SlideShare a Scribd company logo
1 of 39
Download to read offline
Mind the Gap: The novel benefits of
human-curated substance locations for
chemical patent analysis
Aalt van de Kuilen, Patent Information Services BV, NL
Paul Peters, CAS/ACS International, DE
ICIC 2016
October 18, 2016
Heidelberg, Germany
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
Finding the relevant section(s) within the full-text of chemical
patents is often a time-consuming challenge
• They are not always as easy to track
down as we might expect
• They can be long and “artfully” written
• The chemistry is often obscured within complex
names, tables, text, graphics, etc.
Sometimes it seems like the
search may be complete, but
the hunt is just beginning!
Even with a precise chemical patent search, reviewing the results
can quickly become overwhelming
=> FILE CAPLUS
=> S L3
L4 1014 L3
=> S L4 AND (BET OR BROMODOMAIN) AND P/DT
L5 35 L4 AND (BET OR BROMODOMAIN) AND P/DT
A query combining structure and text
terms yields 35 patent publications.
That shouldn’t be too bad, right?
Only 5,498 pages to review.
479
pages
428
pages
321
pages
277
pages
263
pages
261
pages
240
pages
229
pages
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
3
Technology can help, but algorithmic extraction of chemistry in
patents has significant limitations
4
Conclusion: Algorithmic extraction successfully found
only 50-60% of the chemical structures in patents
based on a limited sample, and they were often the
least interesting ones.
Algorithms miss key substances for a myriad of reasons
• Ambiguous naming
• Markush representations
• No name – Explanatory text or
images, rather than as chemical
names or structures
• Stereochemistry issues
• Multi-component substances
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
5
Normally PSS is used for poly(styrenesulfonic acid), but here
it represents the aqueous dispersion, which CAS previously
identified as poly(1-vinyl-2-pyrolidone)
Normally PSS is used for poly(styrenesulfonic acid), but here
it represents the aqueous dispersion, which CAS previously
identified as poly(1-vinyl-2-pyrolidone)
PatentPakTM addresses this gap by combining human curation
with new technology to expedite chemical patent analysis
• Rapidly track down the specific location of hard-to-find chemical information
in patents with interactive links to key substances
– Benefit from the indexing efforts of hundreds of CAS scientists
• Instantly and securely access patent PDFs from major patent offices
– No more wasting time navigating multiple web sites
• Locate patents in languages you know with CAplusSM
global patent family
coverage
– Save time and translation costs
• Conveniently share these benefits with other IP stakeholders
– Even if they do not use STN® or SciFinder®
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
6
PatentPak is built on the indexing effort of the scientific analysts
that create CAS REGISTRYSM
• Scientists review each patent and
identify new substances for CAS
REGISTRY inclusion
• They mark the specific location of
substances in the text during analysis
• Algorithmic processing with human
intervention allows previously registered
substances to be located and annotated
in backfile documents
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
7
“I analyzed the chemistry in this
entire patent to save you time.”
Keiko Sugimoto
Sr. Scientific Information Analyst, CAS
CAS is a division of the American Chemical Society.
Copyright 2015 American Chemical Society. All rights reserved. 8
PatentPak supplements CAplus records with direct pointers to the
chemistry of interest
Bibliographic information (partially shown)
Hit substance indexing including roles
Hit structure display from CAS REGISTRY
PatentPak links for each hit compound
PatentPak links for document
CAS is a division of the American Chemical Society.
Copyright 2015 American Chemical Society. All rights reserved.
It is possible to access the original PDF…
CAS is a division of the American Chemical Society.
Copyright 2015 American Chemical Society. All rights reserved.
… the annotated PDF (PDF +) …
CAS is a division of the American Chemical Society.
Copyright 2015 American Chemical Society. All rights reserved.
… or review the patent using the interactive viewer
PatentPak links are available in transcripts, tables, and reports
and accessible without an STN login ID to support workflow
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
12
No STN login ID required
PatentPak is also available in SciFinder
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All
rights reserved.
New CAplus records from 31 countries are annotated as part of the
normal workflow, and the backfile is growing rapidly
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
14
The current backfile project will extend historical PatentPak
coverage of key offices by more than a decade by year end
ACS / Proprietary and Confidential / Do Not Distribute 15
16
PatentPak example US5739376: Backfile operation for one of the
first patents on Fullerene derivatives (Hoechst AG)
• Originally a
German basic
patent from 1994
but substance
locations have
been added to the
US equivalent
from 1998
• Fullerene structures
were symbolized by
simple rings
PatentPak example WO2016087417: substances identified in a
Markush table (Bayer CropScience AG)
• Only a few selected
substances in this
patent are fully
identified by name
or structure
• The vast majority
of substances are
indexed by
assembling
Markush tables
PatentPak example WO9851681: Substance identified as “oily
product” (Sanofi)
• This particular
substance is
only identified
as “oily product”
• CAS analyst
indexing from
the chemistry
PatentPak example WO2016120821: Find substances that cannot be
identified by algorithm or structure extraction (Novartis AG)
• Substances in formula VII
are claimed by Markush:
LG = “leaving group”
• Analyst marked four specific
compounds which are
defined later in the claims -
only a human can process
claims like this!
PatentPak example DE2013016487: Multiple location markings
(University of Heidelberg)
• Analyst has
marked multiple
locations - claims
and synthetic
example
21
PatentPak example WO2016001362: Find substances inferred by
their starting material after enzymatic conversion (BASF)
• Starting
materials
(substrates)
identified by
structure on
page 51
• Products not
listed but
inferred in a
table on
page 27
PatentPak example WO2015018558: Inorganic chemistry can be
equally challenging (PI Ceramic GmbH)
PatentPak example WO2014184355: Find assembled Markush tables
(Dr. August Wolff GmbH & Co Arzeneimittel)
• 9.5 pages of "table
Markush“ structures - a
core structure shown at
the top, with fragments
• The complete structure is
