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Efficacy and safety of durcabtagene autoleucel in a phase 1 trial for patients with relapsed/refractory multiple myeloma

Prolonged manufacturing times for autologous CAR T cell therapies can be incompatible with rapidly progressive disease (PD), resulting in increased need for bridging therapy to achieve disease stabilization. Bridging therapy was required for most patients receiving cilta-cel and ide-cel in clinical trials (75 and 87%, respectively) (7, 9, 11, 12). Although use of bridging therapy may not affect ORR, CRR, or PFS, it is associated with worse overall survival (15). Similarly, as wait times for CAR T cell product increase, so does risk of mortality as effectiveness of the therapy decreases (16, 17), highlighting the need for improved CAR T cell products with faster and more reliable manufacturing.

Another issue associated with traditionally manufactured CAR T cell products is T cell exhaustion due to extended periods of in vitro stimulation and expansion during manufacturing (18). Higher levels of exhausted T cells were also observed in the leukapheresis material and final products from patients who later experienced PD (18). T cell exhaustion can result in poor persistence of CAR T cells in the body, thereby impeding function as the proliferation and survival of transferred T cells strongly correlate with their antitumor activity (19–22). Specific T cell populations have varying abilities to expand and persist in vivo. Memory (CD8+CD45RO−CD27+) and naive T cell (TN cell) subsets are associated with improved clinical response, given their ability to proliferate and persist after infusion, whereas effector T cell subsets comparatively exhibit lower self-renewal and survival capabilities (19, 23, 24). Although these patient-specific parameters are initially established in leukapheresis material, preservation of such cell populations in the final product via manufacturing techniques may improve the antitumor activity of a patient’s CAR T cell therapy (18, 19, 23, 24).

Durcabtagene autoleucel (PHE885) is an autologous, BCMA-targeting CAR T cell therapy carrying a CAR construct with a fully human anti-BCMA single-chain fragment variable (scFv) fused to 4-1BB/CD3ζ signaling domains manufactured on a next-generation platform. Prior work has shown that this platform can successfully manufacture product in fewer than 2 days by eliminating the need for ex vivo expansion, thereby preserving overall T cell stemness (the ability of T cells to self-renew and mature), which results in a final product with greater proliferative potential and fewer exhausted T cells (18). Here, we present the findings of part A of the phase 1 study (NCT04318327) of durcabtagene autoleucel in r/r MM, along with correlative analyses of the product before and after infusion.

Evidence of scaling advantage for the quantum approximate optimization algorithm on a classically intractable problem

We study the scaling of QAOA TTS with the problem size on the low autocorrelation binary sequences (LABS) problem (15, 16), also known as the Bernasconi model in statistical physics (17, 18). The LABS problem has applications in communications engineering, where the low autocorrelation sequences are used for designing radar pulses (15, 19). To solve LABS, one has to produce a sequence of N bits that minimizes a specific quartic objective.

We choose LABS to study the scaling of QAOA TTS for the following three reasons. First, the complexity of LABS grows rapidly, with optimal solutions known only for N ≤ 66 and the best heuristics producing approximate solutions of quality decaying with N for N 200 (20, 21). This makes it a promising candidate problem, since only a few hundred qubits are required to tackle classically intractable instances. Second, the performance of classical solvers for LABS has been benchmarked (20, 21) in terms of the scaling of their TTS with problem size. Since optimal solutions are only known for N ≤ 66, the scaling of TTS for all classical solvers is obtained by fitting results for N ≤ 66. We reproduce these results and observe that that the scaling of classical solvers at N ≤ 40 matches the behavior for N up to 66 reported in the literature. This provides evidence that the scaling we observe for QAOA at N ≤ 40 will similarly extrapolate to larger N. Third, LABS has only one instance per problem size N. Combined with the hardness of LABS, this makes it possible to reliably study the scaling of QAOA at large problem sizes, where simulating tens or hundreds of random instances would be computationally infeasible.

We obtain the scaling by performing noiseless exact simulation of QAOA with fixed schedules. Our results are enabled by a custom algorithm-specific graphics processing unit (GPU) simulator (22), which we execute using up to 1,024 GPUs per simulation on the Polaris supercomputer accessed through the Argonne Leadership Computing Facility. We find that the TTS of QAOA with number of layers p = 12 grows as 1.46N, which is improved to 1.21N if combined with quantum minimum finding. This scaling is better than that of the best classical heuristic, which has a TTS that grows as 1.34N. We note that we do not propose any new quantum algorithms in this work. Instead, we study a general quantum optimization heuristic with broad applicability (namely, QAOA) and make no specific modifications to adapt it to the LABS problem.

