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Precision medicine (PM) is a medical model that proposes the customization of healthcare. The approach undergoes many medical decisions, treatments, and practices to provide individually tailored therapy. In precision medicine, diagnostic testing helps selects appropriate and optimal therapies based on the context of a patient's genetic content or other molecular or cellular analysis. Tools employed in precision medicine can include molecular diagnostics, imaging, and analytics. Precision medicine can be applied to treating terminal diseases such as cancer, cardiovascular disease, cystic fibrosis, Alzheimer's disease etc. Precision medicine is not yet an optimal technique, developments are needed to help the procedure to mature.

Relationship to personalized medicine
In explaining the distinction from a similar common term of personalized medicine, the National Research Council explains: "Precision Medicine refers to the tailoring of medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs or medical devices that are unique to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology or prognosis of those diseases they may develop, or in their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not. Although the term 'personalized medicine' is also used to convey this meaning, that term is sometimes misinterpreted as implying that unique treatments can be designed for each individual."

On the other hand, precision medicine can also include the meaning of creating unique medical products for particular individuals. For example, "...patient-specific tissue or organs to tailor treatments for different people." Hence, the term in practice has so much overlap with "personalized medicine" that they are often interchangeable.

Scientific basis
Precision medicine often involves applying panomic analysis and systems biology to analyze the cause of an individual patient's disease at the molecular level and then to utilize targeted treatments (possibly in combination) to address that individual patient's disease process. The patient's response is then tracked as closely as possible, often using surrogate measures such as tumor load (v. true outcomes, such as 5-year survival rate) and the treatment finely adapted to the patient's response. The branch of precision medicine that addresses cancer is referred to as "precision oncology". The field of precision medicine that is related to psychiatric disorders and mental health is called "precision psychiatry."

Inter-personal difference of molecular pathology is diverse, so as inter-personal difference in the exposome, which influence disease processes through the interactome within the tissue microenvironment, differentially from person to person. As the theoretical basis of precision medicine, the "unique disease principle" emerged to embrace the ubiquitous phenomenon of heterogeneity of disease etiology and pathogenesis. The unique disease principle was first described in neoplastic diseases as the unique tumor principle. As the exposome is a common concept of epidemiology, precision medicine is intertwined with molecular pathological epidemiology, which is capable of identifying potential biomarkers for precision medicine.

Practice
The ability to provide precision medicine to patients in routine clinical settings depends on the availability of molecular profiling tests, e.g., individual germline DNA sequencing. Precision medicine currently individualizes treatment mainly based on genomic analyses (e.g., Oncotype DX ). Concurrently, several promising technology modalities are being developed, from techniques combining spectrometry and computational power to real-time imaging of drug effects in the body. Many different aspects of precision medicine are getting tested in research settings (e.g., proteome, microbiome). Still, in routine practice, not all available inputs are used. The ability to practice precision medicine is also dependent on the knowledge bases available to assist clinicians in taking action based on test results. Early studies applying omics-based precision medicine to cohorts of individuals with undiagnosed disease has yielded a diagnosis rate ~35% with ~1 in 5 of newly diagnosed receiving recommendations regarding changes in therapy.

On the treatment side, PM can involve the use of customized medical products such drug cocktails produced by pharmacy compounding or customized devices. It can also prevent harmful drug interactions, increase overall efficiency when prescribing medications, and reduce costs associated with healthcare.

Artificial intelligence in Precision Medicine
Artificial intelligence is providing paradigm shift toward precision medicine. Machine learning algorithms are used for genomic sequencing to analyze and draw inferences from the vast amounts of data patients and healthcare institutions recorded in every moment. AI techniques are used in precision cardiovascular medicine to understand genotypes and phenotypes in existing diseases, improve patient care quality, enable cost-effectiveness, and reduce readmission and mortality rates.

Precision Medicine Initiative
In his 2015 State of the Union address, U.S. President Barack Obama stated his intention to fund an amount of $215 million to the "Precision Medicine Initiative" of United States national. A short-term goal of the Precision Medicine Initiative was to expand cancer genomics to develop better prevention and treatment methods. In the long-term, the Precision Medicine Initiative aimed to build a comprehensive scientific knowledge base by creating a national network of scientists and embarking on a national cohort study of one million Americans to expand our understanding of health and disease. The Mission Statement of the Precision Medicine Initiative read: "To enable a new era of medicine through research, technology, and policies that empower patients, researchers, and providers to work together toward development of individualized treatments". In 2016 this initiative was renamed "All of Us" and an initial pilot project had enrolled about 10,000 people by January 2018.

''' What are the benefits of Precision medicine? '''

Precision medicine helps health care providers better understand the many things — including environment, lifestyle, and heredity — that play a role in a patient's health, disease, or condition. This information lets them more accurately predict which treatments will be most effective and safe, or possibly how to prevent the illness from starting in the first place. In addition  benefits are


 * shift the emphasis in medicine from reaction to prevention


 * predict susceptibility to disease


 * improve disease detection


 * preempt disease progression


 * customize disease-prevention strategies


 * prescribe more effective drugs


 * avoid prescribing drugs with predictable side effects


 * reduce the time, cost, and failure rate of pharmaceutical clinical trials


 * eliminate trial-and-error inefficiencies that inflate health care costs and undermine patient care

Application of Precision Medicine to Cancer
Cancer treatment shouldn't be performed as a one-fits-all approach because very different genetic mutations can cause tumor growth in the same region. More targeted therapies such as precision medicine could help identify tumor growth and formulate molecularly targeted drugs that can eliminate the root cause with minimum side effects ..

