A Clinical and Correlative Study of Elotuzumab, Carfilzomib, Lenalidomide, and Dexamethasone (Elo-KRd) for Lenalidomide Refractory Multiple Myeloma in First Relapse.

INTRODUCTION: Treatment of patients with multiple myeloma (MM) in first relapse remains a challenge. This phase II study combined elotuzumab (Elo) with carfilzomib, lenalidomide, and dexamethasone (KRd) for treatment of MM in first relapse with the aim of improving efficacy. METHODS: Enrolled patients received Elo-KRd induction for 4 cycles, and Elo-lenalidomide maintenance until progression. The primary endpoint was VGPR or better (≥VGPR) postinduction. Secondary endpoints were MRD by flow cytometry, OS, PFS, and safety. Correlatives included characterization of the impact of Elo-KRd on NK and T cell subsets via flow cytometry. Target accrual of 40 patients was not met due to COVID-19 pandemic. RESULTS: Of 15 patients enrolled, 10 (67%) had high-risk features (del17p, t[4;14], t[14;16], 1q gain/amplification, plasma cell leukemia, extramedullary MM, or functional high risk), 12 (80%) were lenalidomide-refractory, and 5 (33.3%) bortezomib-refractory. Postinduction ≥VGPR was 7/15 (46.7%) and MRD-negative (10-5) rate 20%. Overall response during study was 80%, including ≥VGPR as best response of 53.3%. At median follow-up of 28.2 (range, 3.8 to 44.2) months, the median PFS was 11.5 months (95% CI 1.9, 18), and median OS not reached (95% CI 10.1, NA). No new safety concerns were reported. Elo-KRd treatment did not augment NK cell distribution or activity in blood or bone marrow. Effector CD4+ and CD8+ T cells significantly decreased postinduction, with concomitant acquisition of T central memory phenotype, particularly at a high rate in ≥VGPR group. CONCLUSION: A short course of Elo-KRd induction followed by Elo-lenalidomide maintenance demonstrated activity in predominantly lenalidomide-refractory and / or high-risk MM. The results with this well-tolerated combination are comparable to other contemporary approved triplet combinations.

Recent advances in drug repurposing using machine learning.

Drug repurposing aims to find new uses for already existing and approved drugs. We now provide a brief overview of recent developments in drug repurposing using machine learning alongside other computational approaches for comparison. We also highlight several applications for cancer using kinase inhibitors, Alzheimer's disease as well as COVID-19.