Data processing: artificial intelligence – Neural network
Reexamination Certificate
2006-06-06
2006-06-06
Moran, Marjorie A. (Department: 1631)
Data processing: artificial intelligence
Neural network
C702S019000, C435S005000
Reexamination Certificate
active
07058616
ABSTRACT:
A method and system for predicting the resistance of a disease to a therapeutic agent is provided. Further provided is a method and system for designing a therapeutic treatment agent for a patient afflicted with a disease. Specifically, the methods use a trained neural network to interpret genotypic information obtained from the disease. The trained neural network is trained using a database of known or determined genotypic mutations that are correlated with phenotypic therapeutic agent resistance. The present invention also provides methods and systems for predicting the probability of a patient developing a genetic disease. A trained neural network for making such predictions is also provided.
REFERENCES:
patent: 5769074 (1998-06-01), Barnhill et al.
patent: 5845049 (1998-12-01), Wu
patent: 5860917 (1999-01-01), Comanor et al.
patent: 5862304 (1999-01-01), Ravdin et al.
patent: 5898792 (1999-04-01), Öste et al.
patent: 5930154 (1999-07-01), Thalhammer-Reyero
patent: 5953727 (1999-09-01), Maslyn et al.
patent: WO 97/27480 (1997-07-01), None
Draghici et al. Correlation of HIV Protease Structure with Indinivir Resistance: a Data Mining and Neural Networks Approach. Proceedings of SPIE, vol. 4057, Apr. 2000, pp. 319-329 in: Data Mining and Knowledge Discovery: Theory, Tools and Technology.
Abidi et al. Applying Knowledge Discovery to Predict Infectious Disease Epidemics : PRICAI '98 : Topics in Artificial Intelligence. Springer-Verlag, Berlin, Germany, 1998, pp. 170-181.
Almeida et al.Application of Artificial Neural Networks to the Detection ofMycobacterium. . . Binary Computing in Microbiology (1995) vol. 7 No. 4-6, pp. 159-166.
Ioannidis et al. (American Journal of Epidemiology (1998) vol. 147, No. 5, pp. 464-471).
Harrigan et al. (AIDS (1999) vol. 13, No. 14, pp. 1863-1871).
Allex et al., “Neural Network Input Representations that Produce Accurate Consensus Sequences from DNA Fragment Assemblies;” BioInformatics, vol. 15, No. 9, pp. 723-728 (Sep. 1999).
Alvager et al., “Neural Network Method to Analyze Data Compression in DNA and RNA Sequences,” Journal of Chemical Information and Computer Sciences, vol. 37, pp. 335-337 (1997).
Bloor et al., “Lamivudine-Resistant HIV-1 Clinical Isolates Lacking the Met184Val Mutation Have Novel Polymorphisms in RT,” Abstract 25 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 19 (Jun. 23-26, 1999).
Bruisten et al., “Prospective Longitudinal Analysis of Viral Load and Surrogate Markers in Relation to Clinical Progression in HIV Type 1-Infected Persons” Aids Research and Human Retroviruses, vol. 13, No. 4, pp. 327-335 (1997).
Cai and Bork, “Homology-Based Gene Prediction Using Neural Nets,” Analytical Biochemistry, vol. 265, pp. 269-274 (1998).
Chow and Cho, “Developmet of a Recurrent Sigma-Pi Neural Network Rainfall Forecasting System in Hong Kong,” Neural Computing & Applications, vol. 5, pp. 66-75 (1997).
de Béthune et al., “Does Natural or Acquired Resistance to Reverse Transcriptase and Protease inhibitors, Observed in HIV-1 Groups M (Subtypes A-H) and O, Differ from Subtype B?,” Abstract 49 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 33 (Jun. 23-26, 1999).
Granjeon and Tarroux, “Detection of Compositional Constraints in Nucleic Acid Sequences Using Neural Networks,” Computer Applications in the Biosciences, vol. 11, No. 1, pp. 29-37 (1995).
Hammer et al., “Relationship of Phenotypic and Genotypic Resistance Profiles to Virological Outcome in a Trial of Abacavir, Nelfinavir, Efavirenz and Adefovir Dipivoxil in Patients with Virological Failure Receiving Indinavir (ACTG 372),” Abstract 64 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 45 (Jun. 23-26, 1999).
