Using PatBase for Patent Landscaping: a case study on EbolaPrepared For: MinesoftConducted By: Aalt van de KuilenApril 2015

Table of Contents

Subject Matter ................................................................................................. 2Introduction ..................................................................................................... 3Summary ......................................................................................................... 5Procedure ........................................................................................................ 5Strategies ........................................................................................................ 6Visualization of the Ebola Patent Landscape ................................................. 17Additional features of PatBase: ..................................................................... 29Conclusions ................................................................................................... 31Appendix 1: PatBase search strategy: ........................................................... 32

Subject Matter Ebola is a devastating viral disease and has received a large amount of news coverage recently as revealed by a Google search on Ebola which identifies millions of articles about the recent outbreak, effecting mainly Guinea, Liberia and Sierra Leone. Although the World Health Organization recently made a statement to ignore IP-rights and focus first on controlling the outbreak, little is known about the exact size of the patent landscape surrounding Ebola.

Enclosed is a case study which takes Ebola as its subject matter and demonstrates how unique features of PatBase can be used to create insightful patent landscapes and how PatBase Analytics can be used to effectively visualise the landscape and answer key questions like:

• Is this a growing area of interest?• What are the fields of current interest?• Who are the key players?• Where are the key players filing their inventions?• Who are the “key opinion leaders” in this field?• What is the legal status of the patents in this landscape?

The aim of any patent landscape analysis is to accurately identify and visualise results so that answers to such key questions are quickly and easily found. This case study will demonstrate how any user can benefit from the innovative features and functionality in PatBase to craft and visualise a meaningfulpatent landscape.

Introduction Ebola virus disease (EVD) (formerly known as Ebola haemorrhagic fever) is a severe disease caused by a virus of the filovirus family, which occurs in humans and other primates. The disease emerged in 1976 in almost simultaneous outbreaks in the Democratic Republic of the Congo (DRC) and Sudan. In 1979, Ebola seemed to disappear but in 1994 was recognized again and outbreaks have occurred with increasing frequency ever since.

Year(s) Country Ebola subtype human cases

R (%) of deaths

March 2014-Present Guinea, Liberia and Sierra Leone Zaire virus 23948 9729 (41%)

December 2007-January 2008

Uganda Bundibugyo virus 149 37 (25%)

2007 Democratic Republic of the Congo Ebola virus 264 187 (71%)

December 2002-April 2003

Republic of the Congo Ebola virus 143 128 (89%)

2000-2001 Uganda Sudan virus 425 224 (53%)1995 Democratic Republic

of the Congo (for-merly Zaire)

Ebola virus 315 250 (81%)

1976 Sudan (South Su-dan) Sudan virus 284 151 (53%)

1976 Zaire (Democratic Republic of the Con-go - DRC)

Ebola virus 318 280 (88%)

Source: EBOLA Website from World Health Organization (see http://www.who.int/mediacentre/factsheets/fs103/en/ )

The largest outbreak of EVD is currently occurring in West Africa affecting primarily Guinea, Liberia and Sierra Leone. A small and unrelated outbreak was confirmed in the Democratic Republic of Congo in August 2014. Three smaller outbreaks occurred in 2012; 1 in the Democratic Republic of Congo, and 2 separate outbreaks in Uganda.There are 5 species of Ebola virus known, 4 of which have caused disease in humans:• Zaïre ebolavirus (EBOV)• Sudan ebolavirus (SUDV)• Tai Forest (TAFV) (formerly known as Ebola Ivory Coast)• Bundibugyo ebolavirus (BDBV) The fifth species, Reston ebolavirus (RESTV), has caused severe illness in non-human primates but not in humans. RESTV was first detected in October 1989 in Reston, Virginia (USA) in a colony of monkeys imported from the Philippines and has subsequently caused outbreaks in non-human primates in Pennsylvania (Philadelphia), Texas (Alice) and Italy (Sienna). Several research workers became infected with the virus during these outbreaks, but did not become ill.

