1550results about "Chemical property prediction" patented technology

A method and system for multi-scale anatomical and functional modeling of coronary circulation is disclosed. A patient-specific anatomical model of coronary arteries and the heart is generated from medical image data of a patient. A multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model. Blood flow is simulated in at least one stenosis region of at least one coronary artery using the multi-scale function model of coronary circulation. Hemodynamic quantities, such as fractional flow reserve (FFR), are computed to determine a functional assessment of the stenosis, and virtual intervention simulations are performed using the multi-scale function model of coronary circulation for decision support and intervention planning.

The invention provides a method for predicting the efficacy of a compound for treating psoriasis based on a pharmacokinetic / pharmacodynamic model.

This invention provides methods for determining drug specificity, therapeutic index and effective doses for individual patients. According to the methods of the invention, graded levels of drug are applied to a biological sample or a patient. A plurality of cellular constituents are measured to determine the activity of the drug on a target pathway and at least one off-target pathway. A drug specificity is determined by comparing the target and off target activities of the drug. A therapeutic concentration (or dose) is defined as a concentration (or dose) of the drug that induces certain response in the target pathway. A toxic concentration (or dose) is defined as a concentration (or dose) of the drug that induces certain response in the off target pathway. Therapeutic index is the ratio of the toxic concentration over therapeutic concentration. Methods are also provided to determine an effective dose of a drug for a patient by measuring the activity of the drug on the particular patient.

It is a purpose of this invention to accurately measure the properties of petroleum and petroleum fractions from a small volume of sample oil in a short period of time with less cost and energy for the analysis by vaporizing and distilling the respective components contained in the sample to be measured by a distillation apparatus. The components in the sample oil are first separated and vaporized by the distillation apparatus and the boiling point distribution of the respective components is measured. The property estimation means is equipped with a property estimation model for evaluating the property estimate value outputted from the property estimation model. The method is incorporated into standard or otherwise any distillation test apparatus to provide accurate measure of the thermodynamic and transport properties of undefined multicomponent mixtures such as crude oil, petroleum fractions, gas condensates and the like.

A computer based, iterative process for generating chemical entities with defined physical, chemical and / or bioactive properties. During each iteration of the process, (1) a directed diversity chemical library is robotically generated in accordance with robotic synthesis instructions; (2) the compounds in the directed diversity chemical library are analyzed to identify compounds with the desired properties; (3) structure-property data are used to select compounds to be synthesized in the next iteration; and (4) new robotic synthesis instructions are automatically generated to control the synthesis of the directed diversity chemical library for the next iteration.

A system for analyzing a vast amount of data representative of chemical structure and activity information and concisely providing conclusions about structure-to-activity relationships. A computer may adaptively learn new substructure descriptors based on its analysis of the input data. The computer may then apply each substructure descriptor as a filter to establish new groups of molecules that match the descriptor. From each new group of molecules, the computer may in turn generate one or more additional new groups of molecules. A result of the analysis in an exemplary arrangement is a tree structure that reflects pharmacophoric information and efficiently establishes through lineage what effect on activity various chemical substructures are likely to have. The tree structure can then be applied as a multi-domain classifier, to help a chemist classify test compounds into structural subclasses.

In some embodiments, systems and methods and apparatus are provided through which the equation of state is used to control a process through analyses of one or more properties of a fluid through an interactive modeler that models the equation of state for the fluid in the process based on measured signals and for selectively enabling the modeling of control changes to the process. In some embodiments, a device generates an indication of machine health based on variations on the equation of state for a fluid in a machine. In some embodiments, one or more properties for the fluid from at least one unmeasured machine parameter in the interactive modeler are determined for the machine at various operating states. In some embodiments, a difference between an expected one or more properties of the fluid beyond a set point indicates the health of the machine.

Abstract of Disclosure A computer-based system is described that provides users with the ability to develop high-fidelity digital quantitative representations of physical and chemical phenomena, and to employ an optimization-based approach to control associated physiochemical processes. The system includes a computational environment, intuitive user interface(s), integrated software libraries, analytical tools, and visualization / rendering engine that together provide an integrated framework for nanoscale modeling, analysis, simulation, and synthesis. Additionally, the system includes an optimal linear control synthesis methodology that incorporates a first order dynamic mathematical representation (of the conceptual molecular system) suitable for applying various pragmatic control system techniques including optimization of structured singular values, linear quadratic performance functions, Lyapunov criteria, or similar, for the purposes of nanoscale fabrication and molecular assembly.

