○ Precision diagnosis involves refining the characterisation of the diabetes diagnosis for therapeutic optimisation or to improve prognostic clarity using information about a person’s unique biology, environment and/or context.

○ Precision diagnostics may involve subclassifying the diagnosis into subtypes, such as is the case in MODY, or utilising probabilistic algorithms that help refine a diagnosis without categorisation.

○ Careful diagnosis is often necessary for successful precision therapy, whether for prevention or treatment. This is true where subgroup(s) of the population must be defined, within which targeted interventions will be applied and also where one seeks to determine whether progression towards disease has been abated.

○ Precision diagnosis can be conceptualised as a pathway that moves through stages, rather than as a single step,. The diagnostic stages include (1) an evaluation of prevalence based on epidemiology, including age, or age at diagnosis of diabetes, sex and ancestry; (2) probability based on clinical features; and (3) diagnostic tests that are interpreted in the light of (1) and (2). A diagnosis in precision medicine is a probability-based decision, typically made at a specific point in the natural history of a disease, and neither an absolute truth nor a permanent state.

○ Precision therapeutics involves tailoring medical approaches using information about a person’s unique biology, environment and/or context for the purposes of preventing or treating disease (see ‘precision prevention’ and ‘precision treatment’, below).

○ Precision prevention includes using information about a person’s unique biology, environment and/or context to determine their likely responses to health interventions and risk factors and/or to monitor progression towards disease.

○ Precision prevention should optimise the prescription of health-enhancing interventions and/or minimise exposure to specific risk factors for that individual. Precision prevention may also involve monitoring of health markers or behaviours in people at high risk of disease, to facilitate targeted prophylactic interventions.

○ Precision treatment involves using information about a person’s unique biology, environment and/or context to guide the choice of an efficacious therapy to achieve the desired therapeutic goal or outcome, while reducing unnecessary side effects.

○ Today, the objective of precision therapy is to maximise the probability that the best treatment of all those available is selected for a given patient. It is possible that in the future, precision diabetes medicines will be designed according to the biological features of specific patient subgroups, rather than for the patient population as a whole.

○ Precision prognostics focuses on improving the precision and accuracy with which a patient’s disease-related outcomes are predicted using information about their unique biology, environment and/or context.

○ The focus of precision prognostics includes predicting the risk and severity of diabetes complications, patient-centered outcomes, and/or early mortality.

○ Precision monitoring may include the detailed assessment of biological markers (e.g. continuous glucose monitoring), behaviours (e.g. physical activity), diet, sleep and psychophysiological stress.

○ Precision monitoring can be achieved using digital apps, cutaneous or subcutaneous sensors, ingestible sensors, blood assays, etc.

○ The intelligent processing, integration and interpretation of the data obtained through precision monitoring are key determinants of success.

○ Precision monitoring may be valuable for precision prevention (e.g. in type 1 diabetes), precision diagnostics (e.g. where diagnoses are based on time-varying characteristics) and precision prognostics (e.g. where disease trajectories are informative of the development of key outcomes).