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Cell therapies have emerged as a promising therapeutic modality with the potential to treat and even cure a diverse array of diseases. Cell therapies offer unique clinical and therapeutic advantages over conventional small molecules and the growing number of biologics. Particularly, living cells can simultaneously and dynamically perform complex biological functions in ways that conventional drugs cannot; cell therapies have expanded the spectrum of available therapeutic options to include key cellular functions and processes. As such, cell therapies are currently one of the most investigated therapeutic modalities in both preclinical and clinical settings, with many products having been approved and many more under active clinical investigation. Here, we highlight the diversity and key advantages of cell therapies and discuss their current clinical advances. In particular, we review 28 globally approved cell therapy products and their clinical use. We also analyze >1700 current active clinical trials of cell therapies, with an emphasis on discussing their therapeutic applications. Finally, we critically discuss the major biological, manufacturing, and regulatory challenges associated with the clinical translation of cell therapies.

 

Abstract Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.