Downloads/ Outbreak Starts

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PATENTS Ebola as a case study for the patent landscape of medical countermeasures for emerging infectious diseases A survey of patenting activity can facilitate coordination of R&D activities to fght emerging infectious diseases.

ethods to combat Ebola virus a 200 196 2,000 disease (EVD) have gradually 175

improved since its discovery in Cumulative patent family number M 1–3 1976 (refs. ). EVD has caused over 33,000 150 infections and 14,000 deaths worldwide, 1,500 with most cases occurring in Africa. Ebola virus (EBOV)—named for the Ebola River, 114113 located near Yambuku, Democratic Republic 100 1,000 of the Congo (formerly Zaire)—is the cause 74 76 75

Patent families 73 4 of the disease . The discovery of the Reston 59 62 54 56 545557 Ebola virus in the Philippines in 1989 50 46 45 showed that EBOV is also present in Asia. 39 500 During the first outbreak, in 1976, 25 14 131614 9 9 9 12 improper nursing techniques such as 1 1 2 1 1 1 3 1 2 2 2 4 3 3 3 3 4 1 0 0 reuse of syringes for different patients and 6 4 7 9 1 3 5 7 8 9 1 2 3 5 7 9 1 3 5 7 9 0 3 4 5 7 9 7 2 4 6 0 4 6 8 0 2 4 6 8 11 2 6 8 0 close contact with infected blood were 195 196197 197197 198198 198198 198198198198 198199 199199 199 199199199 199199 199200 200200 200200 200200 200200 200201 20 201 201201 201201 201201 201202 the main source of human-to-human Year of first application transmission5. A better understanding of methods of virus transmission during b 133 133 the 1994 Cote d’Ivoire outbreak led to the Families with no granted applications use of personal protective equipment and Families with at least one granted application 104 single-use syringes, which helped in the 100 96 control of transmission. The international public health community helped contain 63 the disease by staffing local hospitals 60 51 53 and providing necessary equipment and Patent families 50 49 5 42 42 37 education for health care workers . 34 31 31 32 29 33 33 29 28 26 The 2014 outbreak of EVD caused more 23 23 25 24 23 20 21 17 17 18 18 16 14 than 28,000 cases and 11,000 deaths—more 11 77 7 8 8 8 9 9 6 54 45 6 5 5 than all previous EVD outbreaks combined . 1 1 2 1 1 1 21 1 2 2 2 22 3 21 21 3 31 3 3 2 1 0 Several factors contributed to the devastating 6 7 4 7 9 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 11 2 3 4 5 6 7 8 9 0 195 196 197 197 197 198 198 198 198 198 198 198 198 198 199 199 199 199 199 199 199 199 199 199 200 200 200 200 200 200 200 200 200 200 201 20 201 201 201 201 201 201 201 201 202 effects of this outbreak, such as the delay between identification of cases and reporting Year of first application to the World Health Organization (WHO), Fig. 1 | Analysis of patent application and granting frequencies. a, Number of patent families against the spread of the disease to urban areas, application years as a bar chart and cumulative chart. There were two peaks in the number of patent and the weak response of the international applications that coincide with two EVD outbreaks. b, Families that had at least one granted patent community7. The outbreak also highlighted were counted in the granted families group. The rest of the patent families were counted in no granted lack of proper medical countermeasures families group. The gap between granted and not granted patent applications widened with increase in (MCMs) in diagnosis of, vaccination against the number of patent applications. and treatment of the disease8. WHO has since included EVD on the list of priority pathogens with the potential of severe outbreaks for which to control an EVD outbreak forced WHO be more specific. However, the application few or no MCMs exist9 and has drafted an to call for “rapid, sensitive, safe and simple of rapid diagnostic tests in combination R&D roadmap to accelerate collaborative EBOV diagnostic tests” as a crucial MCM with PCR-based methods was suggested development of MCMs against the disease8. in November 2014 (ref. 10). Following to be more effective11. Lack of data from The vital importance of rapid isolation this call, several tests, including various randomized controlled trials made it of infected patients based on the clinical rapid diagnostic tests, became available4. difficult to draw conclusions about the diagnosis that could be further confirmed PCR-based methods, which detected one or efficacy of therapeutics against EVD. To with the results of a readily available test two of the EBOV genes were considered to address this difficulty, WHO developed an

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a WO 609 US 482 AU 155 CN 142 EP 99 JP 37 RU 22 KR 12 UK 9 CA 4 TW 2 Jurisdiction DE 2 ZA 1 PH 1 NZ 1 FR 1 EA 1 CZ 1 AT 1

