Roche Molecular Systems, Inc.

Scipher Medicine Corporation

Other

The Scripps Research Institute

Nancy J Schoenbrunner

Thomas W Myers

Joseph San Filippo

Keith Bauer

Fred Lawrence Reichert

Viatcheslav R Akmaev

Keith J Johnson

Asher Ameli

Theodore R Mellors

Marc Santolini

Stephen Gordon Will

Veeraiah Bodepudi

Alison Tsan

Dirk Zimmermann

Nicolas Newton

Susan Dina Ghiassian

Heike Wilts

David H Gelfand

Amar Gupta

Edward Soh Smith

Hermann Leying

Eberhard Russmann

Xiaoning Wu

Yu Chuan Tai

Karen K Y Young

Fangnian Wang

Dieter Heindl

Shawn Lee Suko

Henry A Erlich

Ellen H Fiss

Daniel R Salomon

Susanne Stoffel

Stefanie Froehner

Meike Eickhoff

Cherie Holcomb

Dirk Kessler

Christopher D Newhouse

Xiaoying Chen

Nick Newton

Niclas Hitziger

John Niemiec

Bryan Hoglund

Concordio Anacleto

Susan Ghiassian

Thomas Drechsler

Karen Wang

Kevin Janssen

Priscilla Moonsamy

Melinda Rastrou

Jinshuang Lu

Suzanne Cheng

Beiyang Ma

Nancy Patten

Sim C Truong

Anke Mussmann

Olga Budker

Fangbing Liu

Stephan Hug

Martin Eduardo Silvestre

Kwame Sefah

Yu Tian

Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising administering an alternative to anti-TNF therapy to subjects who have been determined to be non-responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Methods of treating a subject suffering from rheumatoid arthritis with anti-TNF therapy based in part on a trained machine learning classifier

Techniques are provided for determining settings of a dPCR experiment for the detection of a chromosomal aneuploidy in a plasma sample from a female pregnant with a fetus. Data about the sample, the dPCR process, and a desired accuracy can be used to determine the settings. Such settings can include a minimal input number of control chromosome molecules for the dPCR experiment, a minimal number of control chromosome molecules for a pre-amplification procedure, and a number of PCR cycles in the pre-amplification procedure. These settings can be used to satisfy the accuracy specified by the accuracy data. Thus, the dPCR experiment can be designed to achieve the desired accuracy while reducing cost, e.g., by not using more of a sample than needed and not performing more pre-amplification than needed or performing more manipulations than needed.

Digital PCR for non-invasive prenatal testing

Methods of treating a subject suffering from rheumatoid arthritis with alternative to anti-TNF therapy based in part on a trained machine learning classifier

The disclosure provides improved magnetic glass particles for use in nucleic acid capture, enrichment, analysis, and/or purification. Various modifications to the disclosed compositions and methods of using the same, as well as devices and kits are described.

Magnetic particles and uses thereof

A sample processing tubule is provided including, from a proximate to a distal end, an opening through which a sample is introducible, at least three segments, and an reagent introduction port operatively connected to a distal segment of the at least three segments. The reagent introduction port enables the addition of a reagent in the distal segment of the tubule, enabling the user to create a customizable assay tubule.

Customizable sample processing device

Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising a step of: administering an anti-TNF therapy to subjects who have been determined to be responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Methods of treating a subject suffering from rheumatoid arthritis based in part on a trained machine learning classifier

Method of treating a subject suffering from rheumatoid arthritis with anti-TNF therapy based on a trained machine learning classifier

The disclosure provides methods, devices, and kits for conducting a quantitative analysis of a whole blood sample. Various modifications to the disclosed methods, devices, and kits are described.

Cell surface marker depletion in a sample processing device

Disclosed are mutant DNA polymerases having increased 3'-mismatch discrimination relative to a corresponding, unmodified polymerase. The mutant polymerases are useful in a variety of disclosed primer extension methods. Also disclosed are related compositions, including recombinant nucleic acids, vectors, and host cells, which are useful, e.g., for production of the mutant DNA polymerases.

DNA polymerases with increased 3'-mismatch discrimination

A method of simultaneously amplifying genotypes 1, 2, 3 and/or 4 of HEV is disclosed comprising amplifying the genotypes 1, 2, 3 and/or 4 of HEV with one single none-degenerate forward primer partially overlapping the 5'UTR region of HEV and at least one reverse primer. Also disclosed are related methods comprising a probe, and kits for the detection of genotypes 1, 2, 3 and/or 4 of HEV.

HEV Assay

The disclosure provides control compositions used in nucleic acid amplification. Various modifications to the disclosed compositions and methods of using the same, devices, and kits are described.

Devices comprising bacteriophage PHI6 internal control compositions

The detection of the presence of rare somatic mutations from a biological sample is often challenging due to the simultaneous presence of a vast excess of wild-type DNA. The present invention describes methods that would allow the enrichment of mutant DNA by depleting amplifiable wild-type DNA.

Methods for the enrichment of mutated nucleic acid from a mixture

The invention is a method of detecting or assessing solid organ graft (transplant) rejection by detecting donor-specific HLA alleles in a blood sample of a graft (transplant) recipient. The invention further comprises a method of detecting the presence of maternal cells in a blood sample of an offspring.

Non-invasive early detection of solid organ transplant rejection by quantitative analysis of mixtures by deep sequencing of HLA gene amplicons using next generation systems

Growing community of inventors

Moraga, CA, United States of America

Nancy J Schoenbrunner