Design of a gene gun

• Main Author: Tan, Charlene Shih Lang.
• Other Authors: Ooi Kim Tiow
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Bioengineering
• Online Access: http://hdl.handle.net/10356/16239
• Institution: Nanyang Technological University

Scientific progress in biological science has brought about the emergence of genetic engineering. With the rising popularity of genetics in this technological era, the use of gene gun has become increasingly important. The gene gun provides a delivery method of introducing new genetic material into cells. In this project, a design optimization study for a gene gun design was carried out by integrating the gene gun simulation model with optimization algorithm. Before carrying out design optimization, the mathematical model of the gene gun was first studied in detail to understand its working concept, the simulation process and most importantly, the mathematical concept used for the program simulation. During the simulation, the range of the gene gun parameters was determined after several numerical trials. This was to ensure that the parameters in analysis fall within the geometrical constraints of the gene gun. The results of the parametric study were plotted and the effects of the various design parameters on the gene gun performance were then studied. From the study of the parameters, the length of Chamber A, L3, length of Chamber B, L5, diameter of piston rod, D3 and diameter of Chamber A and B, D4 were found to have the most significant effect on the performance of the gene gun. Thereafter, these selected significant variables were integrated into the optimization program so that optimization search for the optimal pellet velocity, Vpellet could be done. The results of the optimization show that the final pellet velocity is about 260mm/s after several optimization searches. This value is 1.6 times more than the initial pellet velocity, indicating that the performance of the gene gun had improved. It is evident from the findings that the use of gene gun simulation model together with the optimization algorithm allows the proper selection of design parameters to achieve an overall optimum performance of a gene gun.