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Personalised medicine

Treatment based on the individual's genetics

In modern medicine, the concept of genetic risk factors is well understood. Certain individuals will be predisposed to disease based on their family history and DNA. Similar to

how we inherit traits like eye colour from our parents, susceptibility to conditions such as diabetes or cancer can also be inherited. However, it is only recently that we have begun to

understand that an individual's genetic makeup will affect not only their risk for disease but also their reaction to treatment.

Understanding risk factors is crucial for diagnosing disease and implementing preventative

measures to maintain a patient's health. Utilising a person’s unique DNA could provide

insights into their genetic predisposition towards different health conditions, thus accelerating the diagnostic process. Giving patients the ability to make informed decisions about their health based on their genetic risk could help them prevent disease. For example, women carrying the BRCA1 gene may opt for mastectomies to reduce the risk of breast cancer later in life.

Personalised medicine doesn’t only focus on risk; it can also directly influence how

treatments are administered. Genomic data can indicate which medicines are most likely to

be effective and whether there may be associated side effects. The Human Genome Project

has made tremendous advancements in the last decade. Combining this data with medical

records could provide doctors with insights into the molecular-level interactions of different

drugs with individual patients.

Personalised medicine in practice

Cancer serves as the best example of the importance of personalised medicine. Patients

have a unique combination of risk factors from their DNA and lifestyle. However, the same

treatments are often offered to everyone with the same type of cancer. The specific

mutations that cause a cell to become cancerous are unique to each patient. The genetic

makeup of cancer cells may determine which treatment should be focused on, and this is

where personalised medicine plays a critical role.

An example of personalised medicine already in use is for lung cancer, particularly for

cancers with mutated Epidermal Growth Factor Receptors (EGFRs). EGFRs are surface

proteins involved in cell growth and division. If there is a mutation, it can result in unpredictable and uncontrollable cell proliferation. There are drugs specifically designed to

treat lung cancer cells carrying this EGFR mutation, with their mechanism of action based on

this. These drugs would likely be ineffective for lung cancers with different mutations, as they

have different mechanisms of action. Personalised medicine tailors treatment to the genetic

makeup of a person to achieve a bespoke and hopefully improved outcome.

Transcriptomics, the study of RNA and its alterations instead of DNA, may be a future

avenue of investigation in understanding cancer biology. Tumours can arise due to mutated

RNA or abnormal transcription events, indicating that DNA is not the only genetic material

relevant to oncology. There have been promising innovations in personalised vaccines

tailored to each patient. Tissue from an individual is biopsied and studied, and using

identified biomarkers, a custom mRNA vaccine can prime the immune system to attack

cancer cells.

Future potential

Genetic variation in a patient’s response to drugs can significantly affect their reactions to

treatment. By combining genomic data and AI technology, scientists are developing

predictive algorithms to create individualised medication plans for patients, potentially

eliminating the guesswork in prescriptions. Personalised precision medication holds great

potential. However, the primary limitation currently lies in the cost of treatment. Medical

services are stretched thin across the population, making bespoke treatments currently

unfeasible. Personalised medicine is expected to improve as new genetic biomarkers are

discovered and catalogued, leading to more sophisticated genomic databases over time. As

sequencing technology becomes more mainstream, associated costs are likely to decrease,

possibly making personalised medicine standard practice in the future.

Written by Charlotte Jones

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