Optimal Monitoring of Weekly IGF-I Levels during Growth Hormone Therapy with Once-Weekly Somapacitan

Abstract

Context: Somapacitan is a long-acting growth hormone (GH) in development for once-weekly treatment of GH deficiency (GHD). Optimal monitoring of insulin-like growth factor-I (IGF-I) levels must account for weekly IGF-I fluctuations following somapacitan administration. Objective: To develop and assess the reliability of linear models for predicting mean and peak IGF-I levels from samples taken on different days after dosing. Design: A pharmacokinetic/pharmacodynamic model was used to simulate IGF-I data in adults and children following weekly somapacitan treatment of GHD. Setting and Patients: 39 200 IGF-I profiles were simulated with reference to data from 26 adults and 23 children with GHD. Intervention(s): The simulated dose range was 0.02 to 0.12 mg/kg for adults and 0.02 to 0.16 mg/kg for children. Simulated data with >4 average standard deviation score were excluded. Main Outcome Measure(s): Linear models for predicting mean and peak IGF-I levels based on IGF-I samples from different days after somapacitan dose. Results: Robust linear relationships were found between IGF-I sampled on any day after somapacitan dose and the weekly mean (R2 > 0.94) and peak (R2 > 0.84). Prediction uncertainties were generally low when predicting mean from samples taken on any day (residual standard deviation [RSD]≤0.36) and peak from samples taken on day 1 to 4 (RSD≤0.34). IGF-I monitoring on day 4 and day 2 after dose provided the most accurate estimate of IGF-I mean (RSD<0.2) and peak (RSD<0.1), respectively. Conclusions: Linear models provided a simple and reliable tool to aid optimal monitoring of IGF-I by predicting mean and peak IGF-I levels based on an IGF-I sample following dosing of somapacitan. A short visual summary of our work is available (1).