Stephen C Hanson

US Patent:

7005454, Feb 28, 2006

Filed:

Feb 24, 1999

Appl. No.:

09/257145

Inventors:

Stephen Brocchini - Highland Park NJ, US
Stephen R. Hanson - Stone Mountain GA, US
Joachim B. Kohn - Highland Park NJ, US

Assignee:

Rutgers, The State University - New Brunswick NJ

International Classification:

A61K 47/30
A61K 47/32
A61K 47/34

US Classification:

5147721, 514772, 5147723, 424486

Abstract:

Polymeric drug formulations containing a non-releasing single-phase dispersion of a water-soluble drug in a water-insoluble tissue-compatible polymer matrix. Polymeric drug formulations are also disclosed containing a single-phase dispersion of a water-soluble drug and a water-insoluble tissue-compatible polymer matrix, and a second, phase-disrupting polymer that is non-miscible with the tissue-compatible polymer and is present in an amount sufficient to form phase-separated microdomains of the second polymer in the tissue-compatible polymer matrix, so that the release rate of the water-soluble drug from the tissue-compatible polymer matrix is related to the amount of the second polymer. Methods of preparing the polymeric drug formulations are also described, as well as methods for site-specific drug delivery utilizing the polymeric drug formulations.

US Patent:

7101840, Sep 5, 2006

Filed:

Jun 21, 2002

Appl. No.:

10/177097

Inventors:

Stephen Brocchini - Highland Park NJ, US
Stephen R. Hanson - Stone Mountain GA, US
Joachim B. Kohn - Highland Park NJ, US

Assignee:

Rutgers, The State University - New Brunswick NJ

International Classification:

C07K 14/00
C07K 16/00

US Classification:

514 2, 424485, 424486, 424487, 424488, 5147722, 5147723, 5147724, 5147725, 5147726, 530350

Abstract:

A method of forming a polymeric drug formulation in which a water-soluble drug is blended with a water-insoluble tissue-compatible polymer that is miscible in the solid phase with the drug, and with a poly(alkylene oxide), in a solvent system capable of forming a homogeneous solution of the drug, the tissue-compatible polymer and the poly(alkylene oxide), after which the solution is added to a non-solvent for the drug, the tissue-compatible polymer and the poly(alkylene oxide), so that a microdomain-separated solid co-precipitate of the drug, the tissue-compatible polymer and the poly(alkylene oxide) is formed, wherein the poly(alkylene oxide) is blended in an amount effective to form phase-separated microdomains in said co-precipitate.

US Patent:

58772243, Mar 2, 1999

Filed:

Jul 28, 1995

Appl. No.:

8/508577

Inventors:

Stephen Brocchini - Highland Park NJ
Stephen R. Hanson - Stone Mountain GA
Joachim B. Kohn - Highland Park NJ

Assignee:

Rutgers, The State University of New Jersey - New Brunswick NJ

International Classification:

A61K 4730
A61K 4732
A61K 4734
A61K 914

US Classification:

5147722

Abstract:

Polymeric drug formulations containing a non-releasing single-phase dispersion of a water-soluble drug in a water-insoluble tissue-compatible polymer matrix. Polymeric drug formulations are also disclosed containing a single-phase dispersion of a water-soluble drug and a water-insoluble tissue-compatible polymer matrix, and a second, phase-disrupting polymer that is non-miscible with the tissue-compatible polymer and is present in an amount sufficient to form phase-separated microdomains of the second polymer in the tissue-compatible polymer matrix, so that the release rate of the water-soluble drug from the tissue-compatible polymer matrix is related to the amount of the second polymer. Methods of preparing the polymeric drug formulations are also described, as well as methods for site-specific drug delivery utilizing the polymeric drug formulations.

US Patent:

54616980, Oct 24, 1995

Filed:

Jun 17, 1993

Appl. No.:

8/079687

Inventors:

Robert W. Schwanke - North Brunswick NJ
Stephen J. Hanson - Princeton NJ

Assignee:

Siemens Corporate Research, Inc. - Princeton NJ

International Classification:

G06F 1580
G06K 962

US Classification:

395 22

Abstract:

Given a set of objects (A, B, C,. . . ), each described by a set of attribute values, and given a classification of these objects into categories, a similarity function accounts well for this classification when only a small number of objects are not correctly classified. A method for modelling a similarity function using a neural network comprises the steps of: (a) inputting feature vectors to a raw input stage of a neural network respectively for object S in the given category, for other objects G in the same category being compared the object S, and for object B outside the given category; (b) coupling the raw inputs of feature vectors for S, G, and B to an input layer of the neural network performing respective set operations required for the similarity function so as to have a property of monotonicity; (c) coupling the input elements of the input layer to respective processing elements of an hidden layer of the neural network for computing similarity function results adaptively with different values of a coefficient w of the similarity function; (d) coupling the processing elements of the hidden layer to respective output elements of an output layer of the neural network for providing respective outputs of an error function measuring the extent to which object S is more similar to object G than to object B; and (e) obtaining an optimal coefficient w by back propagation through the neural network which minimizes the error outputs of the error function.