Prior art searches: Introduction Massimo Barbieri

1. Prior art searches: Introduction Massimo Barbieri (Technology Transfer Office) – Politecnico di Milano E-mail: massimo.barbieri@polimi.it

2. Index Patent information: a competitive advantage Tools and methodologies for novelty and inventive step evaluation

3. Introduction (1) • patent documentalist • patent attorney (?) • patent examiner (EPO, USPTO, …, UIBM?, etc) • “In a small team, all members need broad technical expertise” • Sources • scientific journals (World Patent Information) • EPO guidelines • EPO training courses (also online) • training with experts • WON seminars (http://www.won-nl.org/2008/public/en/home.shtml)

4. Introduction (2) When are patent searches carried out? Filing Before thesis Patent publication IT PCT Internal Legal steps “Istruttoria” 12 months 12 months 6 months State of the art search Patentability search Patentability search Patentability search Monitoring When stop a search ? • the probability of discovering others relevant documents is very low compared to the effort needed or; • documents are discovered which doubtlessly demonstrate a violation of patentability requirements

5. Introduction (3) • First questions for the inventors: • type of invention = accurate protection • detailed description of invention • advantages (compared to state of the art) • list of keywords

6. The “Patent space” The technological field is defined by one or more IPC codes No restriction with respect to time or country of publication Drawback: only classified documents are found The temporal dimension of the Patent Space is characterized by the Publication Week of a patent document. Source: B. Wicenec – Searching the patent space – World Patent Information (2008), vol. 30, pages 153 - 155

7. Types of patent searches Main types of patent searches: - patentability, (b) validity and (c) state-of-the-art: high coverage of information (patents + NPL) (b) Limit the search by date (c) Statistical analysis + link to full texts + high level of completeness - Freedom degrees of operation: national source of information + claims + legal status Source: P. Foglia – Patentability search strategies and the reformed IPC: A patent office perspective – World Patent Information (2007), vol. 29, pages 33 - 53

8. Quality of patent information (1) • The search quality (patent information) depends of: • increase number of patent “pending” • increase number of “filings” (above all from Asia) and dimensions (number of pages and claims) • quality of data provided by applicants • accuracy of data loaded in databases • An examiner may improve quality of patent information: • by amending title pr abstract • adding a drawing in the front page • classifying correctly an invention • decreasing backlog [using work done by others and improving efficiency of granting process]

9. Quality of patent information (2) Patent information quality changes during the patent lifecycle [both metadata (title, classification …) both full text] Source: D. Bonino et al. – Review of the state-of-the-art in patent information and forthcoming evolutions in intelligent patent informatics – World Patent Information (2010), vol. 32, page 31

10. Patent information (1) • The “Patent information” is a term that involve: • within a patent • about patent or group of patents • Patent literature is a awesome source of technical and strategic information and represents a necessary complement to the traditional technical literature • Patent information can be: • explicit (i.e. title, inventor, summary,…) • implicit (more difficult to extract from patent documents but much more valuable to the innovation process; i.e. number of patents owned by the same applicant, the quality of patent portfolio, industry trends and so forth)

11. Patent information (2) • Why is it important to know patent literature? • to avoid reinventing what is already existing (a huge amount of intellectual activity is wasted because of the duplication of the research and design for inventions already available and published in the patent literature) • to be forewarned about the risk of accidentally infringing someone else’s patent; • if a search draws a blank and it appears that no-one else has patent protection, this fact will help a patent attorney in the process of drafting your own application

12. Patent information (3) • The usefulness of patents as technical information decreases for the following reasons: • the availability (completeness) of data; • how to retrieve patent information; • fueled by globalization, volume of patent information is growing dramatically (China, Japan, Korea and Taiwan) • increasing complexity of patent applications [too many claims and pages of description]

13. Patent information (4) • a complete patent database doesn’t exist: [ex. Patentscope: Japanese PCT patent collection is not complete, while Chinese PCT patent applications are not available at all; Russian-language WO texts are available from the beginning of the system in 1978 until 1997, but not for recent years] • “full text” search: not always available • the available full text must be searchable and not only displayable • are automatic translators efficient?

