Background: Osteosarcoma is the most common primary malignant bone tumor in children and adolescents (1, 2). Mycophenolate mofetil (MMF) is an FDA-approved drug used as an immunosuppressive agent in organ transplantation with the potential to be repurposed as an anti-cancer agent. (3, 4). MMF is a prodrug of mycophenolic acid (MPA), which is an inhibitor of inosine monophosphate dehydrogenase. MPA treatment significantly inhibits osteosarcoma cell growth and induces cell cycle arrest and apoptosis (4). Furthermore, the in vivo experiment demonstrated the inhibition of tumor growth and lung metastasis of osteosarcoma in mice treated with MMF (4). Unfortunately, there is limited clinical information addressing the use of MMF in individuals with osteosarcoma (5). This is the first population pharmacokinetics (PK) study of MMF for osteosarcoma treatment in Thai patients in a phase II trial. The aims of this study were to develop a population PK model of MPA and determine the population PK parameters and their interindividual variability for a phase II trial in Thai patients with high-grade locally advanced or metastatic osteosarcoma and Thai healthy volunteers.
Method: A single oral dose of MMF 1.5 or 2.5 g was administered to 15 Thai patients with high-grade locally advanced or metastatic osteosarcoma during phase II trials and 1 g was administered to 16 Thai healthy volunteers. Serial blood samples were collected at 0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 10, and 12 hours post-dose in patients and at 0, 0.33, 0.67, 1, 1.5, 2, 4, 6, 8, 10, 12, 24, 36, and 48 hours post-dose in healthy volunteers. Population PK parameters were estimated using a nonlinear mixed-effects modeling approach (NONMEM®). Body weight, age, gender, UGT1A1, UGT1A7, UGT1A8, and UGT2B7 genotypes were investigated as covariates using a stepwise approach. Goodness-of-fit (GOF) plots were used to evaluate the model fit. The prediction-corrected predictive checks (pcVPC) and bootstrapping were performed to determine the predictability and reliability of the final model.
Results: The PK of MPA in Thai healthy volunteers and Thai osteosarcoma patients was best described by a two-compartment model with first-order elimination. No significant covariates were identified, probably due to the small sample size. In patients with high-grade locally advanced or metastatic osteosarcoma, the population estimated apparent clearance (CL/F), apparent volume of distribution of the central compartment (Vc/F), apparent inter-compartment clearance (Q), apparent volume of distribution of the peripheral compartment (Vp/F), and absorption rate constant (Ka) of MPA were estimated to be 16.3 L/h, 12.3 L, 12.7 L/h, 240 L, and 1.39 h-1 respectively. The interindividual variability (IIV) of CL/F, Vc/F, and KA of MPA were 149.1%, 139.5%, and 56.6%, while the IIV of Q/F and Vp/F of MPA was not estimated. The residual variability (RUV) of MPA was best described by a combined proportional (58.12%) and additive error model (0.18 mg/L). In healthy volunteers, the estimated CL/F, Vc/F, Q/F, Vp/F, and Ka of MPA were 24.5 L/h, 24 L, 18.8 L/h, 125 L, and 2.23 h-1, respectively. The IIV of CL/F, Q/F, and KA were 32.7%, 175%, and 31.8%, respectively, while the IIV of Vc/F and Vp/F was not estimated. The RUV of MPA was described by a proportional error model (74.2%). The GOF plots showed no obvious bias in both models. The pcVPC demonstrated adequate predictive performance of models. The median and 95% confidence intervals (CI) generated from bootstrap analysis were comparable to the values obtained from NONMEM for both models.
Conclusion: A two-compartment model adequately describes the pharmacokinetics of MPA in Thai healthy volunteers and Thai patients with high-grade locally advanced or metastatic osteosarcoma. Based on the results of this study, the pharmacokinetic parameters of MPA are different between healthy volunteers and osteosarcoma patients. Osteosarcoma patients had lower CL/F and Vc/F of MPA compared to healthy volunteers.
Reference
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