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Two major advances in optical pooled screening improve substantially on sensitivity and robustness, expanding its applicability to a broader range of biological contexts.
Sample, financial and labor requirements are key barriers to scaling up high-content phenotypic discovery efforts. A broadly applicable method overcomes these challenges through experimental compression (by pooling various perturbations) and computational deconvolution (of their individual effects), empowering the use of phenotypic screening to advance therapeutic discovery.
A CRISPR-based assay both recognizes and amplifies target mRNA, achieving sub-attomolar sensitivity with single-nucleotide resolution. This method enables the detection of low-abundance mRNA in extracellular vesicles, providing clinically relevant information for precision oncology.
The time has come for biotech companies to embrace machine learning for clinical trials, but they should start with compiling the data. That means grappling with real-world patient records.
Escherichia coli engineered to display cytokines destroy hard-to-treat tumors by boosting the activity of local native and adoptive immune effector cells.
The FDA’s approval of the first genetically modified T cell therapy for treating a rare sarcoma is paving the way for next-generation therapies that tackle other types of solid tumors.