14. Patent sections (1) • first page: bibliographic information + summary • description • claims • drawings • Specification • technical field of the invention • state of the art (definition of the technical problem) • summary (advantages of the invention) • description of drawings • detailed description • working examples

15. Bibliographic information contained in the first page (1)

16. Bibliographic information (2)

17. Bibliographic information (3)

18. Search report (1)

19. Search report (2) Source: D. Harhoff et al. – European Patent citations – How to count and how to interpret them? – EPIP Workshop (2004)

20. Search report (3)

21. Search report (4) Patent family members

22. Patent kind codes • A1: publication with search report (ISR) • A2: publication without ISR • A3: publication of the front page + ISR • A4: further publication of amended claims • A8: corrected title page of an EP-a Document • A9: complete reprint of an EP-a Document • B1: patent granted • B2: patent granted after opposition • B3: patent granted with limitations

23. Patent family Source: E. Simmons – “Black sheep” in the patent family, “World Patent Information”, 31 (2009), p. 11 - 18

24. Searching procedures (1) Choice of database The choice of database depends on the type of information to search: for instance, the complete search of chemical compounds or “Markush” structures is only possible with professional tools (Dialog, STN, Questel - Orbit) • Coverage • timeliness • data

25. Searching procedures (2) • Searching for novelty can be difficult, because patent are legal documents and not necessarily written for ease of searching; they are drafted to be defended in court. • A patent search can be conducted in two ways: • by words (intuitive but subjective) • by classification • understand the invention: find out essential features • keywords: identify a group of words (and synonyms) • classification: select one or more classification codes corresponding to the invention • databases

26. Searching procedures (3) • There are several reasons why words may be insufficient when doing a search in patent documents: • terminology used(the language used is a mixture between legal and technical terms (jargon); i.e. transistor  “amplifying means”; electromagnetic shield  “means for reducing electromagnetic radiation”) • multilingual synonyms • incomplete databases(there may be little or no text to search; for instance the USPTO database provides access to US patents since 1790 but has no text at all prior to 1976!) • A large percentage of all patent documents contain non-word information in the form of: • technical drawings • chemical or mathematical formulae • electric circuit diagram • genetic sequences

27. Keywords searching (1) Source: Starešinič et al. – Patent Informatics – the issue of relevance in full-text patent document searches – Online Information Review (2009), vol. 33 No. 1, pages 157 - 172 Non-adequate terminology can be one of the main obstacles to obtain relevant searches (above all in emerging technical fields) Ex. Patent analysis Search query: “Patent processing NOT medicine NOT biology NOT chemistry” 586 patents IPC analysis: most documents are classified into sections A, B and C (and not G) Full text analysis: only 28 documents are relevant (5%) The word “processing” is often used as a common term in chemical and metallurgical technology, while the word “patent” is mentioned in the state-of-art section of patent documents. New search: “Patent analysis”  139 patents (75% of patent documents are relevant) IPC analysis: 81% of these documents are classified into section G

28. Keywords searching (2) Non-adequate terminology is one of the main obstacles to relevant searches, especially if well-defined keywords are non-existent . Terminology problems may also occur with researchers who use English as their second language New terms in newly emerging fields sometimes occur for the first time in patent documents A good test of adequacy of terminology is IPC classification. If a large proportion of patent documents are classified under IPC sections outside the user’s interest, this indicates that the search profile was not well chosen and that the search should be repeated with better search terms.

29. Classification search (1) • Why classification? • Advantages • classifications provide access to concepts rather than words. They enable a single inventive concept to be represented concisely and unambiguously, and the enable complex concepts to be searched in circumstances where single words or phrases don’t lend themselves to efficient retrieval. • classifications are language-independent • Drawbacks • classification is not a panacea: sometimes classes are defined in a too specific manner Generally the best search strategies require a combination of independent mechanisms, such a s free-text plus classifications Source: S. Adams – Comparing the IPC and the US classification systems for the patent searcher – World Patent Information (2001), vol. 23, pages 15 – 23

30. Classification Groups number IPC 70.000 ECLA 134.000 JPO: F-terms 340.000 JPO: FI 190.000 Classification search (2) • Classification schemes may be used in two manner: • when classification perfectly matches the inventive concepts (subgroup level) • in parallel with other systems (subclass level ) • Examples: • a single term may reflect a complex concept (A61K 31/595: “medicinal preparations containing a mixture of vitamin A and D”) • RAM + H01L (integrated circuits) [if F02K (ram-jet)]

31. Classification searching (3) Limits on the use of classification codes A61K31/43 (medicinal preparations containing further heterocyclic ring; e.g. penicillin C07D 499/00 (heterocyclic compounds, e.g. penicillin) The search in only one of the two classification codes don’t allow to obtain a full information. USPC (430 classes 140.000 subclasses) only for US patents FI and F-terms only for JP patents

