An embodiment of the invention receives input including a list of drugs, drug characteristics of each drug, and known drug-disease associations including a disease and a drug having a threshold efficacy for treating the disease. For each drug in the list of drugs, a processor predicts whether the drug meets a threshold efficacy for treating a first disease based on the drug characteristics and the drug-disease associations. For each drug in the list of drugs, the processor predicts whether the drug meets a threshold efficacy for treating a second disease based on the drug characteristics and the predicting of whether the drug meets the threshold efficacy for treating the first disease. Output is generated output based on the predictions, the output including an identified drug-disease association, an identified disease-disease association, an identified chemical fingerprint for the first disease, and an identified chemical fingerprint for the second disease.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving input in an interface, the input including a list of drugs, drug characteristics of each drug in the list of drugs, and drug-disease associations, each of the drug-disease associations including a disease and a drug having a threshold efficacy for treating the disease; predicting whether each drug in the list of drugs meets a threshold efficacy for treating a first disease with a processor based on the drug characteristics and the drug-disease associations; predicting whether each drug in the list of drugs meets a threshold efficacy for treating a second disease with the processor based on the drug characteristics and said predicting whether each drug in the list of drugs meets the threshold efficacy for treating the first disease; and generating output based on said predicting whether the drug meets the threshold efficacy for treating the first disease and said predicting whether the drug meets the threshold efficacy for treating the second disease, the output including an identified drug-disease association, an identified disease-disease association, an identified chemical fingerprint for the first disease, and an identified chemical fingerprint for the second disease, the identified drug-disease association including at least one drug having a threshold predicted efficacy for treating at least one of the first disease and the second disease; the identified disease-disease association including at least one disease having a threshold level of similarity to at least one of the first disease and the second disease, the identified chemical fingerprint for the first disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the first disease, and the identified chemical fingerprint for the second disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the second disease. 2. The method according to claim 1, wherein the drug characteristics include a chemical structure of a drug. 3. The method according to claim 1, wherein the drug characteristics include a chemical-protein interactome of the drug. 4. The method according to claim 1, wherein the input further includes known disease-disease associations. 5. The method according to claim 1, wherein the input further includes known disease classifications. 6. The method according to claim 1, wherein said generating of the output includes generating the identified drug-disease association based on the drug-disease associations. 7. The method according to claim 1, wherein said generating of the output includes generating the identified drug-disease association based on the identified drug-disease association. 8. The method according to claim 1, wherein said generating of the output includes generating the identified drug-disease association based on the identified disease-disease association. 9. The method according to claim 1, wherein said generating of the output includes generating the identified drug-disease association based on the identified chemical fingerprint for the first disease. 10. The method according to claim 1, wherein said generating of the output includes generating the identified drug-disease association based on the identified chemical fingerprint for the second disease. 11. A method comprising: receiving input in an interface, the input including a list of drugs, drug characteristics of drugs in the list of drugs, and drug-disease associations, each of the drug-disease associations including a disease and a drug having a threshold efficacy for treating the disease; predicting whereshold efficacy for treating a first disease with a processor based on at least one of the drug characteristics and the drug-disease associations; predicting whether the drugs in the list of drugs meet a threshold efficacy for treating a second disease with the processor based on said predicting whether the drugs in the list of drugs meet the threshold efficacy for treating the first disease; and generating output including at least one of an identified drug-disease association, an identified disease-disease association, an identified chemical fingerprint for the first disease, and an identified chemical fingerprint for the second disease, the identified drug-disease association including at least one drug having a threshold predicted efficacy for treating at least one of the first disease and the second disease; the identified disease-disease association including at least one disease having a threshold level of similarity to at least one of the first disease and the second disease, the identified chemical fingerprint for the first disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the first disease, and the identified chemical fingerprint for the second disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the second disease. 12. The method according to claim 11, wherein the drug characteristics include a chemical structure of a drug. 13. The method according to claim 11, wherein the drug characteristics include a chemical-protein interactome of the drug. 14. The method according to claim 11, wherein the input further includes at least one of known disease-disease associations and known disease classifications. 15. The method according to claim 11, wherein said generating of the output includes generating the identified drug-disease association based on the drug-disease associations. 16. The method according to claim 11, wherein said generating of the output includes generating the identified drug-disease association based on the identified drug-disease association. 17. The method according to claim 11, wherein said generating of the output includes generating the identified drug-disease association based on the identified disease-disease association. 18. The method according to claim 11, wherein said generating of the output includes generating the identified drug-disease association based on the identified chemical fingerprint for the first disease. 19. The method according to claim 11, wherein said generating of the output includes generating the identified drug-disease association based on the identified chemical fingerprint for the second disease. 20. A computer program product comprising: a computer readable storage medium having stored thereon: first program instructions executable by a device to cause the device to receive input, the input including a list of drugs, drug characteristics of each drug in the list of drugs, and drug-disease associations, each of the drug-disease associations including a disease and a drug having a threshold efficacy for treating the disease; second program instructions executable by the device to cause the device to, for each drug in the list of drugs, predict whether the drug meets a threshold efficacy for treating a first disease based on at least one of the drug characteristics and the drug-disease associations; third program instructions executable by the device to cause the device to, for each drug in the list of drugs, predict whether the drug meets a threshold efficacy for treating a second disease based on the predicting of whether the drug meets the threshold efficacy for treating the first disease; and fourth program instructions executable by the device to cause the device to generate output including at least one of an identified drug-disease association, an identified disease-disease association, an identified chemical fingerprint for the first disease, and an identified chemical fingerprint for the second disease, the identified drug-disease association including at least one drug having a threshold predicted efficacy for treating at least one of the first disease and the second disease; the identified disease-disease association including at least one disease having a threshold level of similarity to at least one of the first disease and the second disease, the identified chemical fingerprint for the first disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the first disease, and the indentified chemical fingerprint for the second disease including a numerical code identifying a known chemical structure having a predicted efficacy for treating the second disease.