John M. Barnar IRFS 040610

8/8/2019 John M. Barnar IRFS 040610

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www.digitalchemistry.co.uk

Searching the Atoms andBonds in Chemical Patents

Presented at IRF Symposium

Vienna, Austria

4 June 2010

Dr John M. Barnard

Scientific Director

Digital Chemistry Ltd., UK


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Outline Chemical structures in patents

Principles of searching for chemical structures

History of chemical structure searching in patents

Current developments

specific structures vs. Markush structures

automatic analysis vs. manual curation

online systems vs. in-house systems

Retrieval performance evaluation


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Chemical structures in patentsThe most important information

in a chemical patent is oftenthe chemical structure

disclosed or claimed.

- specifies atoms and bondspresent and the way they areconnected

- integrated mixture of textand structure diagrams


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Markush structures

N

NR3

CH3 O

R2

R1

R1 = phenyl / cyclohexyl / ...

R2 = H / methyl / ...

R3 = H / Cl / NO2 / ...

Dr EugeneMarkush(1887-1968)

Patents may include both Markushstructure claim and exemplifiedspecific structures.

Classes of molecules withcommon structural features may cover millions (or infinite numbers)

of specific structures

allow protection of related moleculeswith common properties

named after inventor involved in USlegal case in 1924


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Chemical structures in patents

Markushstructure

Specificstructure

name


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Markush structuresSpecific structures can be generated by combinatorialassembly of alternatives for each R-group

Variable-position

attachment

Variablemultiplicity

Genericgroups Specific

groups

Non-structuraldescription


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Substructure search Search a database of chemical structures for

all those containing a specified pattern ofatoms and bonds (substructure)

NCO

N

N

CH3 O

CH3

CH3

NHC

O

N

N

CH2

CH3

CH3

Query substructure:

Retrieved molecule Retrieved molecule Molecule not retrieved

N

N

N

CH3

O

CH3


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Substructure search Originally applied to databases of specificstructures (single, fully-defined molecules)Exact and deterministicsearch algorithms

based in topologicalgraph theory

100% recall

100% precision

Search retrieves all database molecules that containthe query substructure and none of those that don't.

Substructure search also possible for Markushstructures, but more complicated.


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Patent searching before 1980Chemical Fragmentation Codes

substructure fragments used as index terms

manually assigned by expert coders

applied both to specific and Markush structures

search uses Boolean logic for required combinations

Fragment codes wereoriginally designed for

punched cards.

Connectivity / alternativenessrelationships betweenfragments usually lost

Poor

Precision


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Patent searching the 1980s"Topological" / graphical systems introduced

- with display of structure diagrams

Initial work with non-patentdatabases journal literature "in-house" structures

Commercial systems

operational by start of decade "public" databases

CAS Online

Systme DARC

"in-house" data MDL MACCS etc.

Specific Structures Markush Structures

Sheffield University academic research

on patent Markushstorage and retrieval

Commercial systems

and databases launchedat end of decade

Markush DARC(Derwent / Questel / INPI)

MARPAT(Chemical Abstracts)


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Patent searching since 1990

Little change

still only available onlinewith proprietarydatabases

showing their age withclunky interfaces

fragment code systemsstill widely used

Commercial searchsystems Databases

New databases of specificstructures from patents

Reaxys (formerlyMDL/Elsevier ChemicalPatent Database

SURECHEM

Machine-readable patentdocuments available direct

from patent offices

Some automation in databasecreation


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Related developments

Markush applications outsidepatent field

informatics for"combinatorial libraries"

specific structureenumeration

physicochemical property

calculation

Markush searching Data mining

Chemical data extraction fromfree text and diagrams

structure diagram "OCR" chemical nomenclature

translation

Research work on capture ofMarkush structures from free-text patentsNew "in-house" systems for

patent Markush search underdevelopment

Markush applications outsidepatent field

informatics for"combinatorial libraries"

specific structureenumeration

physicochemical property

calculation


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Which way forward?

Markush structures cover the scope of thepatent more comprehensively (better recall),but are more complicated to search, and canlead to poor retrieval precision.

Which structures to index and search?

How to build the databases?

Exemplified / enumeratedspecific structures

Markush structure

Manual input andcuration

Automatic analysis offull text patent

At least at present, searchers regard curateddatabases as the "gold standard" for retrievalperformance.

or

or


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Different approachesSpecific

Structures

MarkushStructures

ManuallyCurated

AutomaticallyExtracted

MMS

MARPAT

SureChemCA Registry

DerwentChemistryResource

Reaxys

IBM

CLiDEchemoCR

Databases

Data-mining software

DecrIPt


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Using specific structuresConventional approach

Extract specific structures frompatent

manual curation

CA Registry Derwent Chemistry

Resource

automatic extraction SureChem

IBM combination of both

Reaxys

Search using standard

substructure search software

IssuesSelection of compounds

exemplified "prophetic"

anything with a name

Effectiveness of automatic

nomenclature identificationand translation

Correctness of systematicnames in patent document


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Using specific structuresOther "text analytics" approaches

Accelrys/Notiora WorkAutomatic chemical name to

structure conversionStructure "fingerprints" foreach molecule based onsubstructure fragments

Logical "OR" of fingerprintsfor whole patent

Structural similarity searchbased on logical "OR"fingerprints and maximumcommon substructure

IBM WorkAutomatic chemical name

to structure conversionVector representationderived from IUPACChemical Identifier (InChI)

Structural similaritysearch based oncomparison of vectorrepresentations


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Using Markush structuresExisting systems

Two online systems/databasesavailable since late 1980s

Merged Markush Service(ThomsonReuters /Markush DARC)

MARPAT (ChemicalAbstracts Service/STN)

Problems

Excessively broad Markushesdefy existing systems, and give

poor recall / precision

Searchers often faced withmanually sifting 1000+ hits tofind 5 or 6 relevant patents

R1 is a substituted orunsubstituted, mono-, di-or polycyclic, aromatic ornon-aromatic, carbocylicor heterocyclic ringsystem, or ...


