Scientific Rationale Supporting the Clinical Development Strategy for the Investigational Aurora A Kinase Inhibitor Alisertib in Cancer

Alisertib (MLN8237) is a selective small molecule inhibitor of Aurora A kinase that is being developed in multiple cancer indications as a single agent and in combination with other therapies. A significant amount of research has elucidated a role for Aurora A in orchestrating numerous activities of cells transiting through mitosis and has begun to shed light on potential non-mitotic roles for Aurora A as well. These biological insights laid the foundation for multiple clinical trials evaluating the antitumor activity of alisertib in both solid cancers and heme-lymphatic malignancies. Several key facets of Aurora A biology as well as empirical data collected in experimental systems and early clinical trials have directed the development of alisertib towards certain cancer types, including neuroblastoma, small cell lung cancer, neuroendocrine prostate cancer, atypical teratoid / rhabdoid tumors and breast cancer among others. In addition, these scientific insights provided the rationale for combining alisertib with other therapies, including microtubule perturbing agents such as taxanes, EGFR inhibitors, hormonal therapies, platinums, and HDAC inhibitors among others. Here we link the key aspects of the current clinical development of alisertib to the originating scientific rationale and provide an overview of the alisertib clinical experience to date

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs

Due to the huge success and rapid development of convolutional neural networks (CNNs), there is a growing demand for hardware accelerators that accommodate a variety of CNNs to improve their inference latency and energy efficiency, in order to enable their deployment in real-time applications. Among popular platforms, field-programmable gate arrays (FPGAs) have been widely adopted for CNN acceleration because of their capability to provide superior energy efficiency and low-latency processing, while supporting high reconfigurability, making them favorable for accelerating rapidly evolving CNN algorithms. This article introduces a highly customized streaming hardware architecture that focuses on improving the compute efficiency for streaming applications by providing full-stack acceleration of CNNs on FPGAs. The proposed accelerator maps most computational functions, that is, convolutional and deconvolutional layers into a singular unified module, and implements the residual and concatenative connections between the functions with high efficiency, to support the inference of mainstream CNNs with different topologies. This architecture is further optimized through exploiting different levels of parallelism, layer fusion, and fully leveraging digital signal processing blocks (DSPs). The proposed accelerator has been implemented on Intel's Arria 10 GX1150 hardware and evaluated with a wide range of benchmark models. The results demonstrate a high performance of over 1.3 TOP/s of throughput, up to 97% of compute [multiply-accumulate (MAC)] efficiency, which outperforms the state-of-the-art FPGA accelerators

Discussion on tunnel bottom excavation method and lining deformation monitoring scheme of operating tunnel

In order to analyze the degree of disturbance to the lining by the full-width excavation and reinforcement of the tunnel bottom, and determine the length of the excavation unit, and the excavation interval and improve the monitoring measurement plan. Through field observation and numerical simulation comparative analysis and verification, it is determined that the deformation of the lining equals mainly the deformation of the side wall, the influence range of the settlement of the side wall is greater than that of the convergence, the maximum value of the maximum principal stress of the lining is mainly distributed from the side wall of the excavation area to the arch line, the side wall of the excavation area produces shear yield when the length of the excavation unit reaches 5m, and the influence area will cross influence when the excavation interval is less than twice the influence area. Based on the distribution law of lining deformation, principal stress and elastoplastic area, it is recommended that the length of the excavation unit should be less than 5m, the excavation interval should be greater than twice the influence range of the side wall settlement; and the monitoring section should be arranged at the central section of the excavation area, the interval of the monitoring section should be determined according to the location of the excavation unit, the monitoring scope may not extend to the unreinforced section, and the settlement of the side walls should be increased

Phase I study of MLN8237—investigational Aurora A kinase inhibitor—in relapsed/refractory multiple myeloma, Non-Hodgkin lymphoma and chronic lymphocytic leukemia

