Introduction: Mycophenolic acid (MPA), the active drug moiety of mycophenolate, is a potent immunosuppressant agent, which is increasingly being used in the treatment of patients with various autoimmune diseases. Despite the accumulation of promising clinical data on the benefits of mycophenolate in autoimmune diseases, there is a relative lack of data on its pharmacokinetics and pharmacodynamics in these populations.
Objective: To provide an overview of the published population pharmacokinetic studies detailing structural models, typical parameter estimates and covariates, and to review pharmacodynamics studies.
Methods: A literature search was conducted using PubMed and EMBASE databases using the following search terms: ‘mycophenolate mofetil’, ‘MMF’, ‘mycophenolate sodium’, ‘EC-MPS’, ‘mycophenolic acid’, ‘MPA’, ‘pharmacokinetic’, ‘pharmacodynamic’, ‘population model(ling)’ and ‘NONMEM’. Bibliographies of relevant papers were also reviewed.
Results: Twelve articles were included in this review: eight describing pharmacodynamic studies and four describing population pharmacokinetic studies. Seven pharmacodynamics studies described adult populations whereas one study involved a combination of children and adolescents. MMF was administered in seven pharmacodynamic studies while both MMF and enteric-coated mycophenolate sodium (EC-MPS) was administered in one study. Seven studies found a significant relationship between MPA exposure and clinical outcomes. MPA exposure correlated well with treatment efficacy (treatment response, disease activity score, disease activity markers) but the relationship between MPA exposure and adverse events was less clear. Three population pharmacokinetic models were developed in adult patients and one was developed in a paediatric/adolescent population. Mycophenolate mofetil (MMF) was used in all population pharmacokinetic studies. A bi-exponential elimination model was most often selected to describe the disposition of total MPA. Various covariates were tested and creatinine clearance was most often identified as a factor that could explain the observed inter-individual variability in CL/F. With inclusion of covariates inter-individual variability in CL/F ranged from 34% to 49%. Due to small subject numbers all population pharmacokinetic models were validated internally.
Conclusions: Further pharmacokinetic and pharmacodynamic studies comprising larger groups of patients with more diverse covariates and conditions are warranted to provide further insight. External validation with a different dataset would have provided stronger justification for choosing one model above the rest.