Exposure–response analysis is a method used to optimize the dose of an active substance to achieve the maximal therapeutic efficacy while ensuring patient safety. In therapeutic antibodies exhibiting target-mediated drug disposition, a false positive exposure–response relationship is frequently observed. Target-mediated drug disposition is a special case of pharmacokinetics in which the active substance binds with high affinity to its pharmacological target, leading not only to its therapeutic effect but also to the elimination of the antibody–receptor complex. A false positive exposure–response relationship may result in unjustified dose escalation and unnecessary clinical trials that ultimately fail to demonstrate improved clinical outcomes at higher doses.
In this master's thesis, we investigated the frequency of false positive exposure–response relationships using the therapeutic antibody rituximab, which exhibits target-mediated drug disposition, as a case study across clinical studies with different designs. We used two published population pharmacokinetic models of rituximab, both developed using concentration data from patients with diffuse large B-cell lymphoma treated at the Institute of Oncology Ljubljana. Using the Monte Carlo method, we simulated different clinical trial designs in four virtual patient cohorts. Drug dose and final clinical treatment outcome were assigned independently. We evaluated the effects of the number and magnitude of dose levels, the number of patients, and the number of treatment cycles on the occurrence of false positive exposure–response relationships.
Monte Carlo simulations of rituximab pharmacokinetics provided insights into the occurrence of false positive exposure–response relationships, the pharmacokinetic behaviour of monoclonal antibodies, and factors influencing optimal clinical trial design. We demonstrated that the probability of a false positive relationship is highest when only a single dose level is used. Introducing two or more dose levels and increasing the difference between them reduces this risk. The inclusion of a third dose level further reduced the probability of a false positive exposure–response relationship. We also showed that increasing the number of enrolled patients increases the likelihood of detecting a false positive exposure–response relationship.
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