In Africa, outbreaks of EVD have historically primarily occurred in remote villages close to tropical rainforests in Central and West Africa. Confirmed cases of Ebola have been reported in the Democratic Republic of the Congo (DRC, formerly Zaire), Sudan, Gabon, Uganda, Republic of Congo, Cote d’Ivoire, and in a number of other countries during 2014. The current Ebola outbreak is caused by EBOV (Zaire ebolavirus), which is the most lethal species, with a mortality rate of up to 90%.

The Ebola virus was at first suspected to be a new “strain” of the closely related Marburg virus but was renamed “Ebola virus” in 2010 to avoid confusion. Ebola virus is the single member of the species Zaire ebolavirus and both the Marburg virus and Ebola virus belong to the family Filoviridae. To date, no proven Ebola virus-specific treatment presently exists and there is currently no vaccine to prevent Ebola. Companies including GSK, J&J and Merck Inc. are developing and testing several vaccines and small molecules in volunteers in the affected countries.

The vaccines are:

cAd3-EBO ZIn September 2014, two Phase I clinical trials began for the vaccine cAd3-EBO Z, which is based on an attenuated version of a chimpanzee adenovirus (cAd3) that has been genetically altered so that it is unable to replicate in humans. It was developed by NIAID in collaboration with Okairos, now a division of GlaxoSmithKline.

VSV-EBOVA vaccine based on the vesicular stomatitis virus, called VSV-EBOV, has been developed by the Public Health Agency of Canada, with development subsequently taken over by Merck Inc.

Advac / MVA-BNJohnson & Johnson has developed an Ebola vaccine at its subsidiary, Janssen Pharmaceutical Company. The regimen consists of two vaccine components that are based on AdVac technology from Crucell Holland B.V., which is part of Janssen, and the MVA-BN technology from Bavarian Nordic.

Small molecules tested in humans with Ebola

Brincidofovir (CMX001, CAS number 444805-28-1, WO20110053812) an antiviral drug, owned by Chimerix, has been granted an emergency FDA approval as an investigational new drug for the treatment of Ebola after it was found to be effective against Ebola virus in in vitro tests. A trial commenced during January 2015 in Liberia, but subsequently was discontinued due to a lack of suitable subjects. In February 2015, Chimerix Inc. stopped the testing of its experimental antiviral in Ebola patients in Liberia, saying the number of infections had dropped in recent weeks, and that only a handful of patients had been enrolled in the Liberian study.

Favipiravir, (T-705 or Avigan, CAS number 259793-96-9, EP1112743 or USRE43748) is an experimental anti-viral drug being developed by Toyama Chemical of Japan with activity against many RNA viruses. This drug is originally developed for treatment of Influenza, but looks also very promising in the treatment of EBOLA.

BCX4430 (Immucillin-A, CAS number 222631-44-9, US7514410) is an antiviral, adenosine analogue. It is developed by BioCryst Pharmaceuticals with funding from NIAID, originally intended as a treatment for Hepatitis C, but subsequently developed as a potential treatment for deadly filovirus infections such as Ebola virus disease and Marburg virus disease.

ZMapp is an experimental biopharmaceutical drug comprising three chimeric monoclonal antibodies under development by Mapp Biopharmaceutical as a treatment for Ebola virus disease (WO0116183).

JK-05 (structure not disclosed yet, but seems to be the same molecule as Favipiravir/T-705) is an antiviral drug developed by the Chinese company Sihuan Pharmaceutical along with the Chinese Academy of Military Medical Sciences. In tests on mice, JK-05 shows efficacy against a range of viruses, including Ebola. This drug, was “developed” by Chinese Professor Wang Hongquan with the Institute of Microbiological Epidemiology under the Academy of Military Medical Sciences.

SummaryThis report shows how the advanced features in PatBase can be used to create clean and reliable patent landscapes, in an efficient manner.