Leaving gravity behind: Experiment from ISS reveals how particles alter turbulent flow behavior

After traveling hundreds of miles above Earth and spending months aboard the International Space Station, a University of Delaware experiment has returned to campus, bringing new data on how turbulence behaves in microgravity.

The project, led by assistant professor of mechanical engineering Tyler Van Buren, is designed to study how particles influence turbulent flows. From dust in the air to sand in coastal zones and bubbles at the sea surface, particles can change how flows behave.

Van Buren compares it to an energetic crowd moving around while carrying objects.

Ripples in fire-ant collectives suggest motions are driven by neighbor alignments

Researchers in Spain have discovered that in collectives of moving fire ants, rippling “waves” of density and activity are likely triggered by local regions where ants collectively travel in the same direction as their neighbors.

Described in a new paper published in Journal of Applied Physics, Alberto Fernandez-Nieves and colleagues at the University of Barcelona are hopeful that their predictions could be confirmed in future experiments—potentially leading to deeper insights into the complex motions of active materials.

Spin wave signals used in computing boosted more than 5,000 times in Z-shaped path approach

A research team from Tohoku University, Shin-Etsu Chemical Co., Ltd., and École Polytechnique Fédérale de Lausanne (EPFL) has invented a new way to efficiently guide spin waves around sharp corners with minimal loss—representing an exciting discovery for energy-efficient computing. Using a two-dimensional magnonic crystal—a copper (Cu) film with a hexagonal array of tiny holes placed on a magnetic garnet film—the team showed through calculations that spin waves travel along a Z-shaped path more than 5,000 times more efficiently than in conventional waveguides.

As artificial intelligence and data centers consume ever more electricity, heat from conventional electronics has become a serious problem. Spin waves are ripples of magnetization in a magnetic material that can carry information with far less heat than moving electrons, making them promising for reduced-energy computing. However, spin waves weaken quickly as they travel, especially when a waveguide is bent. This signal loss has long been the biggest obstacle to building practical spin wave circuits.

Quantum vibronics research points to future energy and computing technologies

Scientists at the University of California, Riverside are making breakthroughs in understanding how quantum wave functions move across ultra-thin materials—research that could eventually improve solar energy technologies and help lay the groundwork for new forms of quantum computing.

The researchers are part of UCR’s Center for Quantum Vibronics in Energy and Time (QuVET), which was established two years ago and focuses on “vibronics,” the interaction between vibrations and electronic quantum states. The center examines both biological molecules and synthetic layered materials, where the same fundamental quantum processes emerge across vastly different systems.

Its research brings together physicists, chemists, engineers, and biochemists from multiple institutions to better understand how vibrations shape quantum behavior.

Cobalt honeycombs open a new path to quantum computing

Honeycombs are famous for their elegant design, but now they may have found a new application: quantum computing. To collect knowledge from subatomic particles, quantum computers require carefully designed materials capable of performing necessary, complex functions. However, the metals used, such as ruthenium and iridium, are often rare and expensive, limiting the potential to build new technology.

In an article recently published in Physical Review Materials, researchers from SANKEN at The University of Osaka and collaborating institutions reported the creation of a special thin-film material in which cobalt atoms formed local honeycomb arrangements embedded inside a larger honeycomb matrix. These cobalt honeycomb motifs exhibit strong magnetic interactions, which are important for quantum computing applications.

Kitaev materials, a class of quantum magnetic materials studied for their potential use in quantum information science, have attracted major attention because they may host exotic quantum states known as spin liquids.

Taking dark energy out of the equation: Mathematicians challenge the standard cosmological model of the universe

Mathematicians are challenging the idea that dark energy is responsible for the accelerating expansion of the universe. In a new paper published in Proceedings of the Royal Society A, mathematicians from the University of California, Davis, provide mathematical proof that instabilities inherent in the Einstein-Euler equations imply that the current model of the expanding universe is not viable.

The Einstein-Euler equations are a union of general relativity and fluid dynamics equations used to model astronomical phenomena such as galaxies, black holes, and cosmic expansion.

The research directly challenges the Lambda-cold dark matter model, the standard cosmological model of the Big Bang.

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