assembled in a table at
the back of PDF+
document, including page
numbers, CAS RN,
chemical name, and
structures
Case study on new Vitamin D metabolites
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
24
How many patent families have been filed since 2013 on new
Vitamin D metabolites?
Find the answer by with
Stepwise approach
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
25
1. Structure search in Registry
2. Remove old compounds
3. Keep compounds with low reference count in CAplus
4. Transfer to Chemical Abstracts
5. Limit to new compounds and published in patents
6. Display records which have a PatentPak record
PatentPak PDF| PatentPak PDF+ | PatentPak Interactive
Structure
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
26
Q
CH
2
CH
3
Ak
Broad definition of Vitamin D skeleton
All rings are isolated and double bonds
are mandatory
CAS REGISTRY search
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
27
FILE 'REGISTRY‘ ENTERED ON 22 SEP 2016
STRUCTURE UPLOADED
=> L3 has 6806 unique substances in Registry
Refine to compounds registered since 2001 (ED>2000)
=> L4 has 2394 unique substances
Refine to substances with less than 5 references (REF.CAPLUS<5)
=> L5 has 2159 unique substances
CAplus search strategy
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
28
Cross-over of L4 with 2159 unique substances
=> L5 has 503 references from all years
Restrict the answer to patent records only (P/DT)
=> L6 has 234 patent references from all years
Restrict to patents with a stronger chemistry focus using C07C
as IPC or CPC codes
=> L7 has 136 patent references from all years
Restrict to patents with a priority year after 2012
=> L8 has 18 patent references
Findings of the 18 patent family records retrieved
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
29
Answer Country Language Pub.year Pages All subst Vitam-D PPAK
1 CN Chinese 2016 27 37 4 Yes
2 CN Chinese 2016 25 47 13 Yes
3 WO English 2016 106 202 55 PDF+
4 CN Chinese 2016 13 4 1 Yes
5 CN Chinese 2016 5 3 1 Yes
6 CN Chinese 2015 21 9 2 Yes
7 CN Chinese 2015 14 9 4 Yes
8 CN Chinese 2015 9 4 1 Yes
9 WO German 2015 45 14 3 Yes
10 DE German 2015 22 14 3 Yes
11 CN Chinese 2014 14 16 1 Yes
12 CN Chinese 2015 12 7 1 Yes
13 US English 2015 18 5 3 Yes
14 WO Spanish 2015 75 141 29 Yes
15 US English 2015 21 18 3 Yes
16 WO English 2015 61 18 2 Yes
17 ES Spanish 2013 55 141 29 Yes
18 WO English 2013 50 30 3 Yes
The result set includes
three “double basic” pairs:
9+10, 14+17, 15+16
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
30
L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN
PatentPak PDF | PatentPak PDF+ | PatentPak Interactive
AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>>
DN 163:118806
TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation
method
IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang
PA Nanjing University of Science and Technology, Peop. Rep. China
SO Faming Zhuanli Shenqing, 14pp.
CODEN: CNXXEV
DT Patent
LA Chinese
FAN.CNT 1
PPPI
PATENT NO. KIND DATE LANGUAGE PatentPak
--------------- ---- -------- ---------- ------------------------
CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive
PI
PATENT NO. KIND DATE APPLICATION NO. DATE
--------------- ---- -------- --------------------- --------
CN 104693087 A 20150610 CN 2013-10664076 20131210 <--
PRAI CN 2013-10664076 20131210 <--
Display
Original
Full-text PDF
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
31
L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN
PatentPak PDF | PatentPak PDF+ | PatentPak Interactive
AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>>
DN 163:118806
TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation
method
IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang
PA Nanjing University of Science and Technology, Peop. Rep. China
SO Faming Zhuanli Shenqing, 14pp.
CODEN: CNXXEV
DT Patent
LA Chinese
FAN.CNT 1
PPPI
PATENT NO. KIND DATE LANGUAGE PatentPak
--------------- ---- -------- ---------- ------------------------
CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive
PI
PATENT NO. KIND DATE APPLICATION NO. DATE
--------------- ---- -------- --------------------- --------
CN 104693087 A 20150610 CN 2013-10664076 20131210 <--
PRAI CN 2013-10664076 20131210 <--
Original
Full-text PDF +
compound table
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
32
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
33
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
34
L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN
PatentPak PDF | PatentPak PDF+ | PatentPak Interactive
AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>>
DN 163:118806
TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation
method
IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang
PA Nanjing University of Science and Technology, Peop. Rep. China
SO Faming Zhuanli Shenqing, 14pp.
CODEN: CNXXEV
DT Patent
LA Chinese
FAN.CNT 1
PPPI
PATENT NO. KIND DATE LANGUAGE PatentPak
--------------- ---- -------- ---------- ------------------------
CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive
PI
PATENT NO. KIND DATE APPLICATION NO. DATE
--------------- ---- -------- --------------------- --------
CN 104693087 A 20150610 CN 2013-10664076 20131210 <--
PRAI CN 2013-10664076 20131210 <--
Interactive Viewer for
substance locations
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
35
Interactive link to
location of compound
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
36
Answer #3 has >600 substance locations, which can only be seen
in the PDF+; still very useful
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
37
Case study conclusions
CAS is a division of the American Chemical Society.
Copyright 2016 American Chemical Society. All rights reserved.
38
1. Fast identification of relevant patents, containing new compounds
2. Easy access to the patent document
3. Time savings when finding the compounds in a specific patent
(PatentPak PDF+ compound table)
4. Quickly and easily locate a specific compound in a patent with links in
the PatentPak Interactive Viewer
Overall conclusions
39
• Semantic technology has made great advances in classifying, mining and
extracting chemical content from text; however, it has significant limitations
• Human analysis is still necessary to find many of the key compound locations
• PatentPak in STN provides convenient links for patent attorneys and outside
council to facilitate their analysis work
• PatentPak in SciFinder is designed to provide a direct interactive session for
scientists to find relevant compounds and search them in SciFinder
• PatentPak provides significant time savings when analyzing novel vitamin D
metabolites disclosed in patents