This invention relates to methods and apparatus for determining the multi-dimensional topology of a substance (system) within a volume (space). A method according to a preferred embodiment of the invention comprises the steps of: acquiring a set of relative values for the density (scalar properties) of the volume, each value for a given location (point) within the volume; interpolating a set of functions to generate a continuous relative density for the volume; identifying critical points of the continuous relative density by using an eigenvector following method; and associating critical points with one another by following a gradient path of the continuous relative density between the critical points, The method is applicable to a wide range of data relating to fields such as crystallography, fluid dynamics, edge detection, and financial markets, to determine the topology of structures contained therein.

A biological modeling system and method for enhanced computer-aided analysis of biological response data provides information synthesized from multiple sources. An executable model of a biological system is developed from information and structures based on multiple sources. In a preferred embodiment, biological data sets are selected by a user from a first active viewer window on a user computer display. A model is created and then run using integrated pharmacokinetic software. The output is next analyzed using integrated analysis tools. Once analyzed, the model is balanced to ensure that it matches the information and structures. Once the model is created, run, and balanced, it can be used to draw attention to important relations through integrated reporting functions. This program could be run with such programs as NONMEM®.

The invention provides a computer readable medium or media, having: (a) a first data structure relating a plurality of reactants to a plurality of reactions from a first cell, each of said reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (b) a second data structure relating a plurality of reactants to a plurality of reactions from a second cell, each of said reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (c) a third data structure relating a plurality of intra-system reactants to a plurality of intra-system reactions between said first and second cells, each of said intra-system reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (d) a constraint set for said plurality of reactions for said first, second and third data structures, and (e) commands for determining at least one flux distribution that minimizes or maximizes an objective function when said constraint set is applied to said first and second data structures, wherein said at least one flux distribution is predictive of a physiological function of said first and second cells. The first, second and third data structures also can include a plurality of data structures. Additionally provided is a method for predicting a physiological function of a multicellular organism. The method includes: (a) providing a first data structure relating a plurality of reactants to a plurality of reactions from a first cell, each of said reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (b) providing a second data structure relating a plurality of reactants to a plurality of reactions from a second cell, each of said reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (c) providing a third data structure relating a plurality of intra-system reactants to a plurality of intra-system reactions between said first and second cells, each of said intra-system reactions comprising a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product; (d) providing a constraint set for said plurality of reactions for said first, second and third data structures; (e) providing an objective function, and (f) determining at least one flux distribution that minimizes or maximizes an objective function when said constraint set is applied to said first and second data structures, wherein said at least one flux distribution is predictive of a physiological function of said first and second cells.

Methods and systems for filtering variants in data sets comprising genomic information are provided herein.

Embodiments of the invention provide methods, systems, and articles of manufacture for modeling molecular properties based on information obtained from sources other than direct empirical measurements of the properties. Embodiments of the invention use “virtual data” related to molecular properties to train a molecular properties model. Virtual data about a molecule may include real-valued data (e.g. measurement values falling along a continuous range) or a positive or negative assertion about whether a molecule exhibits a property of interest. Virtual data may be generated using a variety of techniques and may be further characterized by confidence in the accuracy of the virtual data. In addition to virtual data, embodiments of the invention may use “virtual molecules” paired with “virtual data” to train a molecular properties model. The virtual molecules may themselves be generated in a variety of ways.

This invention presents an innovative framework for the application of machine learning for identification of alloys or composites with desired properties of interest. For each output property of interest, we identify the corresponding driving (input) factors. These input factors may include the material composition, heat treatment, process, microstructure, temperature, strain rate, environment or testing mode. Our framework assumes selection of optimization technique suitable for the application at hand and data available, starting with simple linear, or quadratic, regression analysis. We present a physics-based model for predicting the ultimate tensile strength, a model that accounts for physical dependencies, and factors in the underlying physics as a priori information. In case an artificial neural network is deemed suitable, we suggest employing custom kernel functions consistent with the underlying physics, for the purpose of attaining tighter coupling, better prediction, and extracting the most out of the—usually limited—input data available.

A method for predicting petroleum expulsion is provided. An exemplary embodiment of the method comprises defining a chemical structure of a kerogen and identifying a plurality of reaction products of the kerogen under geologic heating rates. The exemplary method also comprises grouping the plurality of reaction products into a plurality of product lumps based on their chemical composition and predicting petroleum expulsion for each of the plurality of product lumps based on secondary cracking reactions.

