○ Type 1 diabetes. The only existing therapy for types 1 diabetes is insulin. Developments in long-acting and glucose-sensitive insulins are improving the health and well-being of people with type 1 diabetes, as are technological advances in continuous glucose monitoring devices, insulin pumps, closed loop systems and the artificial pancreas.

○ Type 2 diabetes. It has long been recognised that type 2 diabetes is heterogeneous in its aetiology, clinical presentation and pathogenesis. Yet, traditionally, trials of therapeutic intervention do not recognise this variation.

○ Monogenic forms of diabetes are already amenable to precision treatment, if correctly diagnosed. For example, HNF1A-MODY (MODY3), HNF4A-MODY (MODY1) and ABCC8-MODY (MODY12) are acutely sensitive to the glucose-lowering effects of sulfonylureas. Alternatively, individuals with GCK-MODY (MODY 2) can have unnecessary treatments stopped.

○ With increasing efforts to map patients with type 2 diabetes in aetiological space using clinical and molecular phenotype, physiology and genetics, it is likely that this increasingly granular view of type 2 diabetes will lead to increasing precision therapeutic paradigms requiring evaluation and potential implementation. Genetic variation not only can capture aetiological variation (i.e. genetic variants associated with diabetes risk) but also variation in drug pharmacokinetics (absorption, distribution, metabolism, excretion [ADME]) and in drug action (pharmacodynamics).

○ In contrast, ‘true’ type 2 diabetes is a common, complex disease characterised by thousands of etiological variants, each contributing to a small extent to diabetes risk. Thus, it remains uncertain that genetic variants will be identified that are highly predictive of drug outcomes in type 2 diabetes, even if process-specific polygenic risk scores are derived (where all variants on an aetiological pathway are combined to increase power).

○ Barriers to implementation. The current and growing burden of diabetes is not from Western white populations but from other ethnic groups, in particular, South and East Asians. Yet, these populations are under-represented in clinical trials and, in particular, in attempts to understand variation in drug outcomes.

○ Because the diabetes phenotype can vary markedly by ethnic group, it is likely that complications and drug outcomes will differ between populations.

○ Many of the approaches gaining traction in precision medicine generate massive datasets that are a burden to store and require powerful computational servers for analysis.

○ Undertaking appropriately designed clinical trials for precision treatments that meet the current expectations of regulatory authorities may be challenging given the many subgroups within which treatments will need to be evaluated. Innovative clinical trials will likely be needed and real-world evidence will likely need to be part of the evaluation process.

○ Translating complex information to patients about genetic (and other omics) tests in a clear, concise and clinically relevant manner will require healthcare providers to be appropriately trained.

○ Research gaps. For drug outcomes, there is a pressing need to move beyond early glycaemic response and examine variation in response in terms of cardiovascular outcomes and mortality rate, especially of the newer agents, such as SGLT2i and GLP-1RA, with focus on specific patient subgroups. Identifying predictive markers (especially genetic markers) of serious adverse events in patients treated with these drugs presents an additional area urgently in need of greater attention.

○ Need for functional studies to determine the mechanism(s) of action underlying specific gene variants

○ Need for better understanding of the pathophysiology of diabetes to inform on new therapeutic targets

○ Need to study broader populations/ethnic groups

○ Need for understanding outcomes of highest relevance to patients

○ Need for decision support tools to implement precision diabetes medicine in clinical practice

○ Need to demonstrate that approaches are cost-effective