0 200 400 600 Publications

b WO 1 1 1 1 3 6 1 8 16 36 16 39 22 18 32 23 21 19 14 17 20 73 63 53 64 41 US 2 3 1 2 3 2 4 10 18 25 23 24 19 14 24 23 29 17 16 21 20 64 59 30 16 13 AU 1 1 1 2 1 1 2 2 5 3 2 8 2 6 3 6 5 3 6 7 7 7 3 5 6 1 4 4 9 3 10 10 10 8 1 CN 1 1 2 1 3 1 3 4 3 24 30 29 15 18 7 EP 1 1 2 2 1 1 1 1 1 2 1 1 1 4 1 5 3 5 5 9 2 5 5 1 10 5 8 4 5 4 1 1 JP 2 2 1 3 4 3 1 2 3 2 3 1 2 1 1 1 1 2 1 1 RU 1 2 1 1 6 3 4 3 1 KR 2 1 3 3 2 1 UK 1 1 2 2 1 1 1 CA 1 1 2 TW 1 1 1 1

Jurisdiction DE ZA 1 PH 1 NZ 1 FR 1 EA 1 CZ 1 AT 1

19561967 19741977 1979 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 19921993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 20042005 2006 20072008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 20192020 Year

Fig. 2 | Analysis of jurisdictions. a, Offices of the first patent application are grouped and counted. The number of families that were filed through the PCT is more than in other types of applications. b, Patent applications for each patent office plotted versus time in years. Applications in most patent offices are concentrated in the years after 2000. However, applications in some patent offices, such as AU, EP and JP, are more evenly distributed. WO, world (PCT); US, United States; AU, Australia; CN, China; EP, European Patent Office; JP, Japan; RU, Russia; KR, South Korea; UK, United Kingdom; CA, Canada; TW, Taiwan; DE, Germany; ZA, South Africa; PH, the Philippines; NZ, New Zealand; FR, France; EA, Eurasian Patent Organization; CZ, Czech Republic; AT, Austria. ethical framework to bridge compassionate which led to the approval of REGN-EB3, and European Medicines Agency (EMA) for access to investigational therapeutics and or Inmazeb (atoltivimab, maftivimab and the prevention of EVD14 and is being used clinical trials12. Following the development odesivimab), as the first drug to treat EVD13. in the Democratic Republic of the Congo of this guidance, a clinical trial was initiated For vaccine development, GP1,2 according to a ring vaccination strategy. in the Democratic Republic of the Congo protein was considered the major EBOV The EMA has also granted marketing to test the monoclonal antibodies ZMapp, immunogen. A recombinant vesicular authorization for a vaccine composed of mAb114 and REGN-EB3, as well as the stomatitis virus (VSV) pseudotyped a two-dose regimen of Zabdeno (Ad26. viral polymerase inhibitor remdesivir. In with Ebola Zaire glycoprotein, ZEBOV) and Mvabea (MVA-BN-Filo). this trial, patients who received REGN-EB3 rVSVΔG-ZEBOV-GP, was approved by the One of the lessons of the 2014 EVD or mAb114 showed higher survival rates, US Food and Drug Administration (FDA) outbreak was that collaborative development

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a 1. Univ California 27 b 1 3 2 3 2 2 1 1 1 3 2 4 1 1 2 c 1 3 15 10 2. Harvard College 23 2 1 1 1 1 1 1 1 2 1 3 7 3 2 5 1 3 14 3. Univ Emory 21 3 2 1 1 2 2 3 1 4 1 2 1 1 3 1 3 6 11 4. Massachusetts Inst Technology 20 4 1 2 1 1 1 2 1 10 1 4 4 1 15 5. US Gov Health & Human Serv 17 5 1 4 6 2 2 1 1 5 1 2 1 12 1 6. Univ Vanderbilt 17 6 1 1 1 1 2 2 1 3 1 4 6 1 1 2 13 7. Univ Texas 17 7 1 1 1 1 1 1 1 1 1 5 2 1 7 2 8 7 8. Dana Farber Cancer Inst Inc 14 8 1 2 1 2 5 1 2 8 1 13 9. US Health 12 9 1 1 3 1 1 2 2 1 9 5 7 10. Univ Pennsylvania 10 10 1 1 3 1 1 2 1 10 4 6 11. Broad Inst Inc 10 11 1 1 1 5 2 11 2 8 2 12. Biocryst Pharm Inc 10 12 2 3 1 1 1 12 1 6 3 13. Novartis AG 9 13 1 1 1 5 1 13 4 2 3 14. US Army 8 14 1 2 2 1 2 1 1 1 14 8 3 15. Univ Michigan 8 15 1 1 2 1 1 1 1 15 1 1 3 3 16. Curevac AG 8 16 1 1 1 4 1 16 3 3 2 17 17. Coyote Bioscience Co Ltd 8 1 3 3 1 17 8 18 18. Bavari Sina 8 3 2 3 18 5 3 19 1 2 1 2 1 19. Univ Rochester 7 19 2 5 20 1 4 1 1 20. Univ Leland Stanford Junior 7 20 3 4 21 1 1 1 2 1 1 21. Univ Duke 7 21 1 6 22 1 1 1 2 2 22. Nabel Gary J 7 22 2 5 23 2 2 3 23. Integrated Biotherapeutics Inc 7 23 1 6 24 1 2 2 2 1 1 24. Hodge Thomas 7 24 1 8 25 2 3 2

