RESUMO
Background: The outcome of non-transplant eligible newly diagnosed multiple myeloma (NDMM) patients is heterogeneous, partly depending on frailty level. The aim of this study was to prospectively investigate the efficacy and safety of Ixazomib-Daratumumab-low-dose dexamethasone (Ixa-Dara-dex) in NDMM intermediate-fit patients. Methods: In this phase II multicenter HOVON-143 study, IMWG Frailty index based intermediate-fit patients, were treated with 9 induction cycles of Ixa-Dara-dex, followed by maintenance with ID for a maximum of 2 years. The primary endpoint was overall response rate on induction treatment. Patients were included from October 2017 until May 2019. Trial Registration Number: NTR6297. Findings: Sixty-five patients were included. Induction therapy resulted in an overall response rate of 71%. Early mortality was 1.5%. At a median follow-up of 41.0 months, median progression-free survival (PFS) was 18.2 months and 3-year overall survival 83%. Discontinuation of therapy occurred in 77% of patients, 49% due to progression, 9% due to toxicity, 8% due to incompliance, 3% due to sudden death and 8% due to other reasons. Dose modifications of ixazomib were required frequently (37% and 53% of patients during induction and maintenance, respectively), mainly due to, often low grade, polyneuropathy. During maintenance 23% of patients received daratumumab alone. Global quality of life (QoL) improved significantly and was clinically relevant, which persisted during maintenance treatment. Interpretation: Ixazomib-Daratumumab-low-dose dexamethasone as first line treatment in intermediate-fit NDMM patients is safe and improves global QoL. However, efficacy was limited, partly explained by ixazomib-induced toxicity, hampering long term tolerability of this 3-drug regimen. This highlights the need for more efficacious and tolerable regimens improving the outcome in vulnerable intermediate-fit patients. Funding: Janssen Pharmaceuticals, Takeda Pharmaceutical Company Limited.
RESUMO
Prediction of human Cytochrome P450 (CYP) binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD) simulations and Linear Interaction Energy (LIE) theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE) of 4.1 kJ mol-1 and a standard error in prediction (SDEP) in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units).
