Personalised medicine is an approach to healthcare that aims to tailor prevention, diagnosis, treatment or health management to the characteristics and circumstances of an individual. These characteristics can include medical history, age, sex-related biological factors, symptoms, preferences, lifestyle, environment, previous treatment responses, laboratory findings and genetic or other biological information. The term is sometimes used interchangeably with precision medicine, although the concepts can carry slightly different emphases.
Personalised medicine traditionally highlights the individual patient and the tailoring of care, whereas precision medicine often emphasises measurable biological differences and the identification of clinically meaningful subgroups. Personalised care does not necessarily require genetic testing or advanced technology. Choosing a treatment according to a person's previous response, kidney function, ability to take a medicine regularly, values or practical circumstances can also be a form of individualised care. The underlying principle is that healthcare decisions should account for relevant differences between patients rather than assuming that one approach is equally suitable for everyone.
Personalised medicine includes several levels of tailoring. At the most basic level, clinicians already individualise treatment by considering symptoms, examination findings, age, medical history, allergies, other medicines and organ function. More advanced personalised approaches incorporate genetic, genomic, proteomic or metabolic information. Pharmacogenomics can identify inherited differences that influence drug metabolism or response, potentially helping with selection or dosing for particular medicines. In oncology, tumour profiling can help identify treatments that correspond to molecular characteristics of a cancer.
In rare diseases, genomic analysis can help determine the underlying diagnosis and occasionally identify a treatment directed at the causal pathway. Personalised prevention may use an individual's risk factors to determine appropriate screening or interventions, although risk prediction is not the same as certainty of disease. These approaches operate along a spectrum rather than representing a single technology or medical specialty.
Personalised medicine differs from the idea of designing a completely unique treatment for every person. Most clinical care relies on interventions that have been tested in groups of patients and shown to have benefits that can reasonably be applied to individuals. Personalisation involves using relevant information to decide which evidence-based option is most appropriate, rather than abandoning standard evidence in favour of intuition.
For example, two patients with the same diagnosis may receive different treatments because they have different allergies, kidney function, disease severity, genetic characteristics or previous treatment responses. Conversely, two people with very different backgrounds may appropriately receive the same treatment when the evidence indicates that it is effective for both. Personalised medicine therefore does not mean that every medical decision is completely unique. It means that individual differences are incorporated into decisions when those differences are clinically relevant.
Genetics has become an important component of personalised medicine because inherited DNA variation can influence disease susceptibility, drug metabolism and biological response. However, genetic information represents only one component of a person's overall health. Gene expression can change in response to disease and environment, while epigenetic modifications can affect gene activity without changing the underlying DNA sequence. Age, diet, exercise, infections, coexisting diseases, other medicines and environmental exposures can also influence treatment response.
In cancer, the relevant genomic information may come from the tumour rather than the person's inherited DNA, because tumours acquire somatic changes during their development. Distinguishing germline from somatic information is therefore essential. Personalised medicine is best understood as the integration of multiple types of information rather than as a synonym for genetic medicine.
The history of personalised medicine predates modern genomics. Physicians have long adjusted treatment according to individual symptoms, physical characteristics, disease severity and previous responses. The development of laboratory medicine, imaging, pharmacology and evidence-based clinical guidelines increased the ability to distinguish clinically meaningful patient groups. Molecular genetics and high-throughput sequencing subsequently expanded the possibilities for tailoring care according to biological characteristics. The Human Genome Project and subsequent advances in genomic medicine contributed to the modern use of personalised and precision terminology.
Pharmacogenetics developed from observations that inherited differences could affect responses to drugs, while molecular oncology demonstrated that cancers with the same anatomical origin could have different molecular drivers. These developments shifted some areas of medicine towards more detailed classification of disease and more targeted interventions.
Personalised medicine has potential advantages but also important limitations. It can help avoid ineffective treatments, reduce some medication-related adverse effects, identify people who need particular surveillance and provide more specific diagnoses. It may also help patients with unusual or rare disorders by identifying a molecular cause that would otherwise remain unclear. However, personalised approaches can be expensive, require specialised expertise and produce results that are difficult to interpret.
Not every genetic or molecular finding has a clinically useful treatment associated with it. Testing can reveal uncertain or unexpected information, and health data require strong privacy and security protections. Access can also be unequal when advanced testing is available in some healthcare systems or populations but not others. The value of a personalised approach therefore depends on the quality of the evidence, the accuracy of the information used and whether the resulting information changes management in a beneficial way.
Personalised medicine also incorporates the patient's preferences and circumstances, which distinguishes it from purely molecular approaches. A clinically effective treatment may not be practical for someone because of administration requirements, cost, occupational circumstances, other medicines or personal priorities. Shared decision-making allows patients and clinicians to combine scientific evidence with the person's goals and values. This is different from choosing a treatment without evidence: personal preferences help determine which suitable options are acceptable, while clinical evidence helps establish which options are likely to be safe and effective. Personalised medicine can therefore overlap with patient-centred care, individualised medicine and tailored healthcare, although these terms can be used differently by different organisations.
The central challenge is ensuring that personalisation improves outcomes rather than merely increasing the amount of information collected. A personalised test or algorithm is clinically useful only when it produces reliable information that can support an appropriate decision. This requires analytical accuracy, clinical validation, evidence that acting on the information improves outcomes and systems capable of incorporating results into care. Personalised medicine is consequently an evolving field rather than a finished model of healthcare. Its future is likely to involve increasing integration of genomic data with electronic health records, imaging, laboratory measurements, longitudinal monitoring and clinical decision-support systems, while maintaining attention to privacy, equity, patient autonomy and evidence quality.
