Pyry Valitalo 1,2, Elke H.J. Krekels 1,3, YuWei Lin 1, Stephen Duffull 1, S.Y. Amy Cheung 1,4
1 Certara (Radnor, United States), 2 University of Eastern Finland (Kuopio, Finland), 3 Leiden Academic Centre for Drug Research, Leiden University (Leiden, The Netherlands), 4 University of Warwick (Warwick, United Kingdom)
Introduction: During drug development, sponsors are generally required to study their drug candidate in children. Sometimes the drug’s benefit-risk balance in children is established by matching the paediatric exposures to adult exposures [1]. For exposure-matching, accurate characterization of PK in children is important. It has been proposed that paediatric PK studies should be powered to have confidence intervals for the PK parameters clearance (CL) and volume of distribution (Vd) within a pre-specified range [2]. However, Vd may be more influential for drugs whose effects are driven by peak concentrations or early exposure measures, whereas CL is more directly related to steady-state exposure metrics such as AUC. Precision in both CL and Vd may not be needed to achieve precision in the clinically relevant exposure endpoint. Methods are needed to explicitly link parameter precision to precision in clinically relevant exposure metrics to align paediatric study design with decision-making objectives.
Objectives: We show how to calculate the expected precision in the clinically relevant exposure metric based on precision in PK parameters. We assume the availability of dense-sampling adult PK data, which makes the model deterministically identifiable in general; however, paediatric CL and Vd parameters are estimated using only the data relevant for each age-group.
Methods: A two-compartment PK model with first-order absorption and elimination, with PK parameters of {ka=1 1/h, CL=1 L/h, Vc=10 L, Vp=30 L, Q=5 L/h} was used and inter-individual variability in all PK parameters was set to be log-normally distributed and uncorrelated between individuals, with log-standard deviation of 0.3. Log-additive residual error with a standard deviation of 0.3 was used. Allometric scaling with fixed exponents of 0.75 for CL and 1.0 for Vd was applied. A fixed CL maturation function was included in the model, with a PMA50 of 300 days and a Hill coefficient of 2.
Calculations of precision in exposure metrics were conducted for age-groups of <2 years, 2 to <6 years, 6 to <12 years, 12 to <18 years, and adults. Representative weights were simulated as a function of age[3], and assuming full-term gestation. To prevent information sharing between adults and children, the model was parameterized to estimate CL, Vc and Vp uniquely for each age-group.
Two different clinical use scenarios were considered: Acute-use case, in which Cmax after a single dose was the clinically relevant driver of the drug effect, and a chronic-use case in which the steady-state Cavg upon QD dosing was the clinically relevant drug effect driver. Doses were set to be on mg/kg basis, with a 70 kg adult receiving a 100 mg dose.
Two study designs were evaluated, with both designs having n=15 adult subjects, and n=10 paediatric subjects in each age-group. The first study design emphasized the absorption profile, with PK samples taken at {.5,1,2,4,12} h after first dose in children, and {0.1,0.25,0.5,0.75,1,1.5,2,3,5,8,12} h post-dose in adults. The second study design emphasizes the steady-state profile, with PK samples taken upon QD dosing at steady state at {0,1,3,6,12} h after the last dose in children, and {0.1,0.25,0.5,0.75,1,1.5,2,3,5,8,12} h in adults.
The expected Fisher Information was calculated based on previously published equations [4,5]. Monte Carlo simulations were used to propagate variance-covariance in PK parameters to precision in Cmax and Cavg.
Results: In the design emphasizing the absorption phase, Cavg precision was low in paediatric age-groups (RSE 0.591 for adults, and 0.407-0.737 for the different paediatric age-groups), and the Cmax precision was higher (RSE 0.153 for adults, and 0.173-0.193 for paediatric age-groups). Conversely, the study design emphasizing the steady-state profile resulted in Cmax precision being low (RSE 0.691 for adults, and 0.76-1.03 for children) and Cavg precision high (RSE 0.0875 for adults, and 0.0997-0.11 for children). For the design emphasizing the absorption phase, the ratio of CL, Vd and Vp parameter RSE over Cmax RSE was 1 to 25.5. For the design emphasizing the steady-state profile, the RSE ratio was 1.63 to 4.23. These findings illustrate that a study design can result in the clinically relevant exposure measure being captured with high precision, even if not all paediatric PK parameters are captured with high precision.
Conclusion: Paediatric study designs should consider focusing on the expected precision of the clinically relevant exposure measure, instead of on the expected precision of CL and Vd.
References:
References:
[1] Simons CWM, Maton LCH, van Dartel M, van den Heuvel M, den Otter L, Versantvoort C, Colin PJ, Koomen JV. A review on the role of extrapolation as basis for paediatric marketing authorization applications of medicines in the EU. Br J Clin Pharmacol. 2025 May;91(5):1500-1510. doi:10.1111/bcp.16395.
[2] Wang Y, Jadhav PR, Lala M, Gobburu JV. Clarification on precision criteria to derive sample size when designing pediatric pharmacokinetic studies. J Clin Pharmacol. 2012 Oct;52(10):1601-6. doi: 10.1177/0091270011422812.
[3] Sumpter AL, Holford NHG. Predicting weight using postmenstrual age--neonates to adults. Paediatr Anaesth. 2011 Mar;21(3):309-15. doi: 10.1111/j.1460-9592.2011.03534.x.
[4] Retout S, Mentré F. Further developments of the Fisher information matrix in nonlinear mixed effects models with evaluation in population pharmacokinetics. J Biopharm Stat. 2003 May;13(2):209-27. doi: 10.1081/BIP-120019267.
[5] Foracchia M, Hooker A, Vicini P, Ruggeri A. POPED, a software for optimal experiment design in population kinetics. Comput Methods Programs Biomed. 2004 Apr;74(1):29-46. doi: 10.1016/S0169-2607(03)00073-7
Reference: PAGE 34 (2026) Abstr 11984 [www.page-meeting.org/?abstract=11984]
Poster: Methodology - Study Design