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Searchers commentsDiscussion in "breakout group" at International PatentInformation Conference (IPI-Confex), Venice, Mar 2009

Multiple search tools are needed for comprehensive

retrieval Search strategies need to focus on the core structure

of interest and put up with poor precision

Current systems based on automatic extraction andanalysis of nomenclature have limited usefulness

Suggestions for improvement: ranking of search output

more comprehensive indexing of specific structures


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In-house Markush systems?Advantages over existing online systems

Informatics support fordrug discoveryIntegration of patent datawith other chemicaldatabases

end-user chemistaccess to patent data

Adding patentability criteriato drug design

Adjunct or preliminary toexisting systems

confidentiality advantages

Possib

leuse

ofstructural

similarity

and

clusteranalysis

techn

iques

Data miningStructure activity

analysisPhysico-chemicalproperty calculation

Competitive intelligence

Identification ofunpatented "gaps" inchemical space


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In-house Markush systems?Prospects

SoftwareNew Markush search systems

under development Digital Chemistry Ltd.

ChemAxon

Also work on selective

enumeration of specificstructures from Markush

DecrIPt Inc.

DatabasesExisting curated databases

ThomsonReuters haveexpressed interest inmaking MMS data available

MARPAT database anotherobvious possibility

"Home-grown" databases forspecialist purposes

input software needed

Automatic extraction from patentdocuments


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Automatic Markush extractionCurrently a "hot area" for research, after a fallow period

complex combined issues of text and image processing,nomenclature translation and semantic analysis

Sheffield University3 publications (1992-97), initiallyanalysing Derwent patent abstracts.

CLiDE Pro (KeyModule Ltd.)Work by A.P. Johnson (2009) extendingearlier chemical OCR software.

Cambridge UniversityUnilever Centre for Molecular InformaticsOngoing work by Murray-Rust group onanalysis of full-text patents, extendingOPSIN nomenclature translation program.

chemoCR (Fraunhofer SCAI)Recent work on prototype software forMarkush "reconstruction" from patenttext, with limited success.

Cambridge UniversityUnilever Centre for Molecular InformaticsOngoing work by Murray-Rust group onanalysis of full-text patents, extendingOPSIN nomenclature translation program.

ChemProspector (InfoChem)Ongoing research into extraction ofMarkush structures from patents. Commercially-viable operational

systems probably still some way off.


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Precision and recall

Substructure search finds allmolecules in database that

contain query substructure

Patent databases with specific structures

100% precision100% recall

Poor precision

Poor recall

Database contains irrelevant ortrivial molecules from patent text

Database omits moleculescovered by Markush structure

Database contains incorrectmolecules (errors in nomenclatureidentification / translation)


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Precision and recallPatent databases with Markush structures

Poor precision

Poor recall

Query substructure matcheshighly generic description inunimportant part of Markush

Using system search optionsto avoid matches with highlygeneric descriptions

"broad/narrowtranslation" (DARC)

"match level" (MARPAT)

N

N

N

CH3 O

CH3 matches

R84 is a substituted orunsubstituted, mono-, di- orpolycyclic, aromatic or non-aromatic, carbocylic orheterocyclic ring system, or ...


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Patent search evaluationChemical substructure search systems usuallygive 100% precision and 100% recall

retrieval performance evaluation not important

Not really true for chemical patent searches much more room for argument about

whether or not a hit is relevant

Designers of chemical patent search systems may

need to pay more attention to performance evaluation

Precision / Recalltrade-off

Evaluation of hitrelevance in context

of type of query

Consideration of the relativeimportance of different

parts of Markush(what the patent "teaches")


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TREC-CHEM Multi-year evaluation project under auspices of long-

running Text Retrieval Conferences (TREC)

Uses chemical patent data and queries with withrelevance judgements

Used to compare retrieval experiments performed bydifferent groups

Results from first year (2009) presented elsewhere

most search approaches based on automaticanalysis of patent text, nomenclature extraction etc.

some issues identified concerning automatedrelevance judgements based on cited prior artdocuments


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TREC-CHEM

It would be valuable to apply TREC-type evaluation to searchsystems for patent chemistry that are based on commercialdatabases

MARPAT vs. MMS/Markush DARC

existing systems and databases vs. new ones using newtechniques, automated data extraction etc.

There are many potential benefits to practising patent searchers ininvolving cheminformaticians in the IR-IP debate for which the IRF

provides a forum.

TREC-CHEM is not using data from curated databases these are the current "industry standard" against

which new approaches will ultimately be judged

TREC rules do not allow commercial databasesto be included


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Contact details

Dr John M. Barnard

Scientific Director, Digital Chemistry Ltd.46 Uppergate Road, Sheffield S6 6BX, UK

[email protected]+44 (0)114 233 3170

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John M. Barnar IRFS 040610