A pediatric quantitative systems pharmacology model of neurofilament trafficking in spinal muscular atrophy treated with the antisense oligonucleotide nusinersen. (5th December 2022)

• Record Type: Journal Article
• Authors: Paris, Alessio; Bora, Pranami; Parolo, Silvia; MacCannell, Drew; Monine, Michael; van der Munnik, Nick; Tong, Xiao; Eraly, Satish; Berger, Zdenek; Graham, Danielle; Ferguson, Toby; Domenici, Enrico; Nestorov, Ivan; Marchetti, Luca
• Is Part Of: CPT: pharmacometrics & systems pharmacology. Volume 12:Number 2(2023)
• Page Start: 196
• Page End: 206
• Publication Date: 2022-12-05
• Subjects: Pharmacokinetics -- Periodicals; Pharmacology -- Periodicals; Pharmacokinetics; Periodicals; 615.05
• DOI: 10.1002/psp4.12890
• Languages: English
• ISSNs: 2163-8306

Abstract

Abstract: Phosphorylated neurofilament heavy subunit (pNfH) has been recently identified as a promising biomarker of disease onset and treatment efficacy in spinal muscular atrophy (SMA). This study introduces a quantitative systems pharmacology model representing the SMA pediatric scenario in the age range of 0–20 years with and without treatment with the antisense oligonucleotide nusinersen. Physiological changes typical of the pediatric age and the contribution of SMA and its treatment to the peripheral pNfH levels were included in the model by extending the equations of a previously developed mathematical model describing the neurofilament trafficking in healthy adults. All model parameters were estimated by fitting data from clinical trials that enrolled SMA patients treated with nusinersen. The data from the control group of the study was employed to build an in silico population of untreated subjects, and the parameters related to the treatment were estimated by fitting individual pNfH time series of SMA patients followed during the treatment. The final model reproduces well the pNfH levels in the presence of SMA in both the treated and untreated conditions. The results were validated by comparing model predictions with the data obtained from an additional cohort of SMA patients. The reported good predictive model performance makes it a valuable tool for investigating pNfH as a biomarker of disease progression and treatment response in SMA and for the in silico evaluation of novel treatment protocols.