against infectious disorders, epidemics, and pandemics. Hence, in this article, we

would explore the importance of various AI tools that can be utilized for drug

discovery and precision medicine.

Keywords

Molecular phenotype · Clinical phenotype · Personalized drugs · Digital

biomarkers · Omics · Artificial intelligence · Machine learning algorithm ·

Computational biology

1.1

Introduction

In determining the causes of different illnesses, we are in a higher situation than at

any other time in history. Our understanding of disease pathogenesis has changed

significantly due to the advent of newer technology and recent scientific

breakthroughs. Scientists today have a much more refined view of living molecules,

and science is advancing toward understanding the pathophysiology of disease at the

molecular level of living beings ranging from humans to plants, such as dementia,

cancer, heart disease, and diabetes, which are developed during a person’s life span.

New and innovative diagnostic techniques for genetic disorders are now being

developed. Epigenetic modifications, in tandem with genomics and genetics, are

helping to explain and control several diseases. The construction of causal network

models consisting of the genomic regions has become possible by combining the

developed molecular phenotype profiling with deep clinical phenotyping. These

network models can influence the levels of transcripts, proteins, and metabolites

and can be exploited in various ways in diagnosing diseases and personalized drug

development. Digital biomarkers (BM) may help with disease diagnosis in multiple

ways, including patient identification to treatment recommendation. Individualized

healthcare programs, custom-specific nutrition, living practices, and better therapies

will benefit from this kind of treatment. The use of “omics” technology and large

sample sizes has resulted in vast data sets, providing a wealth of knowledge about

different illnesses and their links to intrinsic biology. The analysis of such extensive

data requires sophisticated computational and statistical methods. Insignificant data

processing, artificial intelligence (AI), and deep machine learning algorithms are

beneficial. New data can be converted into usable knowledge to allow for faster

diagnosis and treatment choices using these advanced technologies such as artificial

intelligence, machine learning algorithms, computational biology, and digital BMs

(Seyhan and Carini 2019). As a result, it is expected that such advancements would

aid in the fight against infectious disorders, epidemics, and pandemics. Hence, in this

article, we would explore the importance of various AI tools that can be utilized for

drug discovery and precision medicine.

4

R. C. Sobti et al.