AstraZeneca's Calquence treads on Imbruvica's turf with second phase 3 CLL win

fiercepharma | June 06, 2019

AstraZeneca’s Calquence has been battling it out in mantle cell lymphoma since it won its first approval back in late 2017, but all along, the company has had its eye on another disease: chronic lymphocytic leukemia. And that’s where it’s scored its latest win. In a phase 3 trial, Calquence—combined with Roche’s Gazyva—beat out a regimen of chlorambucil chemotherapy and Gazyva at staving off disease progression in previously untreated CLL patients, AstraZeneca said Thursday. And the trial nailed a key secondary endpoint, too, showing solo Calquence could top the Gazyva-chemo combination at the same feat. The British drugmaker is keeping the details under wraps for now; they’ll debut at a future medical meeting. But in the meantime, later this month, the company plans to unveil full results from another Calquence CLL win that it top-lined in early May.

Spotlight

To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The aging issue is an aspect that researchers, companies, and the government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization, and combinatorial optimization are covered.

Spotlight

To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The aging issue is an aspect that researchers, companies, and the government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization, and combinatorial optimization are covered.

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