PRediction analysis of pharmacokinetic parameters of several oral systemic drugs using In Silico method

Objective: This research aims to observe the pharmacokinetic parameters that can be predicted using a software, discover the best software to predict pharmacokinetic properties, and analyze the correlation between pharmacokinetic parameters used as descriptors with absorption percentage (%ABS) from references. Methods: This research was conducted using Molinspiration, QikProp, admetSAR, SwissADME, Chemicalize, and pkCSM software. This research analyzed 34 oral systemic drug compounds for absorption rate and six descriptors comprising molecular weight (MW), logP, hydrogen bond acceptor (HBA), hydrogen bond donor (HBD), polar surface area (PSA), and pKa. Results: SwissADME showed the most accurate prediction of MW, logP, and HBD. Chemicalize showed the most accurate prediction of HBA, PSA, and pKa. Further, admetSAR showed the most accurate prediction of Caco-2 permeability. The highest R value was obtained from the correlation between %ABS with Caco-2 permeability on 34 drug compounds (R=0.8211). Conclusion: The highest R value was obtained from the correlation between %ABS with Caco2 permeability on 34 drug compounds (R=0.8211), which showed a significant relationship (*p<0.001). This indicates that oral systemic drugs are affected by Caco-2 permeability. Moreover, the result of this research can be considered for the development of oral systemic drugs.