Dimitris Agrafiotis

US Patent:

6434490, Aug 13, 2002

Filed:

Dec 17, 1998

Appl. No.:

09/213156

Inventors:

Dimitris K. Agrafiotis - Exton PA
Roger F. Bone - Bridgewater NJ
Francis R. Salemme - Kennett Square PA
Richard M. Soll - Lawrenceville NJ

Assignee:

3-Dimensional Pharmaceuticals, Inc. - Exton PA

International Classification:

G01N 3100

US Classification:

702 27, 435 724, 435 691, 435 912

Abstract:

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.

US Patent:

6453246, Sep 17, 2002

Filed:

May 7, 1998

Appl. No.:

09/073845

Inventors:

Dimitris K. Agrafiotis - Downingtown PA
Victor S. Labanov - Yardley PA
Francis R. Salemme - Yardley PA

Assignee:

3-Dimensional Pharmaceuticals, Inc. - Exton PA

International Classification:

G06F 1700

US Classification:

702 27, 702 32, 702179, 382225

Abstract:

A system, method and computer program product for representing precise or imprecise measurements of similarity/dissimilarity (relationships) between objects as distances between points in a multi-dimensional space that represents the objects. Self-organizing principles are used to iteratively refine an initial (random or partially ordered) configuration of points using stochastic relationship/distance errors. The data can be complete or incomplete (i. e. some relationships between objects may not be known), exact or inexact (i. e. some or all of the relationships may be given in terms of allowed ranges or limits), symmetric or asymmetric (i. e. the relationship of object A to object B may not be the same as the relationship of B to A) and may contain systematic or stochastic errors. The relationships between objects may be derived directly from observation, measurement, a priori knowledge, or intuition, or may be determined indirectly using any suitable technique for deriving proximity (relationship) data.

US Patent:

6506784, Jan 14, 2003

Filed:

Jun 29, 2000

Appl. No.:

09/606986

Inventors:

Daljit S. Dhanoa - West Chester PA
Dario Doller - Branford CT
Sanath Meegalla - Devon PA
Richard M. Soll - Lawrenceville NJ
Dimitris Agrafiotis - Downingtown PA
Nancy Wisnewski - Fort Collins CO
Gary M. Silver - Fort Collins CO
Dan T. Stinchcomb - Fort Collins CO
R. Lee Seward - Eaton CO

Assignee:

3-Dimensional Pharmaceuticals, Inc. - Exton PA
Heska Corporation - Fort Collins CO

International Classification:

A01N 4356

US Classification:

514407, 5483704

Abstract:

The present invention is directed to inhibiting pest GABA receptors by contacting said receptors with a compound of Formula I: The invention is also directed to methods of controlling pests, especially insects and arachnids such as fleas and ticks, and to novel compounds within the scope of Formula I.

US Patent:

6671627, Dec 30, 2003

Filed:

Feb 28, 2001

Appl. No.:

09/794106

Inventors:

Dimitris K. Agrafiotis - Downingtown PA
Victor S. Lobanov - North Brunswick NJ
Francis Raymond Salemme - Yardley PA

Assignee:

3-D Pharmaceuticals, Inc. - Exton PA

International Classification:

G01N 3348

US Classification:

702 27, 365 94

Abstract:

A greedy method for designing combinatorial arrays. An array of reagents are initially selected from a list of candidate reagents in a combinatorial library. The reagents in the array that maximize a design objective are determined in an iterative manner, by examining each variation site in the combinatorial library in a strictly alternating sequence. During each step, each candidate reagent at a given variation site is evaluated by constructing and evaluating the sub-array resulting from the systematic combination of that reagent with the selected reagents at all the other variation sites in the library. The candidate reagents at that variation site are ranked according to the fitness of their respective sub-arrays, and the reagents with the highest fitness are selected. The process is repeated for each variation site in the combinatorial library, until the fitness of the full combinatorial array can no longer be improved.