The main features of PatBase highlighted in this report include:

- PatBase Analytics- Advanced Statistical Analysis- Citation ranking- Advanced keyword highlighting- Use of the “Similar” function to find similar documents- Classification finder- Chemical search- Citation searching

ProcedureThe landscape search commenced with a broad outlook, by reading the main articles in this area. Searching some basic keywords (in this case “Ebola” in the title, abstract and claims) in PatBase identified additional relevant keywords and active assignees. Additionally, a statistical analysis of the IPC and CPC codes used to classify the initial answer set helped identify relevant classifications which were added to the search strategy.Careful background reading gives information on the Ebola epidemic and enables us to identify relevant keywords and abbreviations for the virus including the virus belonging to the family filoviridae and being closely related to the Marburg virus. Additional keywords for the virus include: Bundibugyo virus (BDBV or BEBOV), Reston virus (RESTV or REBOV), Sudan virus (SUDV or SEBOV), Taï Forest virus (TAFV or CIEBOV), Ebola virus (EBOV or ZEBOV) as well as the close related term Marburg virus and the higher class filo virus (or filovirus or filoviridae). Another virus that generates haemorrhagic fever (one of the symptoms of Ebola) is the arenavirus, belonging to the Arenaviridae family, but related to the Ebola virus as well.

Once the relevant keywords have been defined, PatBase can identify the relevant classification codes for these records, which can be used to refine the strategy by limiting to specific classes.

Additionally, there are some very specific CPC classes known for Ebola in G12N2760 which can be searched in PatBase and finally, the above Ebola therapies can be explored to identify relevant families covering these entities.

After developing a comprehensive search strategy, encompassing keywords, classification codes, synonyms for known therapeutics, citations, the search results were focused closely on the subject matter of interest using a number of limitation steps. This process can be complex and needs to be checked at every step, in order to be sure that relevant records are not eliminated. In this example, we decided to keep the search as broad as possible and limit only by excluding all animal related diseases and remove all antivirals that did not specifically mention the use against Ebola viruses.

After performing a data quality check with eight (8) very relevant documents to ensure that these were included in our final answer set, we completed an analysis on a final answer set of 1670 families.

StrategiesStep 1: Preparation phase to devise a comprehensive search strategy

Utilising the PatBase Analytics software on your basic keyword search results (e.g. TAC=ebola) enables you to identify additional keywords of interest by using the Primary Keywords widget:

In addition, you can generate a more exhaustive overview of keywords by selecting the grid or circle option in the keyword menu.

An example of the circle option is displayed below:

Records clustered into specific areas (e.g. Ebola virus) can be visualised on the right of the screen and/or viewed in PatBase (see blue arrow below). Both enable you to identify other relevant keywords in the area of interest. For example: arenavirus, haemorrhagic viral, Marburg virus were identified from a quick review of the patent families in the Ebola Virus cluster.

Furthermore, relevant keywords also will come from the literature, such as synonyms for different types of the Ebola virus as well as relevant abbreviations. Another use of the keyword analysis in Analytics is the ability to identify the sources of irrelevant results and to exclude them from your search. In this case, the families clustered under the “HIV” area are not of interest and hence can be identified, reviewed in PatBase and then excluded from your landscape.

Other options in Analytics include the ability to visualise the top assignees and inventors. These can be noted and included in your final search strategy.

Therefore, starting with a basic keyword search, you can use PatBase Analytics to identify additional keywords, active assignees and inventors in the area and to exclude potential sources of irrelevant results, enabling a more comprehensive and clean final landscape search.

PatBase offers a very useful feature for identifying synonyms of launched therapies and those in late stage development: the Chemical Search function. A list of vaccines and small molecules currently under development to treat Ebola are given in the introduction and the chemical search feature finds additional relevant keywords.

The vaccines are: cAd3-EBO Z, VSV-EBOV (in the system as VSVDG-ZEBOV) and Advac / MVA-BNSmall molecules :Brincidofovir, Favipiravir, BCX4430, ZMapp and JK-05

The system will give you an indication in blue, as to whether or not the compound exists in the system.Synonyms will be generated in the search and can be added to the search strategy. After pushing the search button a new screen will come up with the synonyms.