More Related Content

What's hot

In grammars we trust: LeadMine, a knowledge driven solution
In grammars we trust: LeadMine, a knowledge driven solutionIn grammars we trust: LeadMine, a knowledge driven solution
In grammars we trust: LeadMine, a knowledge driven solutionNextMove Software
 
Challenges and successes in machine interpretation of Markush descriptions
Challenges and successes in machine interpretation of Markush descriptionsChallenges and successes in machine interpretation of Markush descriptions
Challenges and successes in machine interpretation of Markush descriptionsNextMove Software
 
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...Tackling the difficult areas of chemical entity extraction: Misspelt chemical...
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...dan2097
 
2020 scifinder-n manual (2020) english
2020 scifinder-n manual (2020) english2020 scifinder-n manual (2020) english
2020 scifinder-n manual (2020) englishPOSTECH Library
 
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future?
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future? ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future?
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future? Dr. Haxel Consult
 
ICIC 2017: New product presentations CAS
ICIC 2017: New product presentations CASICIC 2017: New product presentations CAS
ICIC 2017: New product presentations CASDr. Haxel Consult
 
Pharmaceutical industry best practices in lessons learned: ELN implementation...
Pharmaceutical industry best practices in lessons learned: ELN implementation...Pharmaceutical industry best practices in lessons learned: ELN implementation...
Pharmaceutical industry best practices in lessons learned: ELN implementation...NextMove Software
 
ICIC 2014 New Product Presentations ChemAxon
ICIC 2014 New Product Presentations ChemAxon ICIC 2014 New Product Presentations ChemAxon
ICIC 2014 New Product Presentations ChemAxon Dr. Haxel Consult
 
II-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping
II-SDV 2016 Aalt van de Kuilen - The Art of Patent LandscapingII-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping
II-SDV 2016 Aalt van de Kuilen - The Art of Patent LandscapingDr. Haxel Consult
 
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...NextMove Software
 
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...Dr. Haxel Consult
 

What's hot (15)

In grammars we trust: LeadMine, a knowledge driven solution
In grammars we trust: LeadMine, a knowledge driven solutionIn grammars we trust: LeadMine, a knowledge driven solution
In grammars we trust: LeadMine, a knowledge driven solution
 
Challenges and successes in machine interpretation of Markush descriptions
Challenges and successes in machine interpretation of Markush descriptionsChallenges and successes in machine interpretation of Markush descriptions
Challenges and successes in machine interpretation of Markush descriptions
 
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...Tackling the difficult areas of chemical entity extraction: Misspelt chemical...
Tackling the difficult areas of chemical entity extraction: Misspelt chemical...
 
2020 scifinder-n manual (2020) english
2020 scifinder-n manual (2020) english2020 scifinder-n manual (2020) english
2020 scifinder-n manual (2020) english
 
II-SDV 2016 Linguamatics
II-SDV 2016 LinguamaticsII-SDV 2016 Linguamatics
II-SDV 2016 Linguamatics
 
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future?
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future? ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future?
ICIC 2014 What Can We Learn from Our Past, that Equips Us for the Future?
 
ICIC 2017: New product presentations CAS
ICIC 2017: New product presentations CASICIC 2017: New product presentations CAS
ICIC 2017: New product presentations CAS
 
Pharmaceutical industry best practices in lessons learned: ELN implementation...
Pharmaceutical industry best practices in lessons learned: ELN implementation...Pharmaceutical industry best practices in lessons learned: ELN implementation...
Pharmaceutical industry best practices in lessons learned: ELN implementation...
 
WGC Presentation
WGC PresentationWGC Presentation
WGC Presentation
 
ICIC 2014 New Product Presentations ChemAxon
ICIC 2014 New Product Presentations ChemAxon ICIC 2014 New Product Presentations ChemAxon
ICIC 2014 New Product Presentations ChemAxon
 
II-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping
II-SDV 2016 Aalt van de Kuilen - The Art of Patent LandscapingII-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping
II-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping
 
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...
Chemical similarity using multi-terabyte graph databases: 68 billion nodes an...
 
Coming to terms to FAIR semantics
Coming to terms to FAIR semanticsComing to terms to FAIR semantics
Coming to terms to FAIR semantics
 
Cas 2
Cas 2Cas 2
Cas 2
 
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...
II-SDV 2016 Michael Iarrobino - Improving Text Mining Results with Access to ...
 

Viewers also liked

ICIC 2016: New Product Introduction Deep SEARCH 9
ICIC 2016: New Product Introduction Deep SEARCH 9ICIC 2016: New Product Introduction Deep SEARCH 9
ICIC 2016: New Product Introduction Deep SEARCH 9Dr. Haxel Consult
 
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...Dr. Haxel Consult
 
ICIC 2016: 20 Years is Not Enough
ICIC 2016: 20 Years is Not EnoughICIC 2016: 20 Years is Not Enough
ICIC 2016: 20 Years is Not EnoughDr. Haxel Consult
 
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...Dr. Haxel Consult
 
ICIC 2016: Patent Information - Looking beyond China
ICIC 2016: Patent Information - Looking beyond ChinaICIC 2016: Patent Information - Looking beyond China
ICIC 2016: Patent Information - Looking beyond ChinaDr. Haxel Consult
 
ICIC 2016: New Product Introduction LexisNexis
ICIC 2016: New Product Introduction LexisNexisICIC 2016: New Product Introduction LexisNexis
ICIC 2016: New Product Introduction LexisNexisDr. Haxel Consult
 
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...Dr. Haxel Consult
 

Viewers also liked (7)

ICIC 2016: New Product Introduction Deep SEARCH 9
ICIC 2016: New Product Introduction Deep SEARCH 9ICIC 2016: New Product Introduction Deep SEARCH 9
ICIC 2016: New Product Introduction Deep SEARCH 9
 
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...
ICIC 2016: Improving the Pharmacovigilance Literature Screening Process. How ...
 
ICIC 2016: 20 Years is Not Enough
ICIC 2016: 20 Years is Not EnoughICIC 2016: 20 Years is Not Enough
ICIC 2016: 20 Years is Not Enough
 
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...
ICIC 2016: Tutorial: Searching for Information – the Classical Way with Key W...
 
ICIC 2016: Patent Information - Looking beyond China
ICIC 2016: Patent Information - Looking beyond ChinaICIC 2016: Patent Information - Looking beyond China
ICIC 2016: Patent Information - Looking beyond China
 
ICIC 2016: New Product Introduction LexisNexis
ICIC 2016: New Product Introduction LexisNexisICIC 2016: New Product Introduction LexisNexis
ICIC 2016: New Product Introduction LexisNexis
 
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...
ICIC 2016: Universal Resource Access: Connecting Researchers to Scientific Co...
 