Purpose Amplification or over-expression of the mitotic Aurora A kinase (AAK) has been reported in several heme-lymphatic malignancies. MLN8237 (alisertib) is a novel inhibitor of AAK that is being developed for the treatment of advanced malignancies. The objectives of this phase I study were to establish the safety, tolerability, and pharmacokinetic profiles of escalating doses of MLN8237 in patients with relapsed or refractory heme-lymphatic malignancies. Methods Sequential cohorts of patients received MLN8237 orally as either a powder-in-capsule (PIC) or enteric-coated tablet (ECT) formulation. Patients received MLN8237 PIC 25–90 mg for 14 or 21 consecutive days plus 14 or 7 days’ rest, respectively, or MLN8237 ECT, at a starting dose of 40 mg/day once-daily (QD) for 14 days plus 14 days’ rest, all in 28-day cycles. Subsequent cohorts received MLN8237 ECT 30–50 mg twice-daily (BID) for 7 days plus 14 days’ rest in 21-day cycles. Results Fifty-eight patients were enrolled (PIC n = 28, ECT n = 30). The most frequent grade ≥3 drug-related toxicities were neutropenia (45 %), thrombocytopenia (28 %), anemia (19 %), and leukopenia (19 %). The maximum tolerated dose on the ECT 7-day schedule was 50 mg BID. The terminal half-life of MLN8237 was approximately 19 h. Six (13 %) patients achieved partial responses and 13 (28 %) stable disease. Conclusion The recommended phase II dose of MLN8237 ECT is 50 mg BID for 7 days in 21-day cycles, which is currently being evaluated as a single agent in phase II/III trials in patients with peripheral T-cell lymphoma. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10637-013-0050-9) contains supplementary material, which is available to authorized users

Aurora A Functional Single Nucleotide Polymorphism (SNP) Correlates With Clinical Outcome in Patients With Advanced Solid Tumors Treated With Alisertib, an Investigational Aurora A Kinase Inhibitor

BACKGROUND: Alisertib (MLN8237) is an investigational, oral, selective Aurora A kinase inhibitor. Aurora A contains two functional single nucleotide polymorphisms (SNPs; codon 31 [F/I] and codon 57 [V/I]) that lead to functional changes. This study investigated the prognostic and predictive significance of these SNPs. METHODS: This study evaluated associations between Aurora A SNPs and overall survival (OS) in The Cancer Genome Atlas (TCGA) database. The Aurora A SNPs were also evaluated as predictive biomarkers for clinical outcomes to alisertib in two phase 2 studies (NCT01045421 and NCT01091428). Aurora A SNP genotyping was obtained from 85 patients with advanced solid tumors receiving single-agent alisertib and 122 patients with advanced recurrent ovarian cancer treated with alisertib plus weekly paclitaxel (n=62) or paclitaxel alone (n=60). Whole blood was collected prior to treatment and genotypes were analyzed by PCR. FINDINGS: TCGA data suggested prognostic significance for codon 57 SNP; solid tumor patients with VV and VI alleles had significantly reduced OS versus those with II alleles (HR 1.9 [VI] and 1.8 [VV]; p<0.0001). In NCT01045421, patients carrying the VV alleles at codon 57 (n=53, 62%) had significantly longer progression-free survival (PFS) than patients carrying IV or II alleles (n=32, 38%; HR 0.5; p=0.0195). In NCT01091428, patients with the VV alleles at codon 57 who received alisertib plus paclitaxel (n=47, 39%) had a trend towards improved PFS (7.5months) vs paclitaxel alone (n=32, 26%; 3.8months; HR 0.618; p=0.0593). In the paclitaxel alone arm, patients with the VV alleles had reduced PFS vs modified intent-to-treat (mITT) patients (3.8 vs 5.1months), consistent with the TCGA study identifying the VV alleles as a poor prognostic biomarker. No significant associations were identified for codon 31 SNP from the same data set. INTERPRETATION: These findings suggest that Aurora A SNP at codon 57 may predict disease outcome and response to alisertib in patients with solid tumors. Further investigation is warranted