The following terms were identified for these therapies: Ebola vaccine cAd3-EBO Z, cdAd3-EBO Z, cAd3-EBO and cAd3

Ebola Vaccine VSVDG-ZEBOV, VSVDG-ZEBOV and BPSC1001

BCV or Brincidofovir or Cidofovir-HDP or CMX 001 or CMX-001 or CMX001 or HDP-CDV or HDP-Cidofovir or Hexadecyloxypropyl - cidofovir or Hexadecyloxypropyl-cidofovir or Phosphonic acid, p-(((1S)-2-(4-amino-2-oxo-1(2H)-pyrimidinyl)-1-(hydroxymethyl)ethoxy)methyl)-, mono(3-(hexadecyloxy)propyl) ester or UNII-6794O900AX or 444805-28-1 or C27-H52-N3-O7-P or Hexadecyloxypropyl cidofovir

259793-96-9 or 2-Pyrazinecarboxamide, 6-fluoro-3-hydroxy- or C5-H4-F-N3-O2 or Favipiravir6-Fluoro-3-hydroxy-2-pyrazinecarboxamide or Avigan or T 705 or T-705 or T705 or UNII-EW5GL2X7E0

222631-44-9 or BCX-4430 or C11-H15-N5-O3.Cl-H2-(4-Amino-5H-pyrrolo(3,2-d)pyrimidin-7-yl)-5-(hydroxymethyl)pyrrolidine-3,4-diol or BCX 4430 or BCX4430 or UNII-1EL1K52SH1

zMapp, or Ebola treatment Zmapp

These terms were searched in PatBase, where 167 families of interest to these compounds were identified, including some important Chimerix patents. Interestingly, only 35 of these families were found in the basic keyword search and hence, the importance of using the Chemical Search is proven by this result.

Generating Classifications using PatBase Analytics:

PatBase Analytics can identify relevant classification codes, which can be used to supplement your search strategy. To identify relevant classifications, it is necessary to analyse the data at a subclass level. This can be done by clicking on the relevant bar in the graph.

Generating Classifications by PatBase Analytics:

PatBase Analytics can be used to identify relevant classification codes which can be used to supplement your search strategy. To identify relevant classifications, it is necessary to analyse the data at a subclass level. This can be done by clicking on the relevant bar in the graph.

At the family level, classifications can be visualised and by hovering over a bar in the graph, the relevant classification definition is shown:

1

The same analysis can be done for CPC classifications by selecting the relevant classification in the settings menu:

After analysing the classifications, the relevant ones can be selected and added to the search strategy. The Ebola patent landscape seems to be covered by a broad area of classifications both for CPC and IPC, which makes it more difficult to retrieve a very reliable answer set. Not surprisingly, there was high presence of A61P31, as about 40% of the records are related to anti-virals.

It’s important to include both IPC and CPC as a search term, because some records may not have been allocated a CPC classification yet. (In this case 92 % of the families have a CPC and as expected the records without a CPC are mainly coming from China, Japan and Russia, where no CPC is assigned yet).

Furthermore, it is interesting to note the enhanced level of detail in the CPC system, compared to the IPC. An example is the specific CPC classifications which are directly linked to Ebola (e.g. C12N2760), which can be easily identified using the Classification Finder feature in PatBase:

The scheme below shows the classifications related to the term “ebolavirus”:

A separate search on these specific CPC codes was completed and in this case generated a small number of families which were found to be very relevant (62 records).

Step 2: Executing a comprehensive landscape search:

Having identified a list of keywords and used PatBase Analytics to identify relevant classification codes, a comprehensive search strategy was compiled and run in PatBase:

