Prediction of human pharmacokinetics of phosphorodiamidate morpholino oligonucleotides in Duchenne muscular dystrophy patients using viltolarsen

Several modified antisense oligonucleotides (ASOs) have recently been approved for clinical use. Some are phosphorodiamidate morpholino oligomers (PMOs), which, unlike other nucleic acids, are not negatively charged. Thus, PMOs differ from other ASOs in their pharmacokinetic (PK) properties. Drugs with a PMO backbone have been administered to Duchenne muscular dystrophy pediatric patients; however, appropriate methodologies are not currently available to predict their human PK from nonclinical data. In this study, we used viltolarsen as a representative PMO to investigate the applicability of the allometric scaling approach to human PK prediction. We first summarized the nonclinical and clinical PK data for viltolarsen as showing high total clearance, low serum protein binding, metabolic resistance, and urinary excretion as the unchanged drug in both animals and humans. We then investigate the PK of viltolarsen in mice, rats, cynomolgus monkeys, and dogs and used the results, with body weight, to extrapolate to humans by several methods. The estimate of human total clearance obtained from cynomolgus monkeys was the best, and body weight may be the key factor in accurately predicting human total clearance. In contrast, all of the well known prediction methods for the volume of distribution at steady state gave underestimates. However, the human PK profiles predicted from the PK parameters in cynomolgus monkeys fit the observed human plasma concentrations well. These results are expected to contribute to the further development of PMOs. Significance Statement We investigated how to predict the human pharmacokinetics of phosphorodiamidate morpholino oligomers from nonclinical data. The estimates of human pharmacokinetic parameters and profiles determined from cynomolgus monkeys by an allometric scaling approach were the most suitable, and the cynomolgus monkey body weight may be the key factor in accurately predicting human total clearance.