PROCESSING DRUG DATA

• US 20120209864A1
• Filed: 02/10/2012
• Published: 08/16/2012
• Est. Priority Date: 05/02/2001
• Status: Active Grant

• Current Assignee: Druglogic Incorporated
• Original Assignee: Druglogic Incorporated
• Inventors: Gogolak, Lara, Gogolak, Victor T.
• Granted Patent: US 8,694,555 B2
• Time in Patent Office: Days
• US Class Current: 707/755
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

Computer-assisted methods and systems of processing a drug information source. Characterizing the drug by the set comprising: syntax-parsed drug rule elements, adverse event data, mapped terms, and metadata. A method includes: creating a drug rule syntax; extracting metadata from the drug information source; extracting verbatim adverse event data from the drug information source; identifying drug rule content from the drug information source; mapping terms from verbatim data to a reference source; and parsing drug rule elements from at least one identified instance of drug rule content into the drug rule syntax, retaining associations between those drug rule elements that form a drug rule.

Claims

1. A computer-assisted method of processing a drug information source, the drug information source comprising at least one instance of drug rule content, each instance of drug rule content comprising at least one drug rule, the method comprising:

creating a drug rule syntax;

detecting at least one instance of drug rule content from a drug information source; and

parsing drug rule elements from at least one identified instance of drug rule content into the drug rule syntax, retaining associations between those drug rule elements that form a drug rule,

whereby a subset of the drug information source is processed into syntax-parsed drug rules.

2. The method of claim 1 wherein drug source information comprises at least one of:

drug label information; and

drug literature information.

3. The method of claim 1 wherein the drug rule syntax comprises drug rule syntax elements, each drug rule syntax element corresponding to a subset of a logical proposition.

4. A computer-assisted method of processing a drug information source, the drug information source comprising at least one instance of adverse event content, each instance of adverse event content comprising at least one adverse event characterization, the method comprising:

detecting at least one instance of adverse event content from a drug information source; and

parsing at least one adverse event characterization from at least one detected instance of adverse event content,

whereby a subset of the drug information source is processed into at least one parsed adverse event characterization.

5. The method of claim 4 further comprising:

validating at least one parsed adverse event characterization.

6. The method of claim 4, wherein:

adverse event content comprises text content, and

each adverse event characterization comprises the set of reaction name and frequency of occurrence characterization.

7. The method of claim 4, wherein:

adverse event content comprises text content, and

at least one adverse event characterization comprises the set of reaction name, lower limit frequency of occurrence, and higher limit frequency of occurrence.

8. The method of claim 4, wherein:

adverse event content comprises table content, and

at least one adverse event characterization comprises the set of reaction name, and nominal frequency of occurrence.

9. The method of claim 4, wherein:

adverse event content comprises table content, and

at least one adverse event characterization comprises the set of reaction name, lower limit frequency of occurrence, and higher limit frequency of occurrence

10. The method of claim 4, wherein at least one instance of adverse event content comprises an implicit adverse event characterization, and

the method further comprises

deriving an adverse event characterization from the implicit adverse characterization.

11. The method of claim 10, wherein:

the derived adverse event characterization comprises the set of reaction name, and nominal frequency of occurrence.

12. The method of claim 10, wherein:

the derived adverse event characterization comprises the set of reaction name, lower limit frequency of occurrence, and higher limit frequency of occurrence.

13. A method for processing a drug information source, the drug information source characterized by metadata, comprising verbatim data, and comprising at least one instance of drug rule content, each instance of drug rule content comprising at least one drug rule, the method comprising

creating a drug rule syntax;

extracting metadata from the drug information source;

extracting verbatim adverse event data from the drug information source;

identifying at least one instance of drug rule content from the drug information source;

mapping terms from verbatim data to a reference source;

parsing drug rule elements from at least one identified instance of drug rule content into the drug rule syntax, retaining associations between those drug rule elements that form a drug rule;

wherein the drug described by the drug information source is characterized by the set comprising;

the syntax-parsed drug rule elements, the mapped terms, and the metadata.

14. The method of claim 13, wherein:

the reference source comprises MedDRA.

15. The method of claim 13, wherein:

the reference source is selectable by a user.

16. The method of claim 13, wherein:

the mapping between a reference source term and the corresponding verbatim identifies the pedigree of each reference source term-verbatim pair.

17. The method of claim 13, further comprising:

associate remaining drug information source data with the drug,

wherein the drug described by the drug information source is characterized by the set comprising;

the syntax-parsed drug rule elements, the mapped terms, the metadata, and the remaining drug information source data.