Similar to ICIC 2016: Mind the Gap: The novel benefits of human-curated substance locations for chemical patent analysis

New Product Introductions - CAS
New Product Introductions - CASNew Product Introductions - CAS
New Product Introductions - CASDr. Haxel Consult
 
II-PIC 2017: Why did I miss that Patent? How value added databases of STN he...
II-PIC 2017: Why did I miss that Patent? How value added databases of STN  he...II-PIC 2017: Why did I miss that Patent? How value added databases of STN  he...
II-PIC 2017: Why did I miss that Patent? How value added databases of STN he...Dr. Haxel Consult
 
Making the Old New Again - Modern Technical Provides Access to Historical Che...
Making the Old New Again - Modern Technical Provides Access to Historical Che...Making the Old New Again - Modern Technical Provides Access to Historical Che...
Making the Old New Again - Modern Technical Provides Access to Historical Che...Iconic Translation Machines
 
2020 sci finder-n manual (English)
2020 sci finder-n manual (English)2020 sci finder-n manual (English)
2020 sci finder-n manual (English)POSTECH Library
 
ICIC 2014 New Product Introduction CAS
ICIC 2014 New Product Introduction CASICIC 2014 New Product Introduction CAS
ICIC 2014 New Product Introduction CASDr. Haxel Consult
 
SciFinder Scholar
SciFinder ScholarSciFinder Scholar
SciFinder Scholarxqhiris
 
ICIC 2013 New Product Introductions CAS
ICIC 2013 New Product Introductions CASICIC 2013 New Product Introductions CAS
ICIC 2013 New Product Introductions CASDr. Haxel Consult
 
II-PIC 201: Product Presentation CAS / STN
II-PIC 201: Product Presentation CAS / STN II-PIC 201: Product Presentation CAS / STN
II-PIC 201: Product Presentation CAS / STN Dr. Haxel Consult
 
ICIC 2014 New Product Introductions FIZ Karlsruhe
ICIC 2014 New Product Introductions FIZ KarlsruheICIC 2014 New Product Introductions FIZ Karlsruhe
ICIC 2014 New Product Introductions FIZ KarlsruheDr. Haxel Consult
 
CAS: Transforming Discovery
CAS: Transforming DiscoveryCAS: Transforming Discovery
CAS: Transforming DiscoveryCAS
 
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATION
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATIONMAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATION
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATIONTigerGraph
 
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]NextMove Software
 
5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk
5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk
5th Meeting on U.S. Government Chemical Databases and Open Chemistry TalkMarkus Sitzmann
 
CINF 55: SureChEMBL: An open patent chemistry resource
CINF 55: SureChEMBL: An open patent chemistry resourceCINF 55: SureChEMBL: An open patent chemistry resource
CINF 55: SureChEMBL: An open patent chemistry resourceGeorge Papadatos
 
Freedom to design with high performing and sustainable materials for future g...
Freedom to design with high performing and sustainable materials for future g...Freedom to design with high performing and sustainable materials for future g...
Freedom to design with high performing and sustainable materials for future g...Stahl Holdings
 
SciFinder and its utility in Drug discovery
SciFinder and its utility in Drug discoverySciFinder and its utility in Drug discovery
SciFinder and its utility in Drug discoveryAlichy Sowmya
 

Similar to ICIC 2016: Mind the Gap: The novel benefits of human-curated substance locations for chemical patent analysis (20)

New Product Introductions - CAS
New Product Introductions - CASNew Product Introductions - CAS
New Product Introductions - CAS
 
II-PIC 2017: Why did I miss that Patent? How value added databases of STN he...
II-PIC 2017: Why did I miss that Patent? How value added databases of STN  he...II-PIC 2017: Why did I miss that Patent? How value added databases of STN  he...
II-PIC 2017: Why did I miss that Patent? How value added databases of STN he...
 
Making the Old New Again - Modern Technical Provides Access to Historical Che...
Making the Old New Again - Modern Technical Provides Access to Historical Che...Making the Old New Again - Modern Technical Provides Access to Historical Che...
Making the Old New Again - Modern Technical Provides Access to Historical Che...
 
2020 sci finder-n manual (English)
2020 sci finder-n manual (English)2020 sci finder-n manual (English)
2020 sci finder-n manual (English)
 
ICIC 2014 New Product Introduction CAS
ICIC 2014 New Product Introduction CASICIC 2014 New Product Introduction CAS
ICIC 2014 New Product Introduction CAS
 
Chemical abstracts ii
Chemical abstracts   iiChemical abstracts   ii
Chemical abstracts ii
 
SciFinder Scholar
SciFinder ScholarSciFinder Scholar
SciFinder Scholar
 
Chemical abstract
Chemical abstractChemical abstract
Chemical abstract
 
ICIC 2013 New Product Introductions CAS
ICIC 2013 New Product Introductions CASICIC 2013 New Product Introductions CAS
ICIC 2013 New Product Introductions CAS
 
II-PIC 201: Product Presentation CAS / STN
II-PIC 201: Product Presentation CAS / STN II-PIC 201: Product Presentation CAS / STN
II-PIC 201: Product Presentation CAS / STN
 
ICIC 2014 New Product Introductions FIZ Karlsruhe
ICIC 2014 New Product Introductions FIZ KarlsruheICIC 2014 New Product Introductions FIZ Karlsruhe
ICIC 2014 New Product Introductions FIZ Karlsruhe
 
CAS: Transforming Discovery
CAS: Transforming DiscoveryCAS: Transforming Discovery
CAS: Transforming Discovery
 
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATION
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATIONMAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATION
MAXIMIZING THE VALUE OF SCIENTIFIC INFORMATION TO ACCELERATE INNOVATION
 
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]
RDKit: Six Not-So-Easy Pieces [RDKit UGM 2016]
 
Accessing information for Per- & Polyfluoroalkyl Substances using the US EPA ...
Accessing information for Per- & Polyfluoroalkyl Substances using the US EPA ...Accessing information for Per- & Polyfluoroalkyl Substances using the US EPA ...
Accessing information for Per- & Polyfluoroalkyl Substances using the US EPA ...
 
