A pharmacodynamic model of clinical synergy in multiple myeloma

Abstract

Background: Multiagent therapies, due to their ability to delay or overcome resistance, are a hallmark of treatment in multiple myeloma (MM). The growing number of therapeutic options in MM requires highthroughput combination screening tools to better allocate treatment, and facilitate personalized therapy. Methods: A second-order drug response model was employed to fit patient-specific ex vivo responses of 203 MM patients to single-agent models. A novel pharmacodynamic model, developed to account for twoway combination effects, was tested with 130 two-drug combinations. We have demonstrated that this model is sufficiently parameterized by single-agent and fixed-ratio combination responses, by validating model estimates with ex vivo combination responses for different concentration ratios, using a checkerboard assay. This new model reconciles ex vivo observations from both Loewe and BLISS synergy models, by accounting for the dimension of time, as opposed to focusing on arbitrary time-points or drug effect. Clinical outcomes of patients were simulated by coupling patient-specific drug combination models with pharmacokinetic data. Findings: Combination screening showed 1 in 5 combinations (21.43% by LD50, 18.42% by AUC) were synergistic ex vivo with statistical significance (P < 0.05), but clinical synergy was predicted for only 1 in 10 combinations (8.69%), which was attributed to the role of pharmacokinetics and dosing schedules. Interpretation: The proposed framework can inform clinical decisions from ex vivo observations, thus providing a path toward personalized therapy using combination regimens.

IAP and HDAC inhibitors interact synergistically in myeloma cells through noncanonical NF-κB– and caspase-8–dependent mechanisms

“…captured cell movement and membrane motion to identify live cells. Synergy was determined using the method described by Sudalagunta, et al 18 , where percent live cells across time and five serially diluted (1:3) concentrations when treated with LCL161 and LBH589 are used to compute additive response using the Bliss Independence Model. The additive response serves as a reference to determine the extent of synergy observed in each patient sample by comparing it with the percent live cells measured when treated with the combination (at a fixed ratio of the two constituent single agents).…”

The Landscape of Signaling Pathways and Proteasome Inhibitors Combinations in Multiple Myeloma

“…Multiagent therapy is the cornerstone of treatment in multiple myeloma. Recent advances in clinical outcomes for MM patients are derived from the combination of novel agents, such as dexamethasone and immunomodulatory drugs, (lenalidomide), chemotherapy (doxorubicin, mephalan, or cyclophosphamide), antibodies (elotuzumab or daratumumab), or histone deacetylase (HDAC) inhibitors [ 18 , 36 ]. The common rationale is to address the clonal heterogeneity of the MM, thus combining different agents to eradicate both dominant and minor tumor clones.…”

Role of synergy and antagonism in designing multidrug adaptive chemotherapy schedules

“…In this context, it is common to assume that synergistic interactions are desirable in most circumstances, as a lower total dosage accomplishes the same kill rate as a higher dose would accomplish if the drugs acted independently. These kinds of studies have been used effectively to choose appropriate drug cocktails to individual patients by testing wide ranges of combinations on tissue samples obtained from patient tumors [22].…”