AI-ML and System Biology for Drug Discovery in Livestock

Abstract

Advanced research methods have enhanced the productivity and problem solving abilities of scientific development in the field of drug designing and discovery. Various diseases have been problematic for the survival of human civilisation and livestock. Available methods that can provide results for diseases include; computer aided drug designing, system biology, and machine learning. Due to the diversity of livestock and multiple disease types, robust methods are required for drug discovery. Artificial intelligence has paved the way for faster problem solving innovations and discoveries in multiple aspects, such as economics, engineering, and healthcare. Systems biology plays a pivotal role in the biological evaluation of living beings. System-level understanding of livestock animals is the need of the hour for effective drug discovery, which includes genomic, proteomic, enzymatic, and metabolic pathways involved in a biological system. Livestock deaths due to diseases are reported worldwide, which creates a demand for drug discovery solutions. Multiple diseases for various livestock have been investigated, and drug discovery has been a great relief for those specific diseases. In this context, we have communicated about the integration of all the above mentioned aspects (artificial intelligence, machine learning, systems biology, drug discovery) to come up with a better resolution for the livestock in terms of drug development.