Flagship Biosciences, Inc.

Nathan T Martin

Joseph Krueger

Holger Lange

Joshua C Black

Anthony John Milici

George David Young

Famke Aeffner

Steven J Potts

Cris L Luengo Hendriks

Logan Jerome Cerkovnik

Mirza Peljto

Carsten Schnatwinkel

Kristin Wilson

Erik Hagendorn

One type of tissue-based assay, the companion diagnostic ('CDx') allows for the identification of individuals within a larger patient population who are more likely to respond to a therapy. The CDx paradigm typically applies to drugs that target a specific gene product or biologic pathway involving a gene product of interest. It is possible, especially for popular therapeutic targets, for multiple drugs and multiple associated CDx to be developed for a single gene product or biologic pathway involving the gene product. Currently, each of these similar CDx must be applied to identify the best therapy. The present invention can determine the outcome of one CDx using an image of a tissue section used for another CDx. Using a single tissue section and a single CDx, it becomes possible to obtain the outcome of multiple, related CDx.

Method for digitally generating scores for multiple diagnostic tests from tissue assayed with a single test

Staining of tissue is a common approach utilized to visualize a gene product in tissue context. In certain applications, it is necessary to report a sum of events within the tissue as a specific function of the target tissue area, which is a sub-area of the total tissue, as a normalization factor for reporting the quantification. Here, we describe methods of determining target tissue area and reporting a quantification which is ratiometric to the target tissue area, utilizing computer algorithms. It is important to assign a value for the 'target tissue area' in scenarios where a tissue area normalization factor is needed in the most pathologically relevant fashion during the application of tissue image analysis. We have created methods for determining and reporting 'target tissue area' as normalization factor which are useful in diagnostic applications utilizing image analysis.

Method for assigning tissue normalization factors for digital image analysis

The disclosure concerns a method for extracting geographic distribution statistics from patient tissue samples assayed with a tissue-based test for the purpose of scoring the patient tissue samples and guiding treatment based on the score(s). The method described herein utilizes digital image analysis of an image of one or more tissue sections to extract object-based (e.g., cells) features to generate a data array representing said tissue numerically in image analysis feature space. The numerical representation of the image of the tissue section in image analysis feature space is further processed using one or more algorithm processes to extract sophisticated geographical distribution features of one or more object type or sub-type in the tissue. Statistics describing the geographic distribution features are summarized to generate a patient-specific diagnostic score, and this score can be evaluated to guide patient treatment decisions.

Method for scoring pathology images using spatial statistics of cells in tissues

The disclosure concerns a method for patient stratification and selection of patients who are candidates for a specific therapy is described which is based on quantifying one or more digital image analysis feature distributions from stained tissue. The method extends beyond the abilities of a manual observer and a microscope, and generally comprises: acquiring digital images of stained tissue sections from patients submitted for evaluation, applying an algorithm process to said images with a computer to extract the morphometric and staining features of image pixels and tissue objects, deriving one or more distribution function for one or more image analysis features, calculating a summary statistic of the one or more distribution functions, and using said summary statistic along with an associated predefined patient stratification paradigm to separate a patient cohort into distinct strata which correspond to a decision to include or exclude a patient for a specific therapy.

Method for stratifying and selecting candidates for receiving a specific therapeutic approach

The disclosure concerns a method for assessing muscular dystrophy-linked protein expression in muscle fibers using digital image analysis of tissue. The method relates to assessing disease severity in individuals with muscular dystrophy. Muscle tissue samples are obtained from patients submitted for evaluation and processed to produce tissue sections mounted on glass slides which have been stained for a muscular dystrophy-linked protein. Digital images of the stained tissue sections are generated and analyzed by applying an algorithm process implemented by a computer to the images. The algorithm process extracts the morphometric and staining features of the muscular dystrophy-linked protein staining in the tissue, and parameters relating to these features are used to score the disease status for each patient submitted for evaluation. The score of disease status is ultimately used to infer disease severity, monitor the efficacy of a therapeutic approach, or select patients as candidates for a therapeutic approach.

Methods for quantitative assessment of muscle fibers in muscular dystrophy

The invention concerns automated methods for assessing tissue morphometry in digital images of tissue sections derived from small intestine biopsy samples from patients submitted for evaluation of celiac disease. The methods generally involve digital image analysis of tissue section images, and specifically involve post-processing each image to produce a binary mask capturing the tissue area footprint on the glass slide. Virtual stereology probes are placed on each image and assessed to estimate the ratio of the surface area to volume of the tissue specimen. The surface area to volume ratio is used to diagnose celiac disease and make inferences about the severity of celiac disease in those individuals with a positive diagnosis of celiac disease.

Automated methods for assessment of celiac disease

Board support stand

This disclosure concerns methods for evaluating inflammatory cells and modulators of the inflammatory response in tumor tissue and other relevant tissue types. The methods entail: obtaining a tissue sample and processing said tissue sample to produce histologic slides of tissue sections; staining of the tissue sections to identify inflammatory cells and modulators of the inflammatory response; digitizing slides to produce an image of the stained tissue sections; digitally stratifying the tissue sample into tumor and other relevant tissue compartments; and using digital image analysis to quantify cell-based and cell population-based features. The quantification of cell-based and cell population-based features within a tissue compartment of interest is used to develop a summary score of the immune system-tissue compartment of interest interaction. Patient stratification and selection as candidates for a therapeutic approach is ultimately based on the summary score value.

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Boulder, CO, United States of America

Nathan T Martin