Ethics and Privacy Considerations for Systems Biology Applications in Predictive and Personalized Medicine

Abstract

Integrative analysis and modeling of the omics data using systems biology have led to growing interests in the development of predictive and personalized medicine. Personalized medicine enables future physicians to prescribe the right drug to the right patient at the right dosage, by helping them link each patient’s genotype to their specific disease conditions. This chapter shares technological, ethical, and social perspectives on emerging personalized medicine applications. First, it examines the history and research trends of pharmacogenomics, systems biology, and personalized medicine. Next, it presents bioethical concerns that arise from dealing with the increasing accumulation of biological samples in many biobanking projects today. Lastly, the chapter describes growing concerns over patient privacy when large amount of individuals’ genetic data and clinical data are managed electronically and accessible online.

Survival prediction for lung cancer patients by integrating clinical and molecular features using machine learning

“…The results indicates that the combination of energy and clinical features can be a good strategy to predict the survival of the patients, that may help doctors in taking optimal treatment decisions. Due to advancement in the computational speed, and the rise of deep learning, there is a growing interest in the field of personalized medicine [5], [6].…”