Nestec S.a.

Prometheus Laboratories Inc.

Augusto Lois

Bruce P Neri

The present invention provides methods for accurately classifying whether a sample from an individual is associated with an intestinal disorder. In particular, the present invention is useful for associating a sample from an individual as an IBS sample or as a non-IBS sample. The present invention is also useful for ruling out one or more diseases or disorders that present with IBS-like symptoms and ruling in IBS using statistical algorithms and/or empirical data. Thus, the present invention provides an accurate diagnostic prediction of an intestinal disorder and prognostic information useful for guiding treatment decisions.

Methods for diagnosing irritable bowel syndrome

The present invention provides methods, systems, and code for accurately classifying whether a sample from an individual is associated with irritable bowel syndrome (IBS). In particular, the present invention is useful for classifying a sample from an individual as an IBS sample using a statistical algorithm and/or empirical data. The present invention is also useful for ruling out one or more diseases or disorders that present with IBS-like symptoms and ruling in IBS using a combination of statistical algorithms and/or empirical data. Thus, the present invention provides an accurate diagnostic prediction of IBS and prognostic information useful for guiding treatment decisions.

The present invention provides methods, systems, and code for accurately classifying whether a sample from an individual is associated with inflammatory bowel disease (IBD) or a clinical subtype thereof. In particular, the present invention is useful for classifying a sample from an individual as an IBD sample using a statistical algorithm and/or empirical data. The present invention is also useful for differentiating between a clinical subtype of IBD such as Crohn's disease (CD) and ulcerative colitis (UC) using a statistical algorithm and/or empirical data. Thus, the present invention provides an accurate diagnostic prediction of IBD or a clinical subtype thereof and prognostic information useful for guiding treatment decisions.

Methods of diagnosing inflammatory bowel disease

The present invention provides methods, systems, and code for accurately classifying or diagnosing a sample from an individual as an IBS sample. The methods and systems of the present invention are useful for ruling out one or more diseases or disorders that share a similar clinical presentation as IBS followed by identifying (i.e., ruling in) IBS using statistical algorithm(s) and/or empirical data. In particular, the methods and systems of the present invention use a first combination of learning statistical classifier systems to rule out IBD with an accuracy of greater than about 90% and a second combination of learning statistical classifier systems to rule in IBS in a non-IBD sample with an accuracy of greater than about 80%.

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San Diego, CA, United States of America

Augusto Lois