New frontiers in oncology: Immune checkpoint inhibitors in combination therapy

Semimechanistically Based Modeling of Pembrolizumab Time-Varying Clearance Using 4 Longitudinal Covariates in Patients With Non-Small Cell Lung Cancer

Time-varying clearance (CL) has been recently recognized in U.S. Food and Drug Administration drug labels for oncology monoclonal antibodies. Pembrolizumab population CL at steady state decreased about 20% from the first dose, and individual CL changes varied from 75% decrease to 25% increase, which were correlating with disease conditions. From mechanism of action perspective, this research explored the longitudinal covariate effect on pembrolizumab CL based on data from a phase II/III clinical trial in patients with non-small cell lung cancer. Time courses of sum of the longest tumor dimensions, lymphocyte count, albumin, and lactate dehydrogenase were first characterized separately, and the post hoc parameters of each individual patient were fixed in the subsequent semimechanistically based modeling analysis. Pembrolizumab time-varying CL was assumed to be associated with the patient's sum of the longest tumor dimensions, lymphocyte count, albumin, and lactate dehydrogenase, and tumor-related pembrolizumab CL was assumed to be a fraction of total pembrolizumab CL in the semimechanistically based modeling.

New Strategies Using Antibody Combinations to Increase Cancer Treatment Effectiveness

Antibodies have proven their high value in antitumor therapy over the last two decades. They are currently being used as the first-choice to treat some of the most frequent metastatic cancers, like HER2⁺ breast cancers or colorectal cancers, currently treated with trastuzumab (Herceptin) and bevacizumab (Avastin), respectively. The impressive therapeutic success of antibodies inhibiting immune checkpoints has extended the use of therapeutic antibodies to previously unanticipated tumor types. These anti-immune checkpoint antibodies allowed the cure of patients devoid of other therapeutic options, through the recovery of the patient’s own immune response against the tumor. In this review, we describe how the antibody-based therapies will evolve, including the use of antibodies in combinations, their main characteristics, advantages, and how they could contribute to significantly increase the chances of success in cancer therapy. Indeed, novel combinations will consist of mixtures of antibodies against either different epitopes of the same molecule or different targets on the same tumor cell; bispecific or multispecific antibodies able of simultaneously binding tumor cells, immune cells or extracellular molecules; immunomodulatory antibodies; antibody-based molecules, including fusion proteins between a ligand or a receptor domain and the IgG Fab or Fc fragments; autologous or heterologous cells; and different formats of vaccines. Through complementary mechanisms of action, these combinations could contribute to elude the current limitations of a single antibody which recognizes only one particular epitope. These combinations may allow the simultaneous attack of the cancer cells by using the help of the own immune cells and exerting wider therapeutic effects, based on a more specific, fast, and robust response, trying to mimic the action of the immune system.