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.
Keywords: Drug discovery, Livestock, Machine learning, Systems biology.
