Predicting rapid analgesic onset of ibuprofen salts compared with ibuprofen acid: Tlag, Tlow, Tmed, and a novel parameter, TCmaxRef

OBJECTIVE

This study evaluated the early absorption characteristics of ibuprofen salt formulations and standard ibuprofen acid (the reference).

METHODS

In this open-label, crossover, single-center study (NCT02452450) in 32 healthy, fasted adults receiving single oral doses (400 mg ibuprofen) of ibuprofen lysine, ibuprofen liquid capsule, ibuprofen sodium, ibuprofen acid, and paracetamol, intensive blood sampling was conducted for up to 6 h. Time between dosing and the start of absorption (T_lag); a novel parameter, time at which the test formulations (ibuprofen salts) reached the observed maximum plasma concentration (C_max) of the reference (standard ibuprofen acid) (T_CmaxRef); and time to achieve therapeutic plasma concentration were measured.

RESULTS

Ibuprofen was absorbed more rapidly from the salt formulations than the reference; T_lag was 3.3-6.4 min for salt formulations compared with 10.9 min for the reference, and 100% of subjects had a T_lag ≤ 5 min for ibuprofen lysine, compared with 61% for ibuprofen liquid capsule, 21% for ibuprofen sodium, and 7% for the reference. T_CmaxRef was 3.22-5.74-times shorter for salt formulations than for the reference (all p < .0001). The salt formulations reached therapeutic levels earlier than the reference (all p < .0001). All formulations were well tolerated.

CONCLUSIONS

This study shows that ibuprofen salts are absorbed faster than ibuprofen acid. T_lag and T_CmaxRef demonstrated early start and increased speed of absorption of salts compared with the reference, and may predict more rapid onset of analgesia.

Can the confidence in long range atmospheric transport models be increased? The pan-european experience of ensemble

Is atmospheric dispersion forecasting an important asset of the early-phase nuclear emergency response management? Is there a 'perfect atmospheric dispersion model'? Is there a way to make the results of dispersion models more reliable and trustworthy? While seeking to answer these questions the multi-model ensemble dispersion forecast system ENSEMBLE will be presented.