News Column

"Inter-Class Molecular Association Connectivity Mapping" in Patent Application Approval Process

March 3, 2014



By a News Reporter-Staff News Editor at Clinical Trials Week -- A patent application by the inventor Chen, Jake Yue (Indianapolis, IN), filed on October 21, 2013, was made available online on February 20, 2014, according to news reporting originating from Washington, D.C., by NewsRx correspondents (see also Medeolinx, LLC).

This patent application is assigned to Medeolinx, LLC.

The following quote was obtained by the news editors from the background information supplied by the inventors: "Molecular connectivity maps have been gaining popularity in systems biology. Massive amounts of genomics, functional genomics, metabolomics and proteomics information, including genome-wide genetic variations, epigenetic modifications, mRNA expression profiles, protein expression profiles, protein post-translational modifications, and metabolic profile changes in cells, have been generated.

"While there may be steady progress in managing and interpreting data for each type of measurement individually, it remains uncertain how to develop unified models to integrate signals from genomic-scale measurements of different molecular entities under similar biological conditions. In modern therapeutic agent discovery, for example, the expression level of bio-molecular entities such as genes or proteins that change in response to different therapeutic agent perturbations, or 'bio-molecular entity-therapeutic agent association profiles,' may provide valuable insight on a therapeutic agent's potential molecular therapeutic and toxicological profiles prior to clinical trials. The concept of 'inter-class' molecular associations may be quite different from that of 'intra-class' molecular associations such as gene-gene interactions, protein-protein interactions, or therapeutic agent-therapeutic agent interactions.

"Generalizing from bio-molecular entity-therapeutic agent molecular connectivity profiles built from bio-molecular entities and/or therapeutic entities, the comprehensive inter-class molecular associations in a given biological context may be denoted as a molecular association connectivity map. Molecular association connectivity maps may be developed between therapeutic agents and a wide range of bio-molecular entities such as genes, microRNAs, proteins, and metabolites for a variety of disease areas. Maps between therapeutic agents and such bio-molecular entities may enable researchers to simultaneously compare the molecular therapeutic/toxicological profiles of many candidate therapeutic agents. As explained in detail below, current methods of generating molecular association connectivity maps can be expensive and time-consuming.

"It may be beneficial to provide high-quality molecular association connectivity maps to assist researchers in comparing molecular therapeutic/toxicological profiles of many candidate therapeutic agents or a therapeutic agent's target bio-molecular entity/entities. This may improve the chances of developing high-quality therapeutic agents and reducing development time. Additionally, to achieve improved data coverage and quality, a series of statistical and computational methods may be developed to overcome high levels of data noise that may exist in biological networks and literature abstracts."

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventor's summary information for this patent application: "Methods, systems, devices and/or apparatuses are provided for computationally deriving molecular association connectivity maps for the study of inter-class molecular associations in toxicogenomics and drug discovery applications. The inter-class molecular associations can be between at least one bio-molecular entity and at least one therapeutic agent. The methods, systems, devices and/or apparatuses apply integrated molecular interaction network mining and text mining techniques.

"In one aspect, a method of deriving an inter-class molecular association connectivity map can be summarized as including the steps of network mining, text mining, and connectivity mapping.

"In some embodiments, the step of network mining includes generating a list of at least one bio-molecular entity. Alternatively, the step of network mining includes receiving a list of at least one bio-molecular entity from at least one human bio-molecular entity interaction database. Regardless of how one obtains it, the list of at least one bio-molecular entity can include data relating to a plurality of bio-molecular entities. Moreover, the list of at least one bio-molecular entity from the at least one human bio-molecular entity interaction database can be from a curated source or from a source associated with a specific disease. In any embodiment, the at least one bio-molecular entity can be a nucleic acid molecule, amino acid molecule, lipid molecule, saccharide molecule, metabolite or combination thereof. Likewise, in any embodiment, the at least one bio-molecular entity can be a disease-related bio-molecular entity.

"In some embodiments, the step of text mining includes generating a list of at least one therapeutic agent. Alternatively, the step of text mining includes receiving a list of at least one therapeutic agent from at least one medical research literature database. In any embodiment, the at least one therapeutic agent can be a small molecule, nucleic acid-based molecule, or amino acid-based molecule. Likewise, in any embodiment, the at least one therapeutic agent can be a disease-related therapeutic agent.