Tac=(ebola* or ((hemorrhagic or haemorrhagic or zaire or sudan or reston or (tai forest)) w2 vir*))

or Tac=(filovirus or filoviridea or (filo virus) or Marburg or marburgvir* or ebol or ebobun or ebov or filovir* or Arenaviridae or arenavir* or (arena virus))or tac=(evd or ehf or marv or bdbv or ebov or zebov or restv or sudv or tafv or RVFV or rebov or bebov or sebov or ciebov) And FT=(ebol* or filovirus or (filo virus) or (Marburg virus) or marburgvirus or (arena virus) or arenavirus)(Due to the short terms for the viruses which can identify irrelevant art, it was more precise to search these acronyms in title, abstract and claims and to combine with relevant Ebola terms searched in the full text). And: IC =( A61P31* or A61K39* or A61K31* or C12N15* or C07K14* or A61K38* or C12Q1* or A61P37* or C07K15* or A61K38* or C12N5* or C12N7* or C12N15* or C12N33* or A61k35/76 or C07K16/10 or C07K16/08 or G01N33/56983) or CPC=(C12N33* or C12Q1* or A61K39* or C12N15* or A61P31* or A61P37* or C07K14* or A61K38* or A61K31* or C07K15* or A61K38* or C12N5* or C12N15* or C12N2760* or a61k35/76 or a61k2039/52* or c07k16/10 or c07k16/08 or c12n2810/60* or g01n33/56983 or a61k2039/53 or g01n2333/08*)(Broad usage of the classes mainly coming from Patbase analytics)

CPC=(C12N2760/14111 OR C12N2760/14121 OR C12N2760/14122 OR C12N2760/14123 OR C12N2760/14134 OR C12N2760/14143 OR C12N2760/14145 OR C12N2760/14151 OR C12N2760/14152 OR C12N2760/14163 OR C12N2760/14171 OR C12N2760/14211 OR C12N2760/14222 OR C12N2760/14223 OR C12N2760/14234 OR C12N2760/14245 OR C12N2760/14271)(Specific CPC classes generated by the classification finder in PatBase)

A temporary set with 2423 records was saved as “ebola workset”This set is saved in a folder and activated for further processing at any time by going to the “History” and choose “more…”.(1). By clicking “Add to result folder”(2) a new screen will pop-up and ask to give a name to the new folder. After clicking “Save” (3) the new folder is stored and can be activated later from “My saved folders”.

This working set can be cleaned up by excluding all veterinary publications and by eliminating all general antivirals which are not specific to Ebola:

not (ti=(mink* or deer* or fish or rabbit* or elisa or duck* or animal* or pig* or swine* or ((hemorrhagic fever) and (renal syndrom*)) or ((haemorrhagic fever) and (renal syndrom*))) or ti=(influenza or pox*))(exclusion of veterinary, pox and influenza related publications)

not(set nr not (ic=(c07c* or C07D*))) or (set nr and (Tac=(filovirus or (filo virus) or Marburg or marburgvir* or ebola or ebobun or ebov or filovir* or arenavir* or (arena virus)))) (Exclude all anti-virals that are not direct related to EBOLA, MARBURG OR FILOVIRUS)

At this point it is very important to check the data eliminated from the results set, in order to be sure that no relevant answers have been lost.

A final set was retrieved with 1670 records. This set was saved for further statistical analysis.A quick review of the final answer set revealed over 80% relevant answers, which is considered sufficient for a reliable patent landscape analysis. Furthermore, the final answer set included some key patents in this area (US6713069 OR US6200959 OR WO10048615 OR WO0116183 OR WO04007747 OR WO04018649 OR WO08045017 OR WO09116982 OR WO20110053812 OR EP1112743 OR US7514410 OR WO0116183). A additional citation analysis of these key patents retrieved 134 families, of which only 31 were already in the final set and hence, completing a citation analysis on key patents of interest is recommended to enhance the comprehensiveness of your landscape search.extract key inventions in a specific area but in this case, given the relatively premature patent landscape, there is limited citation data. Therefore, other sorting options would be more logical. For example, sorting by priority date or relevance would identify the earliest filed families or those of most relevance.

1

23

A unique feature in PatBase is the ability to rank results by most cited. This usually presents a reliable and reasonably easy way to extract key inventions in a specific area but in this case, given the relatively premature patent landscape, there is limited citation data. Therefore, other sorting options would be more logical. For example, sorting by priority date or relevance would identify the earliest filed families or those of most relevance.