Hanke et al., “Self-Organizing Hierarchic Networks for Pattern Recognition in Protein Sequence,” Protein Science, vol. 5, pp. 72-82 (1996).
Harrigan et al., “Baseline HIV Drug Resistance Profile Predicts Response to Ritonavir—Saquinavir Protease Inhibitor Therapy in a Community Setting,” AIDS, vol. 13, No. 14, pp. 1863-1871 (1999).
Harrigan et al., “Drug Resistance and Short Term Virological Response in Patients Prescribed Multidrug Rescue Therapy,” Abstract 62 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 43 (Jun. 23-26, 1999).
Hertogs et al., “Common, Rare and New Genotypic and/or Phenotypic HIV-1 Resistance Profiles Observed in Routine Clinical Practice: A Survey of Over 5000 Isolates,” Abstract 108 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p.75 (Jun. 23-26, 1999).
Hertogs et al., “A Rapid Method for Simultaneous Detection of Phenotypic Resistance to Inhibitors of Protease and Reverse Transcriptase in Recombinant Human Immunodeficiency Virus Type 1 Isolates form Patients Treated with Antiretroviral Drugs,” Antimicrobial Agents and Chemotherapy, vol. 42, No. 2, pp. 269-276 (Feb. 1998).
Kashiwase et al., “A New Fluoroquinolone Derivative Exhibits Inhibitory Activity Against Human Immunodeficiency Virus Type 1 Replication,” Chemotherapy, vol. 45, pp. 48-55 (1999).
Kemp et al., “Analysis of 5000 HIV-1 Clinical Samples Reveals Complex Non-Nucleoside RT Inhibitor Resistance Patterns,” Abstract 26 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 20 (Jun. 23-26, 1999).
Kemp et al., “A Novel Polymorphism at Codon 333 of Human Immunodeficiency Virus Type 1 Reverse Transcriptase Can Facilitate Dual Resistance to Zidovudine and L-2′,3′-Dideoxy-3′-Thiacytidine,” Journal of Virology, vol. 72, No. 6, pp. 5093-5098 (1998).
Kempf et al., “Analysis of Virological Response to ABT-378/Ritonavir Therapy in Protease Inhibitor-Experienced Patients with Respect to Baseline Viral Phenotype and Genotype,” Abstract 8 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 6 (Jun. 23-26, 1999).
Larder and Stammers, “Closing in on HIV Drug Resistance,” Nature Structure Biology, vol. 6, No. 2, pp. 103-106 (Feb. 1999).
Larder et al., “A Family of Insertion Mutations Between Codons 67 and 70 of Human Immuno-deficiency Virus Type 1 Reverse Transcriptase Confer Multinucleoside Analog Resistance,” Antimicrobial Agents and Chemotherapy, vol. 43, No. 8, pp. 1961-1967 (Aug. 1999).
Larder et al., “Potential Mechanism for Sustained Antiretroviral Efficacy of AZT-3TC Combination Therapy,” Science, vol. 269, pp. 696-699 (1995).
Larder et al., “Predicting HIV-1 Phenotypic Resistance from Genotype Using a Large Phenotype-Genotype Relational Database,”Abstract 59 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 41 (Jun. 23-26, 1999).
Larder et al., “Tipranavir is Active Against a Large Selection of Highly Protease Inhibitor-Resistant HIV-1 Clinical Samples,” Abstract 5 at 3rd International Workshop on HIV Drug Resistance & Treatment Strategies, Antiviral Therapy, vol. 4, Supp. 1, p. 5 (Jun. 23-26, 1999).
Lehne et al., “Challenging Drug Resistance in Cancer Therapy,” Acta Oncologica, vol. 37, No. 5, pp. 431-439 (1998).
Lende and Csernai, “Classification of Genetic Sequences with Backpropagation,” International Journal of Neural Systems, vol. 5, No. 3, pp. 159-163 (Sep. 1994).
Lennerstrand et al., “Mechanism of Zidovudine and Stavudine Resistance for HIV-1 RT with Amino Acid Insertions Between Codons 68 and 70,” Abstract 32 at 3rd International Workshop
Larder Brendan
Wang Dechao
Clow Lori A.
Moran Marjorie A.
Virco Bvba
Woodcock & Washburn LLP
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