Background Type 2 diabetes (T2D) affects approximately 589 million adults worldwide and is the leading driver of cardiovascular disease, nephropathy, neuropathy, retinopathy, and premature mortality. Despite the availability of multiple second-line glucose-lowering drug classes, treatment intensification beyond metformin remains a trial-and-error process. Pharmacogenomics offers a principled route to genotype-guided prescribing: genetic variants modifying glycaemic response to glucose-lowering medications have been identified, yet the field remains limited by small sample sizes, absence of a metformin comparator arm in randomised trials, and follow-up too short to examine hard complication endpoints. Real-world data with extended follow-up address these gaps directly. Aim Identify genetic variants associated with glycaemic response to glucose lowering medication. Hypothesis Common genetic variants modulate the degree of glycaemic benefit and identifying these variants will enable genotype-guided treatment selection that outperforms current clinical practice. Methods Eligible participants are identified from the Swedish Infrastructure for Medical Population-Based Life-Course and Environmental Research (SIMPLER), with extensive longitudinal risk factor data since 1987, newly available multi omics data, and linkage to the National Prescribed Drug Register, National Diabetes Register, National Patient Register, and Swedish Cause of Death Register. The primary outcome is treatment response. All aims use an intention-to-treat design. Cox proportional hazards regression is implemented.