Background: The development of immediate-release tablets requires an appropriate balance between mechanical strength, disintegration, and drug dissolution. Binder and superdisintegrant concentrations are important formulation variables that may influence these quality attributes. Objective: The present study aimed to investigate the combined effects of Povidone K-30 and sodium starch glycolate (SSG) on the pharmaceutical properties of immediate-release ibuprofen tablets using a 3² factorial design. Materials and Methods: Nine formulations (F1–F9) containing 200 mg of ibuprofen per tablet were investigated by varying Povidone K-30 and SSG concentrations at three levels. Povidone K-30 was evaluated at 2%, 4%, and 6%, while SSG was evaluated at the same concentration levels. The prepared formulations were assessed for average tablet weight, thickness, hardness, friability, disintegration time, drug content, and in vitro drug release. The reported experimental findings were interpreted in relation to the individual and combined effects of the selected excipients. Results: Average tablet weights ranged from 399 to 402 mg, hardness ranged from 62 to 86 N, and friability ranged from 0.42% to 0.81%. Drug content varied between 98.25% and 100.50%. Disintegration time ranged from 115 to 280 seconds. Formulations F3 and F6 demonstrated approximately 99% drug release at 30 minutes. F3 exhibited a disintegration time of 115 seconds, whereas F6 showed 125 seconds, a hardness of 72 N, friability of 0.53%, and drug content of 100.10%. The reported results indicated that increasing SSG concentration generally improved disintegration and drug-release performance, while increasing binder concentration improved mechanical strength. Conclusion: The findings demonstrate the usefulness of factorial formulation development for examining excipient-related changes in immediate-release ibuprofen tablets. F6 represents a promising formulation when mechanical strength and dissolution are considered together; however, definitive selection requires verified statistical analysis and predefined multiresponse optimization criteria.
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Gupta* et al. (2026) studied this question.
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