Tamara van Donge (1), Elena Guerini (1), Amaury O’Jeanson (2), Neil Parrott (1), Marc Arca (1), Cordula Stillhart (3), Nassim Djebli (1,4*)
(1) Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche AG, Basel, Switzerland (2) Department of Pharmacy, Uppsala University, Uppsala, Sweden (3) Roche Pharmaceutical Research and Development, Synthetic Molecules Technical Development, F. Hoffmann-La Roche AG, Basel, Switzerland (4) Luzsana Biotechnology, Clinical Pharmacology and Early Development, Basel, Switzerland * Current affiliation
Objectives: The study aimed to establish pediatric dosing guidelines for alectinib, an ALK inhibitor used in adults with ALK-positive advanced NSCLC [1,2]. While adult dosing is well-established, pediatric patients with ALK-positive tumors lack sufficient clinical data for dosing due to the rarity of these malignancies. This research sought to address this gap by integrating pharmacometric analyses with physiologically-based pharmacokinetic (PBPK) modeling to tailor adult dosing for pediatric use. We conducted a comprehensive analysis using population pharmacokinetics (popPK), which did not assume ontogeny and scaled doses based solely on body size, complemented by PBPK modeling to provide a holistic understanding of the PK properties of alectinib in pediatrics, to tailor adult dosing for pediatric use.
Methods: Since a comparable exposure-response relationship in both adult and pediatric patients was expected, the method aimed to identify the pediatric dose that would achieve the effective alectinib exposure observed in adults (i.e.: target AUCss value of 7500 ng⋅h/mL). Alectinib is a lipophilic basic compound with a very low aqueous solubility (BCS class IV) and, to enhance its bioavailability, sodium lauryl sulfate (SLS) is added to the capsule formulation as an inactive ingredient [3,4,5]. Also, Alectinib is mainly metabolized by CYP3A4 (40%) and to a lesser extent by other cytochrome P450 enzymes (10%) into the active metabolite M4 [6]. To account for those characteristics, a base adult PBPK model was created, integrating both drug-specific and system-specific parameters. To capture the absorption phase of alectinib, the advanced dissolution, absorption, and metabolism (ADAM) model available in Simcyp™ was used. The accuracy of this model was then enhanced using data from adult clinical studies (a bioequivalence & food study and a Phase 3 study). To generate a virtual pediatric population, the physiological and anatomical parameters were adjusted and, as a result, physiological parameters such as CYP3A4 tissue concentrations were scaled to the specific pediatric age groups (i.e.: 1-3.5 years, 3.5-5.8 years, and 5.8-7.8 years), accounting for the effect of maturation. The impact on the ontogeny on alectinib metabolism was evaluated on the CYP3A4 pathway for all age groups by comparing Upreti and Simcyp default ontogeny functions and on the non-CYP3A4 pathway in the youngest groups by comparing slow, fast and no ontogeny. Lastly, the predicted exposures from the PBPK model were compared to those obtained from popPK-based simulations for different body weight categories. The popPK model included body weight based allometric scaling of apparent clearance and volume of distribution of both alectinib and M4 [7].
Results: The PBPK predicted exposures were in line with the observed value in the bioequivalence & food study with a median AUC ratio from 0.94 to 1.18 and with the observed value in the Phase 3 study with a median AUCss ratio from 0.81 to 1.02. For the youngest age group, the predicted median AUCss was 1.3 fold higher with Upreti ontogeny function compared to Simcyp function on the CYP3A4 pathway and was 1.35-fold higher when applying the slow ontogeny function on the non-CYP3A4 pathway compared to no ontogeny. Therefore, for this lower age category both the Upreti function and the slow ontogeny were incorporated into the pediatric PBPK model, as these reflected a more conservative approach from a safety point of view, and the selected dose was 100 mg BID. For the two other age groups, minor differences in median AUCss between either slow, no or fast ontogeny groups were observed and the dose of 230 mg BID for 3.5-5.8 years and 270 mg BID 5.8-7.8 years were selected. With those three doses for the youngest age groups, the median AUCss reflected the target exposure for alectinib of 7500 ng⋅h/mL and for all older age groups the recommended doses by popPK were accurate.
Conclusions: The alectinib doses suggested by popPK modeling included strong assumptions (no ontogeny assumed, doses only scaled on body size), while the mechanistic PBPK modeling takes into account the impact of immature enzymes for the youngest patients, together with the differences in absorption in one combined PBPK model. The current PBPK model confirmed the recommended doses by the popPK model but only down to 3.5 years and that for younger patients a dose of 100 mg BID should be used instead of the 190 mg BID suggested by popPK.
References:
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[6] Cleary Y, et al. Model-Based Assessments of CYP-Mediated Drug-Drug Interaction Risk of Alectinib: Physiologically Based Pharmacokinetic Modeling Supported Clinical Development. Clinical pharmacology and therapeutics 104 505-514. (2018)
[7] Hsu JC, et al. Pharmacometric analyses of alectinib to facilitate approval of the optimal dose for the first-line treatment of anaplastic lymphoma kinase-positive non-small cell lung cancer. CPT Pharmacometrics Syst Pharmacol 10 1357-1370. (2021)
Reference: PAGE 32 (2024) Abstr 10985 [www.page-meeting.org/?abstract=10985]
Poster: Drug/Disease Modelling - Oncology