Developing in Silico Models for Drug Screening
Mentor 1
Mahsa Dabagh
Start Date
28-4-2023 12:00 AM
Description
Pancreatic cancer is one of the leading causes of cancer related deaths in the US and worldwide. This is in large part due to its dismal 5-year survival rate percentage of 7-8%. Because of the complexity of the pancreatic cancer’s microenvironment in pancreas, there is very little in the way of proven successful treatment strategies. Computational biology can be used to make predictions about the response of tumor tissue to drugs by examining impact of various stimuli, such as the drug’s size or physical changes in tumor tissue with malignancy. In our study, we use, LAMMPS, a molecular dynamics open-access software to reproduce the pancreatic cancer tissue and mimic the behavior of tumor tissue's components to develop a dynamic model that can be used to simulate the penetration of drug nanoparticles through tumor tissue and their dynamic interactions with tissue components.
Developing in Silico Models for Drug Screening
Pancreatic cancer is one of the leading causes of cancer related deaths in the US and worldwide. This is in large part due to its dismal 5-year survival rate percentage of 7-8%. Because of the complexity of the pancreatic cancer’s microenvironment in pancreas, there is very little in the way of proven successful treatment strategies. Computational biology can be used to make predictions about the response of tumor tissue to drugs by examining impact of various stimuli, such as the drug’s size or physical changes in tumor tissue with malignancy. In our study, we use, LAMMPS, a molecular dynamics open-access software to reproduce the pancreatic cancer tissue and mimic the behavior of tumor tissue's components to develop a dynamic model that can be used to simulate the penetration of drug nanoparticles through tumor tissue and their dynamic interactions with tissue components.