Visualization of the Ebola Patent LandscapeHaving created a reliable set of 1670 families, we can then start to visualise the landscape using the PatBase Analytics software. PatBase Analytics provides an excellent platform from which to gain a visual overview of a landscape search. The ability to view the data from a number of angles (jurisdiction, year, assignee, inventor, etc.) and at multiple levels (families, priorities, applications, grants, etc.) can quickly reveal a number of conclusions to answer the key questions of interest. PatBase Analytics can be launched easily from the PatBase Search History view.

The Summary page below offers an overview of the landscape by identifying such information as the number of families, publications and granted patents in the answer set. In addition, we can quickly identify the number of jurisdictions in which patents have been filed, the number of assignees and the date coverage for the answer set.

The other widgets on the Summary page are customisable by clicking on the “Widgets” menu (see below). Worth noting is the “Primary Keywords” widget (see below) which identifies the most frequently occurring keywords in the final answer set. This could be useful in identifying additional keywords to add to your search strategy.

Is this a growing area of interest?Visualising the number of families, applications, grants and publications published over time allows us to identify that this is a growing area of interest, with a significant increase in the number of publications and grants over the past 10 years. The combined view in the Year menu allows a quick visual overview of the data and is customisable by clicking on the publication type in the key (see below), where for example we have excluded “Applications” by clicking on this in the key.

What are the fields of current interest?There are a number of ways to show the fields of current interest in the Ebola landscape utilising PatBase Analytics:

1) Classification analysis.

Analysing the landscape by classification codes allows the identification of the top classification codes and hence, indicates the fields of most interest. In this example, anti-viral compounds (A61P31 and A61K31) and vaccines/antibodies (A61K38 and A61K39) are amongst the top IPC and CPC codes.

To change the type of classification codes analysed, click on the IPC/CPC button in the settings menu (see 1 below). The graph automatically changes to the classification selected.

You can see some differences between the IPC and CPC classifications, For example, A61P31 is not a CPC class and some specific CPC classes in the “2000” series like A61K2039, C12N2760 and C12N2740 are identified. These classes come from the former In-Computer-Only (ICO) codes used in the ECLA classification system. Note that some care does need to be taken as not all families have a CPC assigned. (In this case 92 % of the families have a CPC, as expected the records without a CPC are mainly coming from China, Japan and Russia, where no CPC is assigned yet).

It is possible to drill down to a sub-class level by clicking on the relevant classification code of interest in the bar chart. For example, clicking on A61K2039 in the above chart allows us to identify the top sub-classes in this group:

1

2) Keyword Analysis

Using the Grid option in the Keyword menu is a useful feature to gain a quick, visual overview of the key fields of interest in the Ebola landscape. In this example, fields encompassing anti-viral compounds; detection; antibodies; vaccines; mechanisms to enhance the immune response to the virus; and understanding the virus at the genetic level (nucleic acid, RNA, amino acid) are identified as predominant keyword clusters:

Who are the key players? A patent assignee analysis clearly identifies the key players in this area. In this case the US Government (NIH) and US based universities are predominant. In addition, a number of smaller companies are identified who are active in this area including Biocryst, Kineta, Alios, Ibis and Curevac. This information is particularly useful as identifying the smaller companies or institutions that are active in this area and could provide opportunities for collaboration or partnership.

An additional and useful option within Analytics is the ability to group patent assignees that belong to the same entity. The Assignee Groupings option can be used to gain a true picture of the active assignees in the landscape and as a way to clean up the visualisation of your data.

Where are the key players filing their inventions?The Jurisdiction menu in Analytics allows you to visualise where the patents in your landscape are being filed. In this case, the top 5 jurisdiction for the granted patents in the landscape are the US, AU, EPO, AT and JP. The geographical display from the Jurisdiction menu is an alternative way to visualise the same data:

If a particular assignee is of interest (e.g. Biocryst – see p21, 1), clicking on the bar in the Assignee chart allows you to identify where they are filing their patents. In this case, the top 5 jurisdictions in which Biocryst file are the US, WO, AU, CA and EPO:

Who are the “key opinion leaders” in this field?