32. IPC vs. ECLA (1) The technical content of patent documents is classified in accordance with the International Patent Classification (IPC). The publishing office assigns an IPC symbol valid at the time of publication of the patent application. The complete IPC can be found on the website of the World Intellectual Property Organization (WIPO ). The classification symbol is made up of a letter denoting the IPC section (e.g. A), followed by a number (two digits) denoting the IPC class (e.g. A63), still followed by a letter denoting the IPC subclass (e.g. A63B). A number (variable, 1-3 digits) denotes the IPC main group (e.g. A63B49), a forward slash "/", and a number (variable, 1-3 digits) denotes the IPC subgroup (e.g. A63B49/02). Source: esp@cenet

33. IPC vs. ECLA (2) The ECLA classification system is an extension of the International Patent Classification (IPC). It is however more precise, having twice as many entries (ECLA: 140 000; IPC: 70 000). EPO examiners use it to classify patent documents and thus facilitate their prior-art searches. ECLA is revised continuously, and the documents are then reclassified accordingly. ECLA usually follows the current IPC; up to IPC subgroup level, the ECLA and IPC classification symbols are in most cases identical. Optionally, the ECLA classification scheme may be further subdivided beyond IPC level by ECLA subgroups represented by a letter which may in turn be followed by a digit and a letter (e.g. B65D81/20B2A). Source: esp@cenet

34. IPC (1) Sections Classes, subclasses Groups, subgroups A: Human necessities B: Performing operations; Transporting C: Chemistry; Metallurgy D: Textiles; Paper E: Fixed constructions F: Mechanical engineering; Lighting; heating; Weapons; Blasting G: Physics H: Electricity A 61: Medical or veterinary science; Hygiene A61F: Filters implantable to blood vessels, prostheses … A61L: Methods or apparatus for sterilizing materials … A61L 27 Materials for prostheses A61L27/02 Inorganic materials . . . A61L27/14 Macromolecular materials Detailed level Technical field More detailed level

35. IPC (2) http://www.wipo.int/classifications/ipc/ipc8/?lang=en Catchwords index

36. IPC (3) IPC natural language search - http://www.wipo.int/tacsy/ DNA computer

37. IPC (4)

38. ECLA (1) • There are four types of ECLA division: • identical to an in-force IPC group, containing the same subject matter as the IPC (IDENTICAL) • groups contains additional subject matter to the IPC (MOVED) • identical to a superseded IPC group (OLD) • new sub-divisions of an IPC group (UNIQUE) • Advantages: • more detailed; • dynamic (continuously revised) • Drawbacks: • some patent applications (JP, KR, CN, etc…) are not classified; • recent patent applications are not classified (only IPC codes are available)

39. ECLA (2)

40. Index Patent information: a competitive advantage Tools and methodologies for novelty and inventive step evaluation

41. Patent databases (1) • Free public sources (provided by patent offices) • Espacenet, USPTO, JPO, UIBM • Free sources (provided by independent patent websites; i.e. PATENT LENS, GOOGLE PATENTS) • Professional tools • Derwent, Micropatent, Delphion, QPAT • Patent databases may be: • specific if they contain only patent data; • mixed if they also contain scientific publications

42. Patent databases (2) • Patent data available and search possibilities vary considerably: • IPDL: simple bibliographic or keyword search • CIPO: include old patents not available elsewhere • EPO (on the web since 1998 with Esp@cenet) + USPTO (on the web since 1994): full access to the patent register and file histories • SurfIP: meta-search engine • GOOGLE PATENTS: only US patents • Patent Lens: full text of AU and EP granted patents

43. Patent databases (3) • An ideal database should contain all applications, granted patents, and utility models of all patent offices. Bibliographic data, the full text and drawings and legal status of patents should also be available. • Patents should be translated into one language, so as to facilitate search and evaluation of prior art.

44. Patent databases (4) No patent database is perfect, but all are highly incomplete Select patent databases according to needs Optimal result Search on different databases with different criteria

45. Patent databases (5) • “Full text” • chemical compounds search • genetic sequences search • The complete indexing of compounds / sequences is an added-value of professional tools compared to free databases. • Reprocessing of titles and summaries

46. Esp@cenet (1) http://ep.espacenet.com/?locale=EN_ep

47. Field where you enter keywords Esp@cenet (2) Database selection: EP, WIPO

48. Click on title Esp@cenet (3)

49. Patent sections Esp@cenet (4) Summary and drawing

50. Esp@cenet (5) • maximum of 500 matching documents listing • no statistical analysis possible • no search history provided • only ECLA and IPC classes searchable • when combining search fields the default operator is AND and cannot be changed (OR within fields is possible)