What is a PFAS?..and the challenges associated with defining them
What is a PFAS?..and the challenges associated with defining themWhat is a PFAS?..and the challenges associated with defining them
What is a PFAS?..and the challenges associated with defining them
 
5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk
5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk
5th Meeting on U.S. Government Chemical Databases and Open Chemistry Talk
 
CINF 55: SureChEMBL: An open patent chemistry resource
CINF 55: SureChEMBL: An open patent chemistry resourceCINF 55: SureChEMBL: An open patent chemistry resource
CINF 55: SureChEMBL: An open patent chemistry resource
 
Freedom to design with high performing and sustainable materials for future g...
Freedom to design with high performing and sustainable materials for future g...Freedom to design with high performing and sustainable materials for future g...
Freedom to design with high performing and sustainable materials for future g...
 
SciFinder and its utility in Drug discovery
SciFinder and its utility in Drug discoverySciFinder and its utility in Drug discovery
SciFinder and its utility in Drug discovery
 

More from Dr. Haxel Consult

AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering ManagementAI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering ManagementDr. Haxel Consult
 
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...Dr. Haxel Consult
 
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...Dr. Haxel Consult
 
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...Dr. Haxel Consult
 
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...Dr. Haxel Consult
 
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...Dr. Haxel Consult
 
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...Dr. Haxel Consult
 
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...Dr. Haxel Consult
 
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...Dr. Haxel Consult
 
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...Dr. Haxel Consult
 
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...Dr. Haxel Consult
 
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...Dr. Haxel Consult
 
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...Dr. Haxel Consult
 
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...Dr. Haxel Consult
 
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...Dr. Haxel Consult
 
AI-SDV 2022: Copyright Clearance Center
AI-SDV 2022: Copyright Clearance CenterAI-SDV 2022: Copyright Clearance Center
AI-SDV 2022: Copyright Clearance CenterDr. Haxel Consult
 
AI-SDV 2022: New Product Introductions: CENTREDOC
AI-SDV 2022: New Product Introductions: CENTREDOCAI-SDV 2022: New Product Introductions: CENTREDOC
AI-SDV 2022: New Product Introductions: CENTREDOCDr. Haxel Consult
 
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...Dr. Haxel Consult
 
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...Dr. Haxel Consult
 

More from Dr. Haxel Consult (20)

AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering ManagementAI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
 
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
 
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
 
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
 
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
 
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
 
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
 
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
 
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
 
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
 
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
 
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
 
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
 
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
 
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
 
AI-SDV 2022: Copyright Clearance Center
AI-SDV 2022: Copyright Clearance CenterAI-SDV 2022: Copyright Clearance Center
AI-SDV 2022: Copyright Clearance Center
 
AI-SDV 2022: Lighthouse IP
AI-SDV 2022: Lighthouse IPAI-SDV 2022: Lighthouse IP
AI-SDV 2022: Lighthouse IP
 
AI-SDV 2022: New Product Introductions: CENTREDOC
AI-SDV 2022: New Product Introductions: CENTREDOCAI-SDV 2022: New Product Introductions: CENTREDOC
AI-SDV 2022: New Product Introductions: CENTREDOC
 
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
 
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
 

Recently uploaded

AlbaniaDreamin24 - How to easily use an API with Flows
AlbaniaDreamin24 - How to easily use an API with FlowsAlbaniaDreamin24 - How to easily use an API with Flows
AlbaniaDreamin24 - How to easily use an API with FlowsThierry TROUIN ☁
 
Moving Beyond Twitter/X and Facebook - Social Media for local news providers
Moving Beyond Twitter/X and Facebook - Social Media for local news providersMoving Beyond Twitter/X and Facebook - Social Media for local news providers
Moving Beyond Twitter/X and Facebook - Social Media for local news providersDamian Radcliffe
 
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark Web
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark WebGDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark Web
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark WebJames Anderson
 
Hot Service (+9316020077 ) Goa Call Girls Real Photos and Genuine Service
Hot Service (+9316020077 ) Goa  Call Girls Real Photos and Genuine ServiceHot Service (+9316020077 ) Goa  Call Girls Real Photos and Genuine Service
Hot Service (+9316020077 ) Goa Call Girls Real Photos and Genuine Servicesexy call girls service in goa
 
Networking in the Penumbra presented by Geoff Huston at NZNOG
Networking in the Penumbra presented by Geoff Huston at NZNOGNetworking in the Penumbra presented by Geoff Huston at NZNOG
Networking in the Penumbra presented by Geoff Huston at NZNOGAPNIC
 
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...Sheetaleventcompany
 
Russian Call Girls in Kolkata Samaira 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Samaira 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Samaira 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Samaira 🤌 8250192130 🚀 Vip Call Girls Kolkataanamikaraghav4
 
Russian Call Girls in Kolkata Ishita 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Ishita 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Ishita 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Ishita 🤌 8250192130 🚀 Vip Call Girls Kolkataanamikaraghav4
 
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝soniya singh
 
Low Rate Call Girls Kolkata Avani 🤌 8250192130 🚀 Vip Call Girls Kolkata
Low Rate Call Girls Kolkata Avani 🤌  8250192130 🚀 Vip Call Girls KolkataLow Rate Call Girls Kolkata Avani 🤌  8250192130 🚀 Vip Call Girls Kolkata
Low Rate Call Girls Kolkata Avani 🤌 8250192130 🚀 Vip Call Girls Kolkataanamikaraghav4
 
VIP Kolkata Call Girl Kestopur 👉 8250192130 Available With Room
VIP Kolkata Call Girl Kestopur 👉 8250192130  Available With RoomVIP Kolkata Call Girl Kestopur 👉 8250192130  Available With Room
VIP Kolkata Call Girl Kestopur 👉 8250192130 Available With Roomdivyansh0kumar0
 
On Starlink, presented by Geoff Huston at NZNOG 2024
On Starlink, presented by Geoff Huston at NZNOG 2024On Starlink, presented by Geoff Huston at NZNOG 2024
On Starlink, presented by Geoff Huston at NZNOG 2024APNIC
 
Russian Call girls in Dubai +971563133746 Dubai Call girls
Russian  Call girls in Dubai +971563133746 Dubai  Call girlsRussian  Call girls in Dubai +971563133746 Dubai  Call girls
Russian Call girls in Dubai +971563133746 Dubai Call girlsstephieert
 
