Precision medicine in the era of artificial intelligence: implications in chronic disease management

Abstract

Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reaction of the immune system to a variety of stimuli, such as pathogens, damaged cells, and harmful substances. Metabolically triggered inflammation, also called metaflammation or low-grade chronic inflammation, is the consequence of a synergic interaction between the host and the exposome—a combination of environmental drivers, including diet, lifestyle, pollutants and other factors throughout the life span of an individual. Various levels of chronic inflammation are associated with several lifestyle-related diseases such as diabetes, obesity, metabolic associated fatty liver disease (MAFLD), cancers, cardiovascular disorders (CVDs), autoimmune diseases, and chronic lung diseases. Chronic diseases are a growing concern worldwide, placing a heavy burden on individuals, families, governments, and health-care systems. New strategies are needed to empower communities worldwide to prevent and treat these diseases. Precision medicine provides a model for the next generation of lifestyle modification. This will capitalize on the dynamic interaction between an individual’s biology, lifestyle, behavior, and environment. The aim of precision medicine is to design and improve diagnosis, therapeutics and prognostication through the use of large complex datasets that incorporate individual gene, function, and environmental variations. The implementation of high-performance computing (HPC) and artificial intelligence (AI) can predict risks with greater accuracy based on available multidimensional clinical and biological datasets. AI-powered precision medicine provides clinicians with an opportunity to specifically tailor early interventions to each individual. In this article, we discuss the strengths and limitations of existing and evolving recent, data-driven technologies, such as AI, in preventing, treating and reversing lifestyle-related diseases.

Translational precision medicine: an industry perspective

“…To go beyond and fully leverage AI technologies for clinical drug development, it is essential to optimize and validate AI algorithms for use in clinical trials and outcome prediction. AI-powered approaches have the potential to enable precision medicine, particularly in chronic disease conditions, by dissecting complex high-dimensional patient datasets and tailoring drug development [ 115 ]. While traditionally regulatory authorities might not have been perceived as enthusiastic about advanced AI models in biomedical R&D, the landscape is evolving rapidly, exemplified by recent developments in the AI-based medical device space [ 116 , 117 ] and the recent FDA pilot program Innovative Science and Technology Approaches for New Drugs (ISTAND) that incentivizes the use of AI-based algorithms to evaluate patients, develop novel endpoints, or inform study designs.…”

Insights into Nonalcoholic Fatty-Liver Disease Heterogeneity

“…Also, a better phenotyping would allow the implementation of tailored treatment approaches in line with concepts of precision medicine or individualized care. 13 15 161 Since the degree of liver fibrosis has been shown to be closely related to liver-related mortality, 93 94 assessment of this variable is now considered crucial in patient stratification and should be performed with the available noninvasive tools. 159 However, most of these tools are not able to distinguish those patients that show a strong wound healing response and thus more likely to have a resolutive phenotype with spontaneous regression of fibrosis versus those that will have a strong fibrogenic response and will more likely show progression of fibrosis.…”

Applications of artificial intelligence in nuclear medicine image generation

“…Artificial intelligence (AI) technology has been rapidly adopted in various fields (1)(2)(3)(4)(5)(6). With the accumulation of medical data and AI technology development, especially deep learning (DL), data-driven based precision medicine has quickly progressed (7,8). Among the applications of AI in medicine, the most striking is for medical imaging.…”