com/products/matlab/description1.html