To identify the key inventors or opinion leaders in this field, an analysis of the inventors in the granted patents in your landscape is a good place to start. Furthermore, in the settings menu, clicking on “Group by company name” identifies their company/institution. In this case, the top inventors are from a number of US universities who may be worth investigating and/or contacting as key opinion leaders in the Ebola field.

What is the legal status of the patents in this landscape?

A new feature within Analytics is the ability to analyse your landscape from a legal status perspective. This can be useful to identify the split of dead or alive applications in your landscape and even the average time for the top assignees to obtain a granted patent:

Additional features of PatBase:One of the interesting tools in PatBase is the “Similar” option. This can be used to identify patent families that are similar to the patent of interest based on their title & abstract, description, claims etc. In this case, we used the most discussed record in Ebola (CA2741523 A1) to find similar documents and identified four (4) records with a similar description. These are of possible interest as a source of art in this technical area and can be added to the final answer set for analysis.

Highlighting:

To enable a comprehensive and efficient review of a PatBase answer set, the advanced highlighting option can be activated by clicking on the pen in the top right of the screen. Keywords can be highlighted within the text in up to ten (10) different colours. Truncations (right and left hand) and Boolean operators can be used:

An example is shown below where “Ebola”, “Marburg” and “hemorrhagic” are highlighted in the text:

ConclusionsThe Intellectual Property (IP) landscape of Ebola is growing and is dominated by the US government and universities. This has resulted in most of the research occurring in the US and >70% of patents being filed in this jurisdiction. Other prevalent jurisdictions include the EPO, WO, JP and more surprisingly AU (Australia) and AT (Austria). In addition, smaller companies seem to be active in this area (including Biocryst, Kineta, Alios, Ibis and Curevac) and thus, there seems ample opportunity for partnerships and collaborations to expedite innovation in this area. The key inventors in this area are from a number of US universities who may be worth contacting as key opinion leaders to provide scientific guidance and/or as potential partners for collaboration.

From the classification and keyword analysis, the fields of current interest in the Ebola landscape are anti-viral compounds, vaccines and antibodies, detection methods and mechanisms to enhance the immune response to the virus. However, at the present time, there is no approved medicine for the treatment of Ebola but the IP landscape shows that a lot of compounds are currently under development as antiviral compounds.

Finally, the majority of the applications in the Ebola landscape are currently active and “alive” which is not surprising given the prematurity of the patent landscape. However, there does seem to a difference in the time taken for the various assignees to obtain a granted patent. Reasons for this could include the breadth of the claim scope and the jurisdictions in which the applications are filed. These could be further explored to help guide an assignees filing strategy.

The step-by-step approach taken in this analysis is applicable for all patent landscape searches:1. Prepare by studying some basic literature2. Generate general keywords used for the specific technology3. Generate keywords and classifications4. Perform the search and analyse the result set5. Clean the set 6. Generate statistical graphs

By utilising the unique review and analysis features of PatBase, it is possible to easily create a thorough and insightful Patent Landscape Report. Of particular note is the use of the PatBase Analytics software to identify relevant keywords, classifications, active assignees and inventors. In addition, the Analytics software can be used to remove irrelevant results identified by the keyword clusters. Sorting answer sets based on “most cited” or “relevance” can identify patent families of particular interest in the field. In addition the advanced highlighting tool allows the comprehensive and efficient review of answer sets.

Furthermore, once satisfied with an answer set, the PatBase Analytics software can quickly and visually present the patent landscape in a series of graphs and charts revealing innovation trends, active assignees, key opinion leaders in the field (inventors), relevant classification codes and keywords of interest. As PatBase Analytics is an integral component of PatBase, all data within any graph or chart can easily be transferred to PatBase (with one click), enabling a more detailed review.

