Background: OPKO Biologics is developing MOD-4023, a long-acting growth hormone (GH), intended for weekly dosing for the treatment of idiopathic GH deficiency in children. At ESPE2015, we presented pharmacokinetic (PK) and pharmacodynamic (PD, based on IGF-1) models for weekly MOD-4023 administration in children aged 311 years. These models confirm that IGF-1 (and IGF-1 SDS) varies during the dosing interval. One critical clinical and research issue is when to optimally sample IGF-1 during a dosing interval and how to interpret that value.
Objective and hypotheses: To evaluate the time course of IGF-1 SDS values during a dosing interval and to determine the relationship between samples obtained at various time points during the interval to peak and mean values.
Method: The previously-described PK and PD models yielded individual (post hoc) parameters for each of 46 adults and 42 children. These models were then used to simulate the IGF-1 plasma concentration profile at steady state based on each subjects. IGF-1 SDS was calculated based on IGF-1, age, and gender. Each subjects peak IGF-1 SDS and values at each of Day 0 (pre-dose) through Day 7 were identified from the simulated data; mean IGF-1 SDS was calculated using linear trapezoids. The relationship between each of peak and mean SDS vs. the value at each day was assessed graphically and by linear regression.
Results: Peak SDS was well predicted by the value obtained at Day 2 (48 hours post-dose) and mean SDS was well predicted by the value at Day 4. Peak SDS correlated strongly with values at Days 35 (r > 0.98) and mean SDS correlated strongly with values at Days 2, 4, 5 (r > 0.98); however, the linear regression deviated from the line of unity.
Conclusion: In children, IGF-1 values at Day 2 can be used as a direct predictor of peak IGF-1 SDS; values at Day 4 are a direct predictor of mean IGF-1 SDS. Using the linear regressions, values at other days (2-5) can be used to model peak and mean IGF-1 SDS.
10 - 12 Sep 2016
European Society for Paediatric Endocrinology