# US 2016/0259918 A1 · Computational Approach for Identifying a Combination of Two Drugs > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2016/0259918 A1 - Document ID: US20160259918A1 - Status: Published application - Kind: A1 - Application number: 15/028,178 - Filed: 2014-10-06 - Published: 2016-09-08 - Earliest claimed: 2013-10-08 - Assignees: Alacris Theranostics GmbH - Applicants: Alacris Theranostics GmbH - Inventors: Alexander KÜHN; Bodo LANGE; Svetlana PEYCHEVA; Hans LEHRACH; Christoph WIERLING - Web page: https://patentgrep.com/patent/US20160259918A1 ## CPC - G16C 20/30: Prediction of properties of chemical compounds, compositions or mixtures - G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 50/50: for simulation or modelling of medical disorders - G16C: COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract The present invention relates to a method for identifying a therapeutic drug combination against a cancer, wherein the cancer comprises at least two alterations in at least two different, but crosstalking signaling pathways, the method comprising the steps of: a) providing a kinetic model of a biological network for said cancer comprising the at least two different, but crosstalking signaling pathways, wherein the kinetic model is generated by choosing a network topology, wherein the nodes of said topology represent biological entities selected from the group comprising genes, transcripts, peptides, proteins, protein modification states, small molecules, complexes, metabolites and modifications thereof, and the edges of said topology represent interactions between said entities, assigning kinetic laws and kinetic constants to the interactions and assigning concentrations to the biological entities, such that the kinetic model reflects the genome, epi-genome, proteome and/or transcriptome of said cancer, b)selecting test combinations from a plurality of known drugs, each test combination comprising at least two drugs, c) simulating the effect of each test combination on the biological network, thereby d) identifying from said test combinations a drug combination that acts against said cancer. ## Claims ### Claim 1 A computer implemented method for identifying a therapeutic drug combination against a cancer, wherein the cancer comprises at least two alterations in at least two different, but crosstalking signaling pathways, the method comprising the steps of: a. providing a kinetic model of a biological network for said cancer comprising the at least two different, but crosstalking signaling pathways, wherein the kinetic model is generated by choosing a network topology, wherein the nodes of said topology represent biological entities selected from the group comprising genes, transcripts, peptides, proteins, protein modification states, small molecules, complexes, metabolites and modifications thereof, and the edges of said topology represent interactions between said entities, assigning kinetic laws and kinetic constants to the interactions and assigning concentrations to the biological entities, such that the kinetic model reflects the genome, epi-genome, proteome and/or transcriptome of said cancer, b. selecting test combinations from a plurality of known drugs, each test combination comprising at least two drugs, c. simulating the effect of each test combination on the biological network, thereby d. identifying from said test combinations a drug combination that acts against said cancer. ### Claim 2 A computer implemented method for predicting the response of a cancer to a therapeutic drug combination, wherein the cancer comprises at least two alterations in at least two different, but crosstalking signaling pathways, the method comprising the steps of: a. providing a kinetic model of a biological network for said cancer comprising the at least two different, but crosstalking signaling pathways, wherein the kinetic model is generated by choosing a network topology, wherein the nodes of said topology represent biological entities selected from the group comprising genes, peptides, nucleic acids, proteins, small molecules, complexes, metabolites and modifications thereof, and the edges of said topology represent interactions between said entities, assigning kinetic laws and kinetic constants to the interactions and assigning concentrations to the biological entities, such that the kinetic model reflects the genome, epigenome proteome and/or transcriptome of said cancer, b. providing a drug combination comprising at least two drugs, preferably one for each of the at least two different signaling pathways, c. simulating the effect of the drug combination on the biological network, thereby d. determining whether the cancer is responsive to the drug combination. ### Claim 3 (depends on 1) The method of claim 1, wherein the at least two alterations in the at least two signaling pathways are selected from the group comprising mutations, overexpression, fusions, epigenetic changes and insertions. ### Claim 4 (depends on 1) The method of claim 1, wherein crosstalk between the signaling pathways occurs via a protein shared by the signaling pathways, transmembrane crosstalk, crosstalk in transcriptional activation, or crosstalk on a transcriptional level. ### Claim 5 (depends on 1) The method of claim 1, wherein the kinetic model reflects crosstalk between the signaling pathways by biological entities shared by the signaling pathways. ### Claim 6 (depends on 1) The method of claim 1, wherein the at least two alterations are determined by analyzing at least parts of the genome, epigenome, transcriptome and/or proteome of said cancer. ### Claim 7 (depends on 6) The method of claim 6, wherein the genome, epigenome and/or transcriptome is analyzed by sequencing, preferably next-generation sequencing. ### Claim 8 (depends on 1) The method of claim 1, wherein the alterations are gain of function, loss of function or gene-overexpression like. ### Claim 9 (depends on 1) The method of claim 1, wherein the effect of each candidate is evaluated by entities reflecting cell survival, or cell proliferation. ### Claim 10 (depends on 1) The method of claim 1, further simulating the effect of a single drug of one of the candidates or the drug combination identified for said cancer on the biological network and comparing the effectiveness of one of the candidates or the drug combination identified for said cancer to the sum of the effectiveness of the single drugs corresponding to said combination. ### Claim 11 (depends on 1) The method of claim 1, wherein the at least two drugs have a known pharmacologic profile. ### Claim 12 (depends on 1) The method of claim 1, wherein the at least two drugs have a known IC50 value. ### Claim 13 (depends on 1) The method of claim 1, wherein the at least two drugs are targeted mechanistic drugs, preferably selected from the group of tyrosinase kinase inhibitors and monoclonal antibodies. ### Claim 14 (depends on 1) The method of claim 1, wherein the biological network represents a human or a part thereof, a tissue, a cell line, one or more cells or a mixture thereof. ### Claim 15 (depends on 1) The method of claim 1, wherein the identified drug combination is further tested in a cancer-specific cell line, a xenograft model and/or in clinical trials. ### Claim 16 (depends on 2) The method of claim 2, wherein the at least two alterations in the at least two signaling pathways are selected from the group comprising mutations, overexpression, fusions, epigenetic changes and insertions. ### Claim 17 (depends on 2) The method of claim 2, wherein crosstalk between the signaling pathways occurs via a protein shared by the signaling pathways, transmembrane crosstalk, crosstalk in transcriptional activation, or crosstalk on a transcriptional level. ### Claim 18 (depends on 2) The method of claim 2, wherein the kinetic model reflects crosstalk between the signaling pathways by biological entities shared by the signaling pathways. ### Claim 19 (depends on 2) The method of claim 2, wherein the at least two alterations are determined by analyzing at least parts of the genome, epigenome, transcriptome and/or proteome of said cancer. ### Claim 20 (depends on 19) The method of claim 19, wherein the genome, epigenome and/or transcriptome is analyzed by sequencing, preferably next-generation sequencing.