US Patent:

6678619, Jan 13, 2004

Filed:

Sep 20, 2001

Appl. No.:

09/956252

Inventors:

Victor S. Lobanov - Yardley PA 19067
Dimitris K. Agrafiotis - Downingtown PA 19335
Francis R. Salemme - Yardley PA 19067

International Classification:

G01N 3350

US Classification:

702 32, 435DIG 51

Abstract:

The present invention provides a method, system, and computer program product for encoding and building products of a virtual combinatorial library. A chemical reaction and reagent data for forming products of the virtual combinatorial library are encoded in a computer readable form. A compiler then operates on the encoded information and generates reagent mapping data. The compiler compiles the encoded chemical reaction to genenerate computer instructions that control the operation of a processor. A compact data structure containing data is generated and stored in a memory. This data structure is then used to gain immediate access to any of the products of the virtual combinatorial library.

US Patent:

6834239, Dec 21, 2004

Filed:

Aug 22, 2001

Appl. No.:

09/934084

Inventors:

Victor S. Lobanov - Yardley PA 19067
Dimitris K. Agrafiotis - Downingtown PA 19335
F. Raymond Salemme - Yardley PA 19067

International Classification:

G06F 1900

US Classification:

702 22, 702 19

Abstract:

The present invention determines properties of combinatorial library products from features of library building blocks. At least one feature is determined for each building block of a combinatorial library having a plurality of products. A training subset of products is selected from the products, and at least one property is determined for each product of the training subset. A building block set is identified for each product of the training subset, and an input features vector is formed from the features of the identified building blocks for each product of the training subset. A supervised machine learning approach is used to infer a mapping function that transforms the input features vector for each product of the training subset to the corresponding at least one property for each product of the training subset. After the mapping function is inferred, it is used for determining properties of other products of the library from their corresponding input features vectors.

US Patent:

7054757, May 30, 2006

Filed:

Jan 29, 2002

Appl. No.:

10/058216

Inventors:

Dimitris K Agrafiotis - Downingtown PA, US
Victor S Lobanov - Yardley PA, US
Francis R Salemme - Yardley PA, US

Assignee:

Johnson & Johnson Pharmaceutical Research & Development, L.L.C. - Raritan NJ

International Classification:

G01N 33/48
G06F 7/00
C12Q 1/68

US Classification:

702 19, 702 20, 702 22, 702 27, 702 30, 707102, 703 11, 435 6, 435DIG 51

Abstract:

The invention provides for in silico analysis of a virtual combinatorial library. Mapping coordinates for a training subset of products in the combinatorial library, and features of their building blocks, are obtained. A supervised machine learning approach is used to infer a mapping function ƒ that transforms the building block features for each product in the training subset of products to the corresponding mapping coordinates for each product in the training subset of products. The mapping function ƒ is then encoded in a computer readable medium. The mapping function ƒ can be retrieved and used to generate mapping coordinates for any product in the combinatorial library from the building block features associated with the product.

US Patent:

7188055, Mar 6, 2007

Filed:

Mar 12, 2001

Appl. No.:

09/802956

Inventors:

Dimitris K Agrafiotis - Downingtown PA, US
Victor S Lobanov - N. Brunswick NJ, US
Francis R Salemme - Yardley PA, US

Assignee:

Johnson & Johnson Pharmaceutical Research, & Development, L.L.C. - Raritan NJ

International Classification:

G06F 17/50
G06F 19/00

US Classification:

703 2, 703 12, 702 22, 382154

Abstract:

A system, method, and computer program product for visualizing and interactively analyzing data relating to chemical compounds. A user selects a plurality of compounds to map, and also selects a method for evaluating similarity/dissimilarity between the selected compounds. A non-linear map is generated in accordance with the selected compounds and the selected method. The non-linear map has a point for each of the selected compounds, wherein a distance between any two points is representative of similarity/dissimilarity between the corresponding compounds. A portion of the non-linear map is then displayed. Users are enabled to interactively analyze compounds represented in the non-linear map.