Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived 'metabolite constellation' (GFR(NMR)). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFR(NMR) equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFR(NMR) had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (-1.0; 1.0) mL/min/1.73 m(2) for GFR(NMR) vs. -6.0 (-7.0; -5.0) mL/min/1.73 m(2) for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI(2012)) (p \textless 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFR(NMR) vs. 47.3% (43.2; 51.5) for CKD-EPI(2012) (p \textless 0.010). Thus, GFR(NMR) holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.