Gram Darshan PPT cyber rural in villages of india
Gram Darshan PPT cyber rural  in villages of indiaGram Darshan PPT cyber rural  in villages of india
Gram Darshan PPT cyber rural in villages of indiaimessage0108
 
VIP Call Girls Kolkata Ananya 🤌 8250192130 🚀 Vip Call Girls Kolkata
VIP Call Girls Kolkata Ananya 🤌  8250192130 🚀 Vip Call Girls KolkataVIP Call Girls Kolkata Ananya 🤌  8250192130 🚀 Vip Call Girls Kolkata
VIP Call Girls Kolkata Ananya 🤌 8250192130 🚀 Vip Call Girls Kolkataanamikaraghav4
 
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝soniya singh
 
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024APNIC
 
Challengers I Told Ya ShirtChallengers I Told Ya Shirt
Challengers I Told Ya ShirtChallengers I Told Ya ShirtChallengers I Told Ya ShirtChallengers I Told Ya Shirt
Challengers I Told Ya ShirtChallengers I Told Ya Shirtrahman018755
 
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...aditipandeya
 

Recently uploaded (20)

AlbaniaDreamin24 - How to easily use an API with Flows
AlbaniaDreamin24 - How to easily use an API with FlowsAlbaniaDreamin24 - How to easily use an API with Flows
AlbaniaDreamin24 - How to easily use an API with Flows
 
Moving Beyond Twitter/X and Facebook - Social Media for local news providers
Moving Beyond Twitter/X and Facebook - Social Media for local news providersMoving Beyond Twitter/X and Facebook - Social Media for local news providers
Moving Beyond Twitter/X and Facebook - Social Media for local news providers
 
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark Web
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark WebGDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark Web
GDG Cloud Southlake 32: Kyle Hettinger: Demystifying the Dark Web
 
Hot Service (+9316020077 ) Goa Call Girls Real Photos and Genuine Service
Hot Service (+9316020077 ) Goa  Call Girls Real Photos and Genuine ServiceHot Service (+9316020077 ) Goa  Call Girls Real Photos and Genuine Service
Hot Service (+9316020077 ) Goa Call Girls Real Photos and Genuine Service
 
Networking in the Penumbra presented by Geoff Huston at NZNOG
Networking in the Penumbra presented by Geoff Huston at NZNOGNetworking in the Penumbra presented by Geoff Huston at NZNOG
Networking in the Penumbra presented by Geoff Huston at NZNOG
 
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...
Call Girls Service Chandigarh Lucky ❤️ 7710465962 Independent Call Girls In C...
 
Russian Call Girls in Kolkata Samaira 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Samaira 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Samaira 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Samaira 🤌 8250192130 🚀 Vip Call Girls Kolkata
 
Russian Call Girls in Kolkata Ishita 🤌 8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Ishita 🤌  8250192130 🚀 Vip Call Girls KolkataRussian Call Girls in Kolkata Ishita 🤌  8250192130 🚀 Vip Call Girls Kolkata
Russian Call Girls in Kolkata Ishita 🤌 8250192130 🚀 Vip Call Girls Kolkata
 
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Defence Colony Delhi 💯Call Us 🔝8264348440🔝
 
Low Rate Call Girls Kolkata Avani 🤌 8250192130 🚀 Vip Call Girls Kolkata
Low Rate Call Girls Kolkata Avani 🤌  8250192130 🚀 Vip Call Girls KolkataLow Rate Call Girls Kolkata Avani 🤌  8250192130 🚀 Vip Call Girls Kolkata
Low Rate Call Girls Kolkata Avani 🤌 8250192130 🚀 Vip Call Girls Kolkata
 
VIP Kolkata Call Girl Kestopur 👉 8250192130 Available With Room
VIP Kolkata Call Girl Kestopur 👉 8250192130  Available With RoomVIP Kolkata Call Girl Kestopur 👉 8250192130  Available With Room
VIP Kolkata Call Girl Kestopur 👉 8250192130 Available With Room
 
On Starlink, presented by Geoff Huston at NZNOG 2024
On Starlink, presented by Geoff Huston at NZNOG 2024On Starlink, presented by Geoff Huston at NZNOG 2024
On Starlink, presented by Geoff Huston at NZNOG 2024
 
Russian Call girls in Dubai +971563133746 Dubai Call girls
Russian  Call girls in Dubai +971563133746 Dubai  Call girlsRussian  Call girls in Dubai +971563133746 Dubai  Call girls
Russian Call girls in Dubai +971563133746 Dubai Call girls
 
Gram Darshan PPT cyber rural in villages of india
Gram Darshan PPT cyber rural  in villages of indiaGram Darshan PPT cyber rural  in villages of india
Gram Darshan PPT cyber rural in villages of india
 
VIP Call Girls Kolkata Ananya 🤌 8250192130 🚀 Vip Call Girls Kolkata
VIP Call Girls Kolkata Ananya 🤌  8250192130 🚀 Vip Call Girls KolkataVIP Call Girls Kolkata Ananya 🤌  8250192130 🚀 Vip Call Girls Kolkata
VIP Call Girls Kolkata Ananya 🤌 8250192130 🚀 Vip Call Girls Kolkata
 
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝
Call Girls In Saket Delhi 💯Call Us 🔝8264348440🔝
 
Call Girls In South Ex 📱 9999965857 🤩 Delhi 🫦 HOT AND SEXY VVIP 🍎 SERVICE
Call Girls In South Ex 📱  9999965857  🤩 Delhi 🫦 HOT AND SEXY VVIP 🍎 SERVICECall Girls In South Ex 📱  9999965857  🤩 Delhi 🫦 HOT AND SEXY VVIP 🍎 SERVICE
Call Girls In South Ex 📱 9999965857 🤩 Delhi 🫦 HOT AND SEXY VVIP 🍎 SERVICE
 
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024
DDoS In Oceania and the Pacific, presented by Dave Phelan at NZNOG 2024
 
Challengers I Told Ya ShirtChallengers I Told Ya Shirt
Challengers I Told Ya ShirtChallengers I Told Ya ShirtChallengers I Told Ya ShirtChallengers I Told Ya Shirt
Challengers I Told Ya ShirtChallengers I Told Ya Shirt
 
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...
VIP 7001035870 Find & Meet Hyderabad Call Girls Dilsukhnagar high-profile Cal...
 

