Essen Instruments, Inc.

Intellicyt Corporation

Indevr, Inc.

Andrew Smolak

Kathy Lou Rowlen

Erica Dawson Tenent

Jean-Luc Fraikin

Christopher Converse

Garrett S Wilson

Gregory Yamada

Evan M Toth

Goran Rauker

Garrett Wilson

Jeffrey T Ives

The systems and methods contained herein are directed toward automated analysis of agglutination reactions to determine properties of materials, including viruses and vaccines thereto. Advanced digital imaging and processing techniques are used to determine the presence or absence of viruses or antibodies within a fluid sample. The systems and methods are versatile, and can be used to determine specific properties of biomaterials and viruses, such as titer value, concentration, genotype, phenotype, serotype, vaccine efficacy, viral resistance and other properties of relevance in the medical, research and development fields. Also provided are systems and methods of standardization, repeatability, and data storage and transmittal to reduce errors and subjectivity inherent to conventional assays characterized by human readers.

Automated agglutination analyzer with contour comparison

A method and a flow cytometer system in which a light path is aligned to optimally direct light from a light source to a flow cell of a flow cytometer instrument are provided. The flow cytometer may include an orientable mirror disposed in the light path between the light source and the flow cell. By changing an orientation of the mirror through a sequence of different orientations, an optimal orientation of the mirror may be determined, and the mirror may be oriented accordingly before proceeding to conduct a flow cytometry investigation.

Automated alignment of optics within a flow cytometer

Methods of evaluating particle attributes in a sample fluid subjected to flow cytometry investigation in a flow cytometer instrument, methods of processing time series signal data traces output by a flow cytometer instrument, and a flow cytometer system are provided. In the methods and systems, data points comprising time series signal data traces corresponding with detection during the flow cytometry investigation of light from the sample fluid in one or more wavelength ranges indicative of the presence of one or more particle attributes in the sample fluid are batch-processed using a batch-specific signal peak threshold determined as a function of a batch-specific noise characteristic to identify signal peaks in the batch of data points indicative of the presence of the one or more particle attributes in the sample fluid.

Flow cytometer signal peak identification employing dynamic thresholding

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Golden, CO, United States of America

Andrew Smolak