A personalized medicine approach using artificial intelligence

The use of artificial intelligence in personalizing medicine is a revolutionary new approach to improving the quality of life for all. Personalized medicine involves providing healthcare tailored to the lifestyle, genes, and environment of a particular individual. In the modern world, genetics, artificial intelligence, and growing access to health data present an opportunity to make precise personalized patient care a clinical reality.
Healthcare is a very personal industry, so no two illnesses are the same, so each person’s treatment is unique and different. The advantage of AI is that it can measure the transcription in real-time of all the genetic profile of the individual within the organism. Doctors are faced with enormous amounts of data. Finding and analyzing a combination of genes whose expression levels distinguish the groups of patients is a difficult task for a human, but for artificial intelligence, it is relatively straightforward[10].
Computers, artificial intelligence, and smart healthcare monitoring devices in the modern world make it very easy for us to collect and store this information. Is there any possibility for your labs to move from your center lab to your smartphone, your home, or even inside of your body to measure drug levels or other kinds of data? Our modern era is centered around genomics. Your genomic profile can help you understand whether you need a low dose, a high dose, or perhaps another combination of drugs.
As an example, imagine your doctor or your pharmacist was able to integrate this information into their workflow database, augmented with artificial intelligence, so that they would be able to understand which of the 22,000 approved drugs to use and in what dose.
Artificial intelligence in healthcare plays a vital role in personalizing care. Artificial intelligence has already become an essential element of IT services. In the near future, it brings together advances in biomedical data sciences, imaging, and genomics, mobile technologies, environmental sciences, social engagement, networking, and communication in order to make therapies, diagnostics, and proactive, more individualized, predictive, and precise therapies.
However, machine learning and big data are already used in the pharmaceutical R&D field in broad ways to discover and develop new drugs. This big data will probably originate from improved and more refined monitoring health devices, which will be used to gather information to build prediction models for the improvement of more accurate predictions.
In the future, personalized medicine is likely to reduce drug-development costs, treatment costs, and time, which will lead to improved health outcomes. For personalised medicine to be a breakthrough in the medical healthcare system, everyone has to play an important role from patient to regulatory authorities and researchers to leaders by developing new creative ideas, experimental diagnostics, and personalized care protocols [11,12].