A novel method for assessing in vitro oncology drug combinations using growth rates.

We propose a new method that allows screening oncology drug combinations using data from in vitro studies to select agents that have the promise of showing a synergistic effect in vivo. In contrast to known approaches that define combination effects either on the concentration scale or on the percent inhibition scale, we use the growth rate of treated cells as a primary indicator of treatment activity. The developed method is based on a novel statistical model that describes the growth of cancer cells that are subject to treatment with a combination of compounds. The model assumes a multicompartment cell population with transition rates between compartments modeled according to biochemical reaction properties, and cells in each compartment growing according to exponential law. This translates to a linear system of ordinary differential equations, whose solution is accurately approximated by a closed-form expression using rapid equilibrium assumptions. Special cases of the aforementioned model represent situations when the combination effect is absent or when the considered drugs act as the same compound. Assuming the normal distribution for the growth rate measurement error, we describe a formal statistical testing procedure to distinguish between different mechanisms of action for the considered compounds, and to test if a significant combination effect is being observed.

Results of a phase 1 study of AME-133v (LY2469298), an Fc-engineered humanized monoclonal anti-CD20 antibody, in FcγRIIIa-genotyped patients with previously treated follicular lymphoma.

PURPOSE: AME-133v is a humanized monoclonal antibody engineered to have increased affinity to CD20 and mediate antibody-dependent cell-mediated cytotoxicity (ADCC) better than rituximab. Safety, pharmacokinetics, and efficacy were assessed in a phase 1/2 trial in patients with previously treated follicular lymphoma (FL). PATIENTS AND METHODS: AME-133v was characterized in vitro by ADCC and cell binding assays. A phase 1 study was conducted in which 23 previously treated patients with FL were assigned sequentially to one of five dose-escalation cohorts of AME-133v at 2, 7.5, 30, 100, or 375 mg/m(2) weekly × 4 doses. RESULTS: AME-133v showed a 13- to 20-fold greater binding affinity for CD20 and was 5- to 7-fold more potent than rituximab in ADCC assays. Cell binding assays showed AME-133v and rituximab competed for an overlapping epitope on the CD20 antigen, and AME-133v inhibited binding of biotinylated rituximab to CD20 in a concentration-dependent manner. AME-133v was well tolerated by patients and common related adverse events included chills and fatigue. One patient experienced a dose-limiting toxicity of neutropenia. AME-133v showed nonlinear pharmocokinetics with properties similar to rituximab. Selective reduction of B cells during and after AME-133v treatment was shown by flow cytometry of peripheral blood. A partial or complete response was observed in 5 of 23 (22%) patients and the median progression-free survival was 25.4 weeks. CONCLUSIONS: AME-133v was safe and well tolerated at the doses tested. AME-133v showed encouraging results as an anti-CD20 therapy in heavily pretreated FL patients with the less favorable FcγRIIIa F-carrier genotype.

Modeling the transition of lung cancer from early to advanced stage.

We present a stochastic parametric model of the natural history of lung cancer that predicts the primary tumor volume at the moment the disease transits from early to advanced stage. Our model also produces estimates for the probability of symptomatic detection as a function of tumor volume and clinical stage. We estimate model parameters by likelihood maximization using data from the Mayo Lung Project (MLP), which was a clinical trial that evaluated screening for lung cancer in the 1970s. Mayo Lung Project cancer cases reported in Stage III or greater, according to the 1979 AJCC staging for lung cancer, were considered advanced stage. Our estimator distinguishes between the cases detected because of clinical symptoms and cases detected by screening. For nonsmall cell lung cancer cases detected in MLP, we estimate that the median primary tumor diameter at the onset of advanced stage disease was 4.1 cm. In addition, we estimate that the rate of patients symptomatically detected with their disease increases as their primary tumor increases in size, and for patients with a primary tumor of a given size, the rate of symptomatic detection is 12.8 times greater among patients with advanced stage disease compared to patients with early stage disease.