ICIC 2016: Mind the Gap: The novel benefits of human-curated substance locations for chemical patent analysis

  • 1. Mind the Gap: The novel benefits of human-curated substance locations for chemical patent analysis Aalt van de Kuilen, Patent Information Services BV, NL Paul Peters, CAS/ACS International, DE ICIC 2016 October 18, 2016 Heidelberg, Germany CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved.
  • 2. Finding the relevant section(s) within the full-text of chemical patents is often a time-consuming challenge • They are not always as easy to track down as we might expect • They can be long and “artfully” written • The chemistry is often obscured within complex names, tables, text, graphics, etc. Sometimes it seems like the search may be complete, but the hunt is just beginning!
  • 3. Even with a precise chemical patent search, reviewing the results can quickly become overwhelming => FILE CAPLUS => S L3 L4 1014 L3 => S L4 AND (BET OR BROMODOMAIN) AND P/DT L5 35 L4 AND (BET OR BROMODOMAIN) AND P/DT A query combining structure and text terms yields 35 patent publications. That shouldn’t be too bad, right? Only 5,498 pages to review. 479 pages 428 pages 321 pages 277 pages 263 pages 261 pages 240 pages 229 pages CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 3
  • 4. Technology can help, but algorithmic extraction of chemistry in patents has significant limitations 4 Conclusion: Algorithmic extraction successfully found only 50-60% of the chemical structures in patents based on a limited sample, and they were often the least interesting ones.
  • 5. Algorithms miss key substances for a myriad of reasons • Ambiguous naming • Markush representations • No name – Explanatory text or images, rather than as chemical names or structures • Stereochemistry issues • Multi-component substances CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 5 Normally PSS is used for poly(styrenesulfonic acid), but here it represents the aqueous dispersion, which CAS previously identified as poly(1-vinyl-2-pyrolidone) Normally PSS is used for poly(styrenesulfonic acid), but here it represents the aqueous dispersion, which CAS previously identified as poly(1-vinyl-2-pyrolidone)
  • 6. PatentPakTM addresses this gap by combining human curation with new technology to expedite chemical patent analysis • Rapidly track down the specific location of hard-to-find chemical information in patents with interactive links to key substances – Benefit from the indexing efforts of hundreds of CAS scientists • Instantly and securely access patent PDFs from major patent offices – No more wasting time navigating multiple web sites • Locate patents in languages you know with CAplusSM global patent family coverage – Save time and translation costs • Conveniently share these benefits with other IP stakeholders – Even if they do not use STN® or SciFinder® CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 6
  • 7. PatentPak is built on the indexing effort of the scientific analysts that create CAS REGISTRYSM • Scientists review each patent and identify new substances for CAS REGISTRY inclusion • They mark the specific location of substances in the text during analysis • Algorithmic processing with human intervention allows previously registered substances to be located and annotated in backfile documents CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 7 “I analyzed the chemistry in this entire patent to save you time.” Keiko Sugimoto Sr. Scientific Information Analyst, CAS
  • 8. CAS is a division of the American Chemical Society. Copyright 2015 American Chemical Society. All rights reserved. 8 PatentPak supplements CAplus records with direct pointers to the chemistry of interest Bibliographic information (partially shown) Hit substance indexing including roles Hit structure display from CAS REGISTRY PatentPak links for each hit compound PatentPak links for document
  • 9. CAS is a division of the American Chemical Society. Copyright 2015 American Chemical Society. All rights reserved. It is possible to access the original PDF…
  • 10. CAS is a division of the American Chemical Society. Copyright 2015 American Chemical Society. All rights reserved. … the annotated PDF (PDF +) …
  • 11. CAS is a division of the American Chemical Society. Copyright 2015 American Chemical Society. All rights reserved. … or review the patent using the interactive viewer
  • 12. PatentPak links are available in transcripts, tables, and reports and accessible without an STN login ID to support workflow CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 12 No STN login ID required
  • 13. PatentPak is also available in SciFinder CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved.
  • 14. New CAplus records from 31 countries are annotated as part of the normal workflow, and the backfile is growing rapidly CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 14
  • 15. The current backfile project will extend historical PatentPak coverage of key offices by more than a decade by year end ACS / Proprietary and Confidential / Do Not Distribute 15
  • 16. 16 PatentPak example US5739376: Backfile operation for one of the first patents on Fullerene derivatives (Hoechst AG) • Originally a German basic patent from 1994 but substance locations have been added to the US equivalent from 1998 • Fullerene structures were symbolized by simple rings
  • 17. PatentPak example WO2016087417: substances identified in a Markush table (Bayer CropScience AG) • Only a few selected substances in this patent are fully identified by name or structure • The vast majority of substances are indexed by assembling Markush tables
  • 18. PatentPak example WO9851681: Substance identified as “oily product” (Sanofi) • This particular substance is only identified as “oily product” • CAS analyst indexing from the chemistry
  • 19. PatentPak example WO2016120821: Find substances that cannot be identified by algorithm or structure extraction (Novartis AG) • Substances in formula VII are claimed by Markush: LG = “leaving group” • Analyst marked four specific compounds which are defined later in the claims - only a human can process claims like this!
  • 20. PatentPak example DE2013016487: Multiple location markings (University of Heidelberg) • Analyst has marked multiple locations - claims and synthetic example
  • 21. 21 PatentPak example WO2016001362: Find substances inferred by their starting material after enzymatic conversion (BASF) • Starting materials (substrates) identified by structure on page 51 • Products not listed but inferred in a table on page 27
  • 22. PatentPak example WO2015018558: Inorganic chemistry can be equally challenging (PI Ceramic GmbH)
  • 23. PatentPak example WO2014184355: Find assembled Markush tables (Dr. August Wolff GmbH & Co Arzeneimittel) • 9.5 pages of "table Markush“ structures - a core structure shown at the top, with fragments • The complete structure is assembled in a table at the back of PDF+ document, including page numbers, CAS RN, chemical name, and structures
