Essential Learning Tools For Precision Medicine

Precision medicine seeks to circumvent this by taking into account subpopulation variability in genetic, socio-environmental, and lifestyle factors to propose precise therapies. It aims for accurate measurement of molecular, environmental, and behavioral factors contributing to health and disease thus leading to more precise diagnosis, rational disease prevention strategy, treatment selection, and development of newer therapies. The various tools by which precision medicine seeks to achieve its goals are omics, pharmaco-omics, big data, artificial intelligence, machine learning (ML), environmental, social, and behavioral factors, and integration with preventive and public health.

Some of the learning tools for precision medicine are listed below.


The main tools of precision medicine are Big data, artificial intelligence, various omics, pharmaco-omics, environmental and social factors, and the integration of these with preventive and population medicine. Environmental, social, and behavioral factors are as important or more important than genetic factors in most complex diseases, and managing these factors form an important part of precision medicine. Finally integrating precision with preventive and public health makes “precision medicine” a complete final product that will change the way medicine will be practiced in the future.

Big Data

The data obtained from clinical information, complex biomolecular assays, radiological investigations, and social and environmental factors are collected together forming a large amount of data for an individual and subpopulation which is referred to as the Big Data. These data are obtained through electronic medical records, scanners, biosensors, social media, and various omics including DNA sequences, transcriptomes, proteomes, metabolomes, epigenomes, and microbiomes

Artificial Intelligence (AI) and Machine Learning (ML)

Artificial intelligence (AI) and machine learning (ML) can process volumes of data promptly through the bioinformatics system. AI and ML can integrate and convert Big Data into useful diagnostic and therapeutic interventions.45 Data storing, handling, and analysis are best carried out using these methods. They can also handle all statistical challenges more efficiently than traditional methods.


Remote patient monitoring, telemedicine, and AI use in radiology during the pandemic were some of the modalities which also highlighted the growing importance of digitalization and precision medicine.

Environmental, social, and behavioral factors

It has been increasingly realized that apart from genes, there are many other important determinants of health. Genetic factors have been attributed to account for only up to 30% of determining the health of any individual.  Unlike genetic factors, most behavioral, social, and environmental factors can be modified to alter the risk of any given disease for an individual in the future especially if we know the genetic predisposition of the disease.

Integration with preventive medicine and public health

With the increasing ability to not only measure but also to store and share data related to health in addition to the abundance of available genetic testing tools, the integration of precision medicine with public health will be a very productive union.

Precision medicine is thus the new age medicine and its various tools as described previously will change the way medicine is practiced in the future. New strategies of precision medicine will be an important member of clinical and translational medicine and need to be further developed and validated in the clinical basket for clinical practice. In addition to therapeutic strategies, precision medicine will be a new approach to health care and disease prevention in larger populations.

Kindly visit for additional advice and recommendations about attending medical school. If you're seeking a trustworthy internet source, please check out the whole medical school package at the URL below.

Back to blog