First applicant 25. GPC Biotech AG 7 25 1 1 5 26 4 1 1 1 26. Curevac GmbH 7 26 1 1 2 3 27 2 4 1 27. Crucell Holland BV 7 27 2 2 3 28 1 1 1 1 1 1 1 28. Commw Scient Ind Res Org 28 5 1 1 7 29 1 2 1 1 1 1 29. Chimerix Inc 7 29 2 1 2 2 30 1 6 30. Bevec Dorian 1 6 7 31 2 3 1 30 31. Zirus Inc 6 31 6 32 1 1 1 1 1 1 32. Univ Johns Hopkins 6 32 1 4 1 33 1 1 1 1 2 33. Univ Columbia 6 33 1 5 34 1 2 2 2 1 1 34. Rubin Donald 34 1 8 6 35 2 2 1 1 35. Replicor Inc 35 2 1 3 6 36 1 2 2 1 1 1 36. Murray James 36 1 7 6 37 6 1 5 37. Mondobiotech Lab AG 6 38 1 1 1 1 1 1 37 1 1 4 38. Massachusetts Gen Hospital 6 39 1 1 1 2 1 38 2 1 2 1 39. Interdigital Tech Corp 6 40 6 39 6 40. Inst of Microbiology and Epidemiology 41 1 1 1 2 1 40 the Acad of Military Medical Sciences 6 1 5 42 1 1 3 1 41 41. Gen Hospital Corp 6 2 2 2 43 6 42 42. Centre Nat Rech Scient 6 1 5 44 6 43 43. Cavalli Vera 6 1 5 45 6 44 44. Cavalli Fabio 6 1 5 46 2 1 2 1 45 45. Bacher Gerald 6 46 1 5 46. Aquinnah Pharmaceuticals Inc 6 1986199219941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019 0 10 20 AU CA CN EP US WO ZA Publications Year Jurisdiction

Fig. 3 | Analysis of applicants with the most applications. a, Applicants in each patent family with more than five applications, plotted as a bar chart. US academic, governmental and commercial institutions are the leading applicants. b, The number of applications in each year, graphed for the applicants in a. Each applicant has a different patenting activity over the years. However, most patenting activity is concentrated in the years after 2000. c, Applications by each applicant versus the office of first application. Most leading applicants prefer PCT over other patent offices for their first application. of MCMs under the guidance of WHO can which are related to medical technologies same document. These clusters might be be an effective strategy to control disease such as vaccines19. PLRs can help to combat attributable to different MCMs against EVD. outbreaks15. Major improvement on the priority pathogens by providing global collaborative development of MCMs could decision-makers like WHO with tools for Results be achieved if investors, pharma companies coordinating R&D on various aspects of We used the Lens patent database (https:// and researchers could identify ongoing R&D the development of MCMs against these www.lens.org/) to construct a database activities in a technological field or against pathogens. However, to the best of our of patents related to Ebola, then used R a specific disease to find collaboration knowledge, there has been no published PLR packages to process and visualize different opportunities and avoid parallel activities. In on patents or patent applications regarding aspects of the database. We analyzed the this regard, patent landscape reports (PLRs), MCMs against EVD. patent application rate, granting rate, the identification and analysis of issued Here we used freely available databases jurisdiction, applicants and classifications. patents and published patent applications and open-source R packages to generate We also used a modified network analysis for a particular technology or market area16, a PLR on MCMs developed to fight EVD. technique to cluster patent families on are valuable tools for data-driven decision Patenting activity showed a remarkable the basis of the co-occurrence of IPC making for various audience groups. PLRs increase after the 2001 and 2014 EVD classifications in each patent family. are used by companies to assess risks outbreaks. The United States was dominant imposed on their business by other patent in the number of total applications and Total and granted numbers. Application holders, by academics and governmental institutions with the most applications. rates and granting rates were obtained to agencies looking to measure the level of Commercial institutions applied for more assess application rate fluctuations over the R&D in a specific technological area, and by patents and increased their patenting activity years. To remove the effect of patent filing investors in company valuation17. The World more sharply after EVD outbreaks. Analysis in multiple patent offices, the patent with Intellectual Property Office (WIPO) has of International Patent Classifications the earliest application date was considered published guidelines for the preparation of (IPCs) showed that medicinal preparations representative for each family. Families with PLRs in an effort to make the process more containing antigens or antibodies were most more than 20 members are summarized in standard and to help consumers of these frequent among the patent families in the Supplementary Table 2. The total and the reports better understand what to expect dataset. Finally, we used a modified network cumulative number of patent applications from them18. WIPO has also prepared PLRs analysis tool to cluster patent families on are shown in Fig. 1a. There are two distinct in various technological areas, several of the basis of the co-occurrence of IPCs in the changes in patenting activity on EVD, which