The current DNA sequencing technology NGS has enabled researchers to identify tens and thousands of genetic mutations linked to tumor cells .. The precision medicine approach utilizes this information to use screening techniques such as liquid biopsy on cancer patients to extract real-time information regarding circulating tumor DNA (ctDNA ) .. The presence of ctDNA implies tumor cells somewhere inside the patient's body. Researchers can localize the tumor cells by referring to the unique variation among genes specific to certain types of cancer .. For instance, a mutated APC presence will suggest that doctors examine colon and rectum areas because APC is unique to colorectal cancer. Some other mutations in tumor proteins such as p53 and KRAS contribute to colorectal or pancreatic cancer. In like manner, these proteins provide regulation for cell divisions, but the molecular approach is very different. Different mutations are responsible for each type of regulatory protein to become non-functional. Researchers need to use genomic analysis to find the responsible mutation .. Molecular-targeted drugs are then applied only to affect the mutated cells instead of unnecessarily damaging other cells that aren't contributing to tumor growth. Studies indicate that patients treated with precision medicine experienced a better response; they also retained more extended periods without recurrence and survival.

Application of Precision Medicine to Cardiovascular Diseases
Cardiovascular diseases usually develop slowly and across multiple decades. It is the leading cause of death in America today. The massive cluster of people potentially affected by this disease provides enough data for the precision medicine approach. The disease's slow development offers ample opportunities to identify risks in the early stage of the disease, offering patients preventative strategies.

Recent technology advancements and big data have allowed researchers to discover genetic variants strongly associated with cardiovascular conditions such as hypertension, coronary artery disease, etc., which significantly improves the predictability of the disease among people with heredity for vulnerability to cardiovascular disease. Testing can be done anytime in life, which helps patients to take early precautions by taking treatment resulted from pharmacogenetics.

In addition to genetics, environmental factors such as exercise, diet, air quality, etc., also contribute to developing cardiovascular diseases. Scientists are making continuous progress in improving epigenetic tools to study the intrinsic relationship between the environment and genetics. A closer study of the connection between genetics and the external world will enhance the treatment's accuracy in determining subjects' vulnerabilities due to external factors.

Application of Precision Medicine to Cystic fibrosis
Cystic fibrosis is a model case for demonstrating the use of precision medicine. Symptoms are very similar among patients, but the cause of the disorder is very distinguishable. Mutation-specific treatment can restore health from patients suffering from specific mutations.

Cystic fibrosis is a genetic disease caused by a mutation on chromosome 7 responsible for CFTR regulator protein. Failure in the protein will cause chronic diseases such as lung infection, pancreas inflammation, and malabsorption, which leads to malnutrition.

There are roughly five categories of cystic fibrosis, each with different effects on the CFTR protein. Group I leads to altered RNA and absent or truncated CFTR protein. Class II leads to folding or maturation defects that cause insufficient CFTR in the cell membrane. Category III mutations are related to failure defect that results in limit channel opening. Category IV and V are due to either reduced chloride conductance through the CFTR channel or reduced CFTR protein level in the cell membrane.

The right modulator can be applied to regulate the disorder based on the classification of CFTR mutation. Potentiator is a type of modulator that works on the CFTR channel present on the cell surface by opening the dysfunctional CFTR channel. The channel's opening increases gating of the abnormal CFTR proteins, which can benefit category III and IV defects. Correctors work by increasing the trafficking of CTFR protein to cell membranes, which can be used jointly with potentiator to restore dysfunction caused by category II mutation. Studies have shown persistent benefits in lung function, weight, and quality of life among patients treated by modulators.

Application of Precision Medicine to Alzheimer's Disease
Currently, drug creation to treat Alzheimer's Disease is very limited, and the results have been unsuccessful. The primary reason is the lack of clinical characterization of the disease due to AD's molecular complexity. Researchers are exploring deep genomic sequencing to expect a revelation that paves the path for a new drug development approach.

Drugs developed until now have perceived Alzheimer's Disease as a homogenous disease. However, the molecular profile of patients with AD shows vast variation. Precision medicine approaches this problem by addressing the molecular cause based on a specific person's risk factors, aiming to administer prevention that explicitly targets the molecular pattern. In addition to the genetic configuration that leads to AD, many underlying environmental factors increase AD's risk. Some of these factors include cerebrovascular disease, traumatic brain injury, or intellectual activity. Thus, to make breakthroughs in precision medicine targeting AD, scientists need to gain more insight into interactions between genes and the environment.

Limitations and Future Developments
The current paradigm for drugs targeting mutations is costly and time-consuming. It cannot address large-based sequencing. Most sequencing tests focus on the presence or absence of a given gene, insertion or deletion, or rearrangement of sequences. The localization of data can cause inaccurate and incomplete data, so discoveries of genetic variations associated with specific diseases will be prevented.

There also needs to be a context of normal to describe diseases. For example, if the genetic variance is present within a person that causes a disease, individual data must be compared to a reference data, so that sequences will correctly reassemble into one that does not code for the condition. To act as a baseline for comparison, it requires a database containing accurate ancestral genomic information, so the frequency of disease-causing variants in ancestral genes can help discover genetic defects. It can also serve as a reference to what a typical sequence looks like for individuals without the disease.

With more sequencing data produced, it will require more storage space to preserve the data and faster speed to access wanted information. An improved organizational approach of data could help with faster retrieval. A new algorithm in processing sequence data, storing only the regions of sequences that contribute to the target of interest, will save space so that more data can be stored.