"In some embodiments, the step of connectivity mapping includes relating the results of the network mining and text mining. The results of the network mining and text mining can be related by generating a connectivity score for each possible bio-molecular entity-therapeutic agent combination. The connectivity scores, at least in part, can be used for deriving an inter-class molecular association connectivity map as a two-dimensional ('2-D') matrix having a plurality of colored and/or shaded cells associated with the connectivity scores. The connectivity scores can be indicative of the extent of medical literature involving the at least one bio-molecular entity and the at least one therapeutic agent.

"In some embodiments, the method further includes the step of filtering the inter-class molecular association connectivity map to output only disease-related bio-molecular entity-therapeutic agent combinations associated with at least one specific disease.

"In some embodiments, the inter-class molecular association can be a nucleic acid molecule-therapeutic agent association, amino acid molecule-therapeutic agent association, or nucleic acid/amino acid-therapeutic agent association.

"In another aspect, a system for deriving an inter-class molecular association connectivity map can be summarized as including a network construction component, text retrieval and information extraction component, and molecular connectivity mapping component.

"In some embodiments, the network construction component can be at least one bio-molecular entity database, where each bio-molecular entity database is configured to store bio-molecular entity data related to one of a plurality of bio-molecular entities. As above, the bio-molecular entity can be a disease-related bio-molecular entity.

"In some embodiments, the text retrieval and information extraction component can be at least one therapeutic agent database, where each therapeutic agent database is configured to store therapeutic data related to one of a plurality of therapeutic agents. As above, the therapeutic agent can be a disease-related therapeutic agent.

"In some embodiments, the connectivity mapping component can be configured to analyze bio-molecular entity data and therapeutic agent data and output a bio-molecular entity-therapeutic agent molecular association connectivity map representing associations and/or non-associations between the plurality of bio-molecular entities and the plurality of therapeutic agents. Moreover, the molecular association connectivity mapping component can be configured to output, cluster, and/or filter the bio-molecular entity-therapeutic agent molecular association connectivity map with respect to at least one specific disease.

"In some embodiments, the inter-class molecular association connectivity map includes a two-dimensional table relating associations and/or non-associations between the plurality of bio-molecular entities and the plurality of therapeutic agents. A connectivity score can represent the associations and/or non-associations between the plurality of bio-molecular entities and the plurality of therapeutic agents, where the two-dimensional table can include a plurality of colored and/or shaded cells associated with the connectivity score. Moreover, the connectivity score can include a statistical confidence score that indicates an extent of literature studies involving one of the plurality of bio-molecular entities and one of the plurality of therapeutic agents.

"In some embodiments, the bio-molecular entity data and/or therapeutic agent data can be obtained by data mining medical research documents.

"In yet another aspect, a device and/or apparatus for deriving an inter-class molecular association connectivity map can be summarized as a web server configured to perform the methods described herein. Alternatively, the device and/or apparatus for deriving the inter-class molecular association connectivity map can be summarized as computer-readable medium having instructions to perform the methods described herein. Alternatively still, the device and/or apparatus for deriving the inter-class molecular association connectivity map can be summarized as a memory device having software configured to perform the methods described herein.

"Advantageously, the inventions described herein can be performed computationally (i.e., in silico) and therefore do not require studies such as gene expression profiling (e.g., therapeutic agent perturbation experiments) on control and disease samples.

BRIEF DESCRIPTION OF THE DRAWINGS

"FIG. 1 is a diagram depicting an exemplary embodiment of the present invention.

"FIG. 2 is an example connectivity map generated in an example embodiment of the present invention.

"FIG. 3 is a flow diagram depicting another exemplary embodiment of the present invention.

"FIG. 4 is a flow diagram depicting yet another exemplary embodiment of the present invention."

URL and more information on this patent application, see: Chen, Jake Yue. Inter-Class Molecular Association Connectivity Mapping. Filed October 21, 2013 and posted February 20, 2014. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&u=%2Fnetahtml%2FPTO%2Fsearch-adv.html&r=650&p=13&f=G&l=50&d=PG01&S1=20140213.PD.&OS=PD/20140213&RS=PD/20140213

Keywords for this news article include: Genetics, Peptides, Proteins, Amino Acids, Therapeutics, Medeolinx LLC, Clinical Trials and Studies.

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Source: Clinical Trials Week


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