An extension of the vector space model for computing chemical similarity using textual and chemical descriptors is described. The method uses a chemical and / or textual description of a molecule / chemical and a decomposes a molecule / chemical descriptor matrix by a suitable technique such as singular value decomposition to create a low dimensional representation of the original descriptor space. Similarities between a user probe and the textual and / or chemical descriptors are then computed and ranked.

The present inventions relates to methods and assays to predict the response of an individual to a psychiatric treatment and to a method to improve medical treatment of a disorder, which is responsive to treatment with a psychiatric treatment.

A method for determining oral bioavailibility based on the linear regression computer program, SIMCA (Soft Independent Modelling of Class Analogy) is described.

A method of designing a material by optimising values for design variables includes the steps of: (i) providing one or more property models that produce a prediction for a value of a respective property of the material as a function of the design variables and produce a value for the uncertainty in the prediction, (ii) setting a specification target for a desired value for each property and a probability for that specification target to be met or exceeded, (iii) determining a probabilistic target for a value for each property, the probabilistic target being based on the specification target and the probability, and defining a merit index factor based on the degree to which a given prediction satisfies the probabilistic target, (iv) constructing an overall merit factor from the individual merit index factors of the properties, and (v) determining a set of optimal design variables that optimise the overall merit factor.

A method and system for planning and assessing the results of high-throughput solid form screening and high-throughput formulation screening are disclosed. Also disclosed are methods and systems for using high-throughput solid form screening and high-throughput formulation screening to select compounds and formulations for further testing, or to prioritize testing.

There is provided a method of developing a pharmacokinetic profile of an xenobiotic disposition in a mammalian tissue, the method comprising inputting mammalian-specific data into a physiologically based pharmacokinetic (PBPK) model, where said mammalian-specific data comprises tansporter properties related data, where said transporter properties related data reflect genetic and environmental factors associated with said mammalian; inputting xenobiotic-specific data into said PBPK model; and simulating, using said PBPK model, a pharmacokinetic profile of said xenobiotic disposition as a function of said inputted data.

A method for predicting a set of chemical, physical or biological features related to chemical substances or related to interactions of chemical substances including using at least 16 different individual prediction means, thereby providing an individual prediction of the set of features for each of the individual prediction means and predicting the set of features on the basis of combining the individual predictions, the combining being performed in such a manner that the combined prediction is more accurate on a test set than substantially any of the predictions of the individual prediction means.

A computer based, iterative process for generating chemical entities with defined physical, chemical and / or bioactive properties. During each iteration of the process, (1) a directed diversity chemical library is robotically generated in accordance with robotic synthesis instructions; (2) the compounds in the directed diversity chemical library are analyzed to identify compounds with the desired properties; (3) structure-property data are used to select compounds to be synthesized in the next iteration; and (4) new robotic synthesis instructions are automatically generated to control the synthesis of the directed diversity chemical library for the next iteration.

The invention disclosed herewith is a computer-implemented method for evaluating the toxicity of chemical compounds. In particular, some embodiments of the invention comprise importing microarray data representing measurements of the RNA transcription from hepatocytes, and running at least one algorithm (such as a coefficient penalized linear regression algorithm) on the imported data to assess potential adverse drug effects. After the evaluation has been carried out, the results are exported to reports or databases.In some embodiments of the invention, the algorithm has been trained on reference data using machine learning techniques.In some embodiments of the invention, the evaluation of toxicity is carried out concurrently with the evaluation of efficacy, where it can be used to assess the clinical value of the compounds evaluated.In some embodiments of the invention, the evaluation of toxicity is inserted into a pharmaceutical evaluation process prior to expensive testing of toxicity in animals.

The embodiment of the invention provides a simulation method and device for predicting lithium-ion battery material electrochemical performance and equipment. The simulation method comprises the stepsthat basic crystal structure parameters of an electrode material of a battery are acquired, and a crystal structure model of the electrode material is constructed; the crystal structure model is optimized, and optimal crystal structure parameters with minimum total energy are obtained; an optimal crystal is constructed according to the optimal crystal structure parameters; energy band calculationis performed on the optimal crystal, and an energy band, density of states and dynamic parameters of the optimal crystal are acquired; phonon spectrum calculation is performed on the optimal crystal,and thermodynamic parameters of the optimal crystal are acquired; a synthetic electrode material with the optimal crystal structure parameters is synthesized; the synthetic electrode material is adopted to construct a battery sample model, and dimension parameters of the battery are acquired; charge-discharge loop testing, battery surface temperature distribution testing and temperature rise curve testing are performed on the battery; an electrochemical-thermal coupling model of the battery is constructed; and the effectiveness of the electrochemical-thermal coupling model is verified.