Abstract: In silico tools are used to determine possibly effective therapies for treating a patient's cancer based on patient, drug, and cancer information. Functional assays can be performed on living cancer cells from the patient to evaluate the possibly effective therapies along with subsequent genomic or other more destructive assays to provide additional information from a single sample. Drug, patient, cancer, and outcome information can be recorded and updated iteratively and analyzed using machine learning to identify correlations between various patient, cancer, and drug characteristics and expected outcomes and drug efficacies.

Abstract: The invention provides devices and methods for linked multimodal measurements of individual particles using a mass sensor and an additional sensor.

Abstract: The present invention includes methods and systems for assessing a cellular response to a treatment modality, such as potential drug candidate, by comparing normalized single-cell measurements of cellular properties without the need of a calibration step.

Abstract: The invention provides devices and methods for linked multimodal measurements of individual particles using a mass sensor and an additional sensor.

Abstract: Methods of calibration are provided. A method comprises introducing a material with cell-like properties and a known mass into a sensor on a measurement instrument to generate a calibration reading and adjusting an output module of the measurement instrument until the measurement instrument calibrates to the known mass for the material.