Jaya Algorithm for Optimization of Cooling Slope Casting Process Parameters

This study proposed the Jaya algorithm to estimate an improved value of billet performance through the cooling casting process. Jaya algorithm is a recent evolution-based algorithm that simulates using stochastic behaviour. The algorithm concept is the solution obtained for a given problem should move towards the best solution and should avoid the worst solution. This algorithm requires only the common control parameters and does not require any algorithm specific control parameters. To the best our knowledge, Jaya algorithm is not yet been used computational approach for optimization practice, particularly in the Cooling casting process. Three Cooling slope parameters process that influences the billet performance measurements, a maximum degree of sphericity and minimum grain size are pouring temperature, slanting angle, and travelling distance. The results show that the Jaya algorithm gave a better optimal solution for the maximum degree of sphericity and minimum particle size than experimental data.

Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial

HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms ‘graduate’ in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome.

CTNI-40. EVALUATING FEASIBILITY AND EFFICIENCY OF PHASE II ADAPTIVE PLATFORM TRIAL DESIGNS BASED ON THE INDIVIDUALIZED SCREENING TRIAL OF INNOVATIVE GLIOBLASTOMA THERAPY (INSIGhT) EXPERIENCE

BACKGROUND The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial with Bayesian adaptive randomization and deep genomic profiling to more efficiently test experimental agents in newly diagnosed glioblastoma and to prioritize therapies for late-stage testing. METHODS In the ongoing INSIGhT trial, patients with newly diagnosed MGMT-unmethylated glioblastoma are randomized to the control arm or one of three experimental therapy arms (CC-115, abemaciclib, and neratinib). The control arm therapy is radiotherapy with concomitant and adjuvant temozolomide, and primary endpoint is overall survival. Randomization has been adapted based on Bayesian estimation of biomarker-specific probability of treatment impact on progression-free survival (PFS). All tumors undergo detailed molecular sequencing, and this is facilitated with the companion ALLELE protocol. To evaluate feasibility of this approach, we assessed the status of this ongoing trial. RESULTS Since INSIGhT was activated 4.3 years ago, it has expanded to include 12 sites across the United States. A total of 247 patients have been enrolled. Randomization probabilities have been repeatedly adjusted over time based upon early PFS results to alter the randomization ratio from standard 1:1:1:1 randomization. All three arms have completed accrual and efficacy estimates are available based upon comparison to the common control arm in context of relevant biomarkers. There are 87 patients alive and in follow-up, and there are ongoing plans to add additional arms to evaluate further treatments in the future. CONCLUSION The INSIGhT trial demonstrates that a multi-center Bayesian adaptive platform trial is a feasible and effective approach to help prioritize therapies and biomarkers for newly diagnosed GBM. The trial has maintained robust accrual, and the simultaneous testing of multiple agents, sharing a common control arm and adaptive randomization serve as features to increase trial efficiency relative to traditional clinical trial designs.

Business Combinations under Common Control: The Gain/loss Group Perspective. What the IASB Project Leaves Unaddressed

Although BCUCCs are widespread, a clear treatment is missing under IFRS. Most contributions have taken partial views. This article innovatively provides a systematic theoretical apparatus of the role accounting plays for all the affected members of a group, with a focus on gain or loss opportunities below the consolidated statements. The method used is international technical accounting analysis under IFRS and U.S. GAAP. It shows how a BCUCC may be driven to achieve gain/loss in separate financial statements and how cross-company consistency in policies and substance may reveal gain/loss arbitrage; the interaction of principles for disposals, demergers, and business combinations; and the position of sub-holdings, which in real practice is more relevant than the ultimate parent company. This paper is timely, as the IASB has recently published a Discussion Paper. The IASB project fails to give answers to these points as it only looks at the receiving entity and consolidated statements.