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].