Suthunya Chupradit 1, Thanakorn Vongjarudech 2, Nut Koonrungsesomboon 3,4, Dumnoensun Pruksakorn 5,6, Nahathai Dukaew 3,4, Parunya Chaiyawat 5, Nutnicha Sirikaew 5, Patcharawadee Thongkumkoon 5, Mingkwan Na Takuathung 3,4, Baralee Punyawudho 1
1 Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University (, Thailand), 2 Department of Pharmacy, Faculty of Pharmacy, Mahidol University (, Thailand), 3 Department of Pharmacology, Faculty of Medicine, Chiang Mai University (, Thailand), 4 Clinical Research Center for Food and Herbal Product Trials and Development (CR-FAH), Faculty of Medicine, Chiang Mai University (, Thailand), 5 Center of Multidisciplinary Technology for Advanced Medicine (CMUTEAM), Faculty of Medicine, Chiang Mai University (, Thailand), 6 Department of Orthopedics, Faculty of Medicine, Chiang Mai University (, Thailand)
Objective: Osteosarcoma is the most common primary bone malignancy in children and adolescents, and outcomes remain poor for patients with advanced or metastatic disease [1–3]. Recently, mycophenolate mofetil (MMF) has been investigated for its anticancer potential; preclinical studies demonstrated that its active metabolite, mycophenolic acid (MPA), inhibits osteosarcoma cell growth, induces cell cycle arrest and apoptosis, and suppresses tumor growth and lung metastasis in mice [4]. However, a recent Phase II clinical trial yielded negative results potentially due to insufficient drug exposure [5]. While higher doses may be required for therapeutic efficacy, their clinical utility is often limited by poor gastrointestinal and hematological tolerability. Consequently, there is a critical need to obtain pharmacokinetic data to support dose optimization in this population. This study aims to perform the first population pharmacokinetic (PopPK) analysis of MPA in patients with high-grade locally advanced or metastatic osteosarcoma to characterize the sources of variability and provide a framework for model-informed dose optimization.
Methods: Data were pooled from a Phase II study enrolling 15 patients with high-grade locally advanced or metastatic osteosarcoma [5] and a separate study of 16 healthy volunteers. Participants received MMF at doses of 3 or 5 g/day (1.5 or 2.5 g twice daily) for up to four 28-day cycles, whereas healthy volunteers received a single 1 g oral dose. In the patient cohort, intensive pharmacokinetic sampling was conducted during Cycle 1 at both the first dose and at steady state. Serial blood samples were collected at 0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 10, and 12 hours post-dose for patients and at 0, 0.33, 0.67, 1, 1.5, 2, 4, 6, 8, 10, 12, 24, 36, and 48 hours post-dose for healthy volunteers. Population pharmacokinetic analysis was performed using nonlinear mixed-effects modeling in NONMEM® (version 7.5), supported by Perl-Speaks-NONMEM (PsN) [7]. MPA concentrations below the limit of quantification (BLQ), 0.05 mg/L, were handled using the M3 method [6]. Data management, statistical processing, and visualization were performed using R. Parameter estimation was conducted using the Importance Sampling (IMP) algorithm with interaction and the Laplacian option. The Fisher Information Matrix was utilized to estimate relative standard errors (RSE).
Results: A two-compartment model with first-order elimination, delayed absorption, and an enterohepatic recirculation (EHC) adequately described the concentration-time profiles. The EHC was characterized by 5 transit compartments mimicking the transfer from the bile duct back to the gut, effectively capturing the observed secondary peaks in both groups. Allometric scaling of body weight was incorporated a priori as a significant covariate on apparent clearance (CL/F) and central volume of distribution (Vc/F), with fixed exponents of 0.75 and 1 respectively. The typical CL/F was estimated to be 19.1 L/h (23.6% RSE) with an inter-individual variability (IIV) of 48.0% CV (27.8% RSE). The typical Vc/F was 25.8 L (14.7% RSE) with an IIV of 60.6% CV (16.3% RSE). The mean transit absorption time (MTT) was 0.42 h (33.4% RSE), with an IIV of 89.3% CV and an inter-occasional variability (IOV) of 135.2% CV (62.5% RSE). EHC transit time from bile duct to gut for enterohepatic recirculation was fixed at 10 hours based on data exploration and consistent with published literature [8,9]. Notably, patients with osteosarcoma exhibited a 21.9% (41.3% RSE) longer transit through bile duct back to the gut compared with healthy volunteers, suggesting slower hepatic recirculation in the patient group. Residual unexplained variability (RUV) was best described by a proportional error of 65.4% (9.4% RSE) with a fixed additive component of 0.01 mg/L.
Conclusion: This study presents the first population pharmacokinetic model of MPA in patients with high-grade locally advanced or metastatic osteosarcoma, successfully characterizing the complex EHC and high inter-individual variability. The identified delays in absorption and slower EHC transit times in cancer patients compared to healthy volunteers highlight a unique physiological shift in this population. This PopPK model provides a robust tool to optimize dosing strategies, balancing efficacy and safety to overcome the narrow therapeutic window. Ultimately, these results provide a bridge for the future application of MMF in osteosarcoma through model-informed precision dosing.
References:
[1] Mirabello L et al. International osteosarcoma incidence patterns in children and adolescents, middle ages and elderly persons. Intl Journal of Cancer 2009; 125(1):229–34.
[2] Pruksakorn D et al. Age Standardized Incidence Rates and Survival of Osteosarcoma in Northern Thailand. Asian Pac J Cancer Prev 2016; 17(7):3455–8.
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[5] Koonrungsesomboon N et al. Efficacy and safety of mycophenolate mofetil in patients with high-grade locally advanced or metastatic osteosarcoma (ESMMO): a multicenter, phase II clinical trial. Int J Clin Oncol 2025; 30(11):2362–74.
[6] Wijk M et al. A Pragmatic Approach to Handling Censored Data Below the Lower Limit of Quantification in Pharmacokinetic Modeling. CPT Pharmacometrics Syst Pharmacol 2025; 14(6):1042–9.
[7] Lindbom L et al. PsN-Toolkit–a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed 2005; 79(3):241–57.
[8] Annapandian V et al. Mycophenolic acid area under the curve recovery time following rifampicin withdrawal. Indian J Nephrol 2010; 20(1):51.
[9] Sam WJ et al. Population Pharmacokinetics of Mycophenolic Acid and Metabolites in Patients With Glomerulonephritis. Therapeutic Drug Monitoring 2010; 32(5):594–605.
Reference: PAGE 34 (2026) Abstr 12019 [www.page-meeting.org/?abstract=12019]
Poster: Drug/Disease Modelling - Oncology