  • 24. Case study on new Vitamin D metabolites CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 24 How many patent families have been filed since 2013 on new Vitamin D metabolites? Find the answer by with
  • 25. Stepwise approach CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 25 1. Structure search in Registry 2. Remove old compounds 3. Keep compounds with low reference count in CAplus 4. Transfer to Chemical Abstracts 5. Limit to new compounds and published in patents 6. Display records which have a PatentPak record PatentPak PDF| PatentPak PDF+ | PatentPak Interactive
  • 26. Structure CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 26 Q CH 2 CH 3 Ak Broad definition of Vitamin D skeleton All rings are isolated and double bonds are mandatory
  • 27. CAS REGISTRY search CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 27 FILE 'REGISTRY‘ ENTERED ON 22 SEP 2016 STRUCTURE UPLOADED => L3 has 6806 unique substances in Registry Refine to compounds registered since 2001 (ED>2000) => L4 has 2394 unique substances Refine to substances with less than 5 references (REF.CAPLUS<5) => L5 has 2159 unique substances
  • 28. CAplus search strategy CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 28 Cross-over of L4 with 2159 unique substances => L5 has 503 references from all years Restrict the answer to patent records only (P/DT) => L6 has 234 patent references from all years Restrict to patents with a stronger chemistry focus using C07C as IPC or CPC codes => L7 has 136 patent references from all years Restrict to patents with a priority year after 2012 => L8 has 18 patent references
  • 29. Findings of the 18 patent family records retrieved CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 29 Answer Country Language Pub.year Pages All subst Vitam-D PPAK 1 CN Chinese 2016 27 37 4 Yes 2 CN Chinese 2016 25 47 13 Yes 3 WO English 2016 106 202 55 PDF+ 4 CN Chinese 2016 13 4 1 Yes 5 CN Chinese 2016 5 3 1 Yes 6 CN Chinese 2015 21 9 2 Yes 7 CN Chinese 2015 14 9 4 Yes 8 CN Chinese 2015 9 4 1 Yes 9 WO German 2015 45 14 3 Yes 10 DE German 2015 22 14 3 Yes 11 CN Chinese 2014 14 16 1 Yes 12 CN Chinese 2015 12 7 1 Yes 13 US English 2015 18 5 3 Yes 14 WO Spanish 2015 75 141 29 Yes 15 US English 2015 21 18 3 Yes 16 WO English 2015 61 18 2 Yes 17 ES Spanish 2013 55 141 29 Yes 18 WO English 2013 50 30 3 Yes The result set includes three “double basic” pairs: 9+10, 14+17, 15+16
  • 30. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 30 L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN PatentPak PDF | PatentPak PDF+ | PatentPak Interactive AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>> DN 163:118806 TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation method IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang PA Nanjing University of Science and Technology, Peop. Rep. China SO Faming Zhuanli Shenqing, 14pp. CODEN: CNXXEV DT Patent LA Chinese FAN.CNT 1 PPPI PATENT NO. KIND DATE LANGUAGE PatentPak --------------- ---- -------- ---------- ------------------------ CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive PI PATENT NO. KIND DATE APPLICATION NO. DATE --------------- ---- -------- --------------------- -------- CN 104693087 A 20150610 CN 2013-10664076 20131210 <-- PRAI CN 2013-10664076 20131210 <-- Display Original Full-text PDF
  • 31. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 31 L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN PatentPak PDF | PatentPak PDF+ | PatentPak Interactive AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>> DN 163:118806 TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation method IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang PA Nanjing University of Science and Technology, Peop. Rep. China SO Faming Zhuanli Shenqing, 14pp. CODEN: CNXXEV DT Patent LA Chinese FAN.CNT 1 PPPI PATENT NO. KIND DATE LANGUAGE PatentPak --------------- ---- -------- ---------- ------------------------ CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive PI PATENT NO. KIND DATE APPLICATION NO. DATE --------------- ---- -------- --------------------- -------- CN 104693087 A 20150610 CN 2013-10664076 20131210 <-- PRAI CN 2013-10664076 20131210 <-- Original Full-text PDF + compound table
  • 32. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 32
  • 33. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 33
  • 34. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 34 L16 ANSWER 7 OF 18 CAPLUS COPYRIGHT 2016 ACS on STN PatentPak PDF | PatentPak PDF+ | PatentPak Interactive AN 2015:979679 CAPLUS Full-text<<LOGINID:ssscas83ppp:20160907>> DN 163:118806 TI 24,28-Olefine-1-hydroxy-vitamin D derivatives and preparation method IN Fang, Zhijie; Guo, Wei; Liu, Yanan; Li, Hongliang PA Nanjing University of Science and Technology, Peop. Rep. China SO Faming Zhuanli Shenqing, 14pp. CODEN: CNXXEV DT Patent LA Chinese FAN.CNT 1 PPPI PATENT NO. KIND DATE LANGUAGE PatentPak --------------- ---- -------- ---------- ------------------------ CN 104693087 A 20150610 Chinese PDF | PDF+ | Interactive PI PATENT NO. KIND DATE APPLICATION NO. DATE --------------- ---- -------- --------------------- -------- CN 104693087 A 20150610 CN 2013-10664076 20131210 <-- PRAI CN 2013-10664076 20131210 <-- Interactive Viewer for substance locations
  • 35. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 35 Interactive link to location of compound
  • 36. CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 36
  • 37. Answer #3 has >600 substance locations, which can only be seen in the PDF+; still very useful CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 37
  • 38. Case study conclusions CAS is a division of the American Chemical Society. Copyright 2016 American Chemical Society. All rights reserved. 38 1. Fast identification of relevant patents, containing new compounds 2. Easy access to the patent document 3. Time savings when finding the compounds in a specific patent (PatentPak PDF+ compound table) 4. Quickly and easily locate a specific compound in a patent with links in the PatentPak Interactive Viewer
  • 39. Overall conclusions 39 • Semantic technology has made great advances in classifying, mining and extracting chemical content from text; however, it has significant limitations • Human analysis is still necessary to find many of the key compound locations • PatentPak in STN provides convenient links for patent attorneys and outside council to facilitate their analysis work • PatentPak in SciFinder is designed to provide a direct interactive session for scientists to find relevant compounds and search them in SciFinder • PatentPak provides significant time savings when analyzing novel vitamin D metabolites disclosed in patents