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prevention a south zirus matthew bioengineering regeneron diseases warﬁeld immune junior genetics lisa washington antiviral represented mary school beijing mcdonald group duke design nippon ﬂorida sante limited ann bavari systems kelly

chinese oxford dorian bioscience paul pennsylvania university martin mcmaster for sina diagnostics uchrezhdenie institute peter rubin kettering bioscience wuhan broad jomaa bayer albert texas emory infectious ecole henrik org med zhang gerald chang jose gmbh

biopharma medicine bevec and pharmaceuticals academy hitachi north curevac human company

bert scott vaccines james research mark hart

institut cancer foundation wisconsin nabel mondobiotech johns beth

genzyme china bioteknologii zhejiang discovery elenore corp gpc acad daniel scient vera yang gov david cheng biotherapeutics inc holland centre fabio state massachusetts park israel thomas novartis columbia michigan gen llc ind donald technologies suzhou stephen health interdigital hodge gary pty harvard john hopkins wyeth sloan univ

bogoch res lab states nat sec pharm epidemiology replicor the southern ltd jan lee michael int julie hospital command technology chimerix federalnoe medical college klebl biotechnology farber tech robert pharmaceutical tsentr army inst hong william dev dennis vanderbilt

boston coyote found california sciences cavalli brigham electronics pharma

toshiba disease wilson schmaljohn

therapeutics biocryst stanford science rech military dana center gosudarstvennoe agenovir serv commw services shanghai pla biotech kim electric control zhou healthcare pasteur richard andrew biomedical geisbert secretary samuel rochester sinai united leland alumni microbiology byudzhetnoe barry integrated childrens wang murray huang maria biosciences alan innovation virginia natalie bacher client altria crucell ashley maryland aquinnah nauki government wei kang jiangsu virusologii b c

Commercial 43 Government & commercial & academic 600 Government & commercial Government & academic Academic 25 Government Academic & commercial Individual Individual 15.5 Academic Commercial

400 Academic & 9.2 commercial

Applicant type Government 3.7

Government 1.8 200 & academic Cumulative sum of patent families

Government 1 & commercial

Government 0.8 0 & commercial 2011 & academic 1956 1967 1974 1977 1979 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2012 2013 2014 2015 2016 2017 2018 2019 2020 0 10 20 30 40 Percent of total families Year

Fig. 4 | Analysis of applicant types. a, Applicants column of the patent family dataset pasted together and, after cleaning, converted into a word cloud. Commercial and academic institutions are the most abundant applicant types. b, Applications by each type of applicant, grouped on the basis of search keywords provided in Supplementary Table 1. Applications by commercial and academic institutions and collaborations therewith account for most of the applications. c, Cumulative application counts for each applicant type, plotted against year of application. Applications by commercial institutions show a greater growth rate than those by other types of applicants. are detectable by the change in the total increased in line with the number of total illustrated as a sum total and by year to number of applications and in the slope of applications, especially in recent years determine the most favored jurisdiction the cumulative patent applications. These (Fig. 1b). It seems that EVD outbreaks have for applications related to EBOV and the increases in patenting activity coincide with had a motivational effect on R&D activities, pattern of applications over the years. two EVD outbreaks: after the 2001 outbreak and as a result the patent application rate Patent Cooperation Treaty (PCT) on the border of Gabon and Republic of has increased after them. applications were the most abundant type the Congo20 and after the 2014 outbreak in of applications, followed by applications the Democratic Republic of the Congo21. Jurisdictions. Since the patent with the filed at the US Patent and Trademark Office Although the rate for granting patents earliest application date was chosen as the (USPTO), the Australian Patent Office and follows that of the total application rate, the family representative, patent jurisdictions the Chinese Patent Office (Fig. 2a). The gap between the number of families with reflect the office of the first application. pattern of patent applications was different and without any granted applications has Applications in each jurisdiction were for each patent office (Fