Pharmacovigilance database

• US 6,778,994 B2
• Filed: 05/02/2001
• Issued: 08/17/2004
• Est. Priority Date: 05/02/2001
• Status: Active Grant

• Current Assignee: Druglogic Incorporated
• Original Assignee: Victor Gogolak
• Inventors: Gogolak, Victor
• Primary Examiner(s): Robinson, Greta
• Assistant Examiner(s): RAYYAN, SUSAN F
• Application Number:
  US09/681,587
• Publication Number:
  US 20020165853A1
• Time in Patent Office: 1,203 Days
• Field of Search: 707/100, 707/1, 707/102, 707/205-206, 704/1-10, 715/530-533
• US Class Current: 1/1
• 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

A system and method for developing a pharmacovigilance database from source data and reference data. The unedited source data contains verbatim terms. The method includes parsing source data into a relational safety database; performing cleanup on the relational safety database; and mapping verbatim terms from the cleaned safety database to at least one token from at least one reference source. Cleanup includes removing redundant entries, correcting misspellings, removing irrelevant non-alpha characters and noise words, and relocating dislocated terms. Mapping verbatim terms to tokens includes nominating tokens from the source data, choosing tokens from the reference sources, and linking chosen tokens to corresponding verbatim terms. In one embodiment, the history of clean-up and mapping is saved as the pedigree of the verbatim-to-token mapping.

Claims

1. A method for developing a pharmacovigilance database from source data having verbatim terms and from reference data, wherein the source data represents a plurality of cases regarding effects experienced by persons using one or more drugs, the method comprising:

parsing the source data into a relational database;

performing cleanup on the source data stored in the relational database and storing cleaned up source data in the relational database; and

mapping verbatim terms from the cleaned up source data to at least one token, the token being at least one of (1) a term from the reference data and (2) a term selected from the verbatim terms,

wherein when the token is selected from the verbatim terms, the step of mapping comprises analyzing the verbatim terms contained in the plurality of cases, nominating one of the verbatim terms as a likely correct token in view of other data associated with the verbatim terms, and selecting the nominated token as the at least one token for mapping,

whereby a pharmacovigilance database comprising the cleaned up source data and mapped tokens is developed.

3. The method of claim 1, wherein parsing further comprises parsing at least one of publicly available source data and privately available source data into the relational database.

4. The method of claim 3, wherein the publicly available source data comprises at least one of Spontaneous Reporting System (SRS) data and Adverse Event Reporting System (AERS) data.

5. The method of claim 1, performing cleanup further comprises, suppressing at least one redundant entry.

6. The method of claim 1, wherein performing cleanup further comprises, suppressing printable and non-printable non-alpha characters.

7. The method of claim 1, wherein performing cleanup further comprises, suppressing numeric characters.

8. The method of claim 1, wherein performing cleanup further comprises, suppressing noise words.

9. The method of claim 1, wherein performing cleanup further comprises, suppressing combination words.

10. The method of claim 1, wherein performing cleanup further comprises, suppressing misspellings.

11. The method of claim 10, wherein suppressing misspellings further comprises:

interactively identifying likely misspelled terms to an operator;

accepting direction from an operator; and

editing the likely misspelled term for which direction was accepted in accordance with the direction.

12. The method of claim 11, wherein suppressing misspellings further comprises nominating at least one correction for at least one likely misspelled term to an operator.

13. The method of claim 1, wherein performing cleanup further comprises moving at least one valid, but dislocated, entry to a proper field in the relational database for that entry.

14. The method of claim 1, wherein the other data associated with the verbatim terms comprises at least one of age, sex, dates, reaction, dose, outcomes, report sources, and concomitant drugs.

15. The method of claim 1, further comprising providing an interactive display for selecting the token.

16. The method of claim 1, further comprising displaying pedigree information generated in the course of performing the step of mapping verbatim terms to at least one token.

17. The method of claim 1, further comprising record linking to match successor case reports with predecessor case reports.

18. The method of claim 17, further comprising comparing predetermined fields in each of the reports.

19. The method of claim 1, further comprising capturing and using domain-specific lexical knowledge.

20. The method of claim 5, wherein the step of suppressing at least one redundancy comprises analyzing at least two separate cases of the plurality of cases to determine whether the at least two cases represent a single case with multiple events.

2. A method for developing a pharamcovigilance database from source data having verbatim terms and from reference data, wherein the source data represents a plurality of cases regarding effects experienced by persons using one or more drugs, the method comprising:

performing cleanup on the source data to obtain cleaned up source data;

parsing the cleaned up source data into a relational database; and

mapping verbatim terms from the cleaned up source data to at least one token, the token being at least one of (i) a term from the reference data and (2) a term selected from the verbatim terms,

wherein when the token is selected from the verbatim terms, the step of mapping comprises analyzing the verbatim terms contained in the plurality of cases, nominating one of the verbatim terms as a likely correct token in view of other data associated with the verbatim terms, and selecting the nominated token as the at least one token for mapping,

whereby a pharmacovigilance database comprising the cleaned up source data and mapped tokens is developed.