In conclusion, any Patent Landscape Analysis can be created and enhanced using the innovative features available in PatBase including:

- PatBase Analytics- Advanced Statistical Analysis- Advanced Keyword Highlighting - Finding “Similar” documents- Chemical Search- Classification Finder- Citation Search

Appendix 1: PatBase search strategy:

(17 not (ic=(c07c* or C07D*))) or (17 and (Tac=(filovirus or (filo virus) or Marburg or marburgvir* or ebola or ebobun or ebov or filovir* or arenavir* or (arena virus))))

1670

16 not (ti=(mink* or deer* or fish or rabbit* or elisa or duck* or animal* or pig* or swine* or ((hemorrhagic fever) and (renal syndrom*)) or ((haemorrhagic fever) and (renal syndrom*))) or ti=(influenza or pox*))

1788

RF=(ebola workset) 1977(12 and 13) or 14CPC=(C12N2760/14111 OR C12N2760/14121 OR C12N2760/14122 OR C12N2760/14123 OR C12N2760/14134 OR C12N2760/14143 OR C12N2760/14145 OR C12N2760/14151 OR C12N2760/14152 OR C12N2760/14163 OR C12N2760/14171 OR C12N2760/14211 OR C12N2760/14222 OR C12N2760/14223 OR C12N2760/14234 OR C12N2760/14245 OR C12N2760/14271)Specific Ebola CPC-classifications

63

IC =( A61P31* or A61K39* or A61K31* or C12N15* or C07K14* or A61K38* or C12Q1* or A61P37* or C07K15* or A61K38* or C12N5* or C12N7* or C12N15* or C12N33* or A61k35/76 or C07K16/10 or C07K16/08 or G01N33/56983) or CPC=(C12N33* or C12Q1* or A61K39* or C12N15* or A61P31* or A61P37* or C07K14* or A61K38* or A61K31* or C07K15* or A61K38* or C12N5* or C12N15* or C12N2760* or a61k35/76 or a61k2039/52* or c07k16/10 or c07k16/08 or c12n2810/60* or g01n33/56983 or a61k2039/53 or g01n2333/08*)(Classifications generated by Patbase Analytics)

more than

5 or 11 242311 6 or 7 or 8 or 9 or 10 (result from chemical name searches) 567

FT=( zMapp or Ebola treatment Zmapp) 19 FT=( BCX-4430 or C11-H15-N5-O3.Cl-H or BCX 4430 or BCX4430 or UNII-

1EL1K52SH1 )1

8 FT=(( 259793-96-9 or 2-Pyrazinecarboxamide-6-fluoro-3-hydroxy or C5-H4-F-N3-O2) or Favipiravir or 6-Fluoro-3-hydroxy-2-pyrazinecarboxamide or Avigan or T 705 or T-705 or T705 or UNII-EW5GL2X7E0 or 222631-44-9)

396

7 FT=( Brincidofovir or Cidofovir-HDP or CMX 001 or CMX-001 or CMX001 or HDP-CDV or HDP-Cidofovir or Hexadecyloxypropyl-cidofovir or mono(3-(hexadecy-loxy)propyl) ester or UNII-6794O900AX or 444805-28-1 or C27-H52-N3-O7-P or Hexadecyloxypropyl cidofovir)

65

6 FT=(cdAd3-EBO Z or cAd3-EBO or cAd3 or VSVDG-ZEBOV or BPSC1001) 1125 1 or 2 or (3 and 4) (result from key word searches) 18914 FT=(ebol* or filovirus or (filo virus) or (Marburg virus) or marburgvirus or (arena

virus) or arenavirus)6793

3 tac=(evd or ehf or marv or bdbv or ebov or zebov or restv or sudv or tafv or RVFV or rebov or bebov or sebov or ciebov)

1551

2 Tac=(filovirus or filoviridea or (filo virus) or Marburg or marburgvir* or ebol or eb-obun or ebov or filovir* or Arenaviridae or arenavir* or (arena virus))

1108

1 Tac=(ebola* or ((hemorrhagic or haemorrhagic or zaire or sudan or reston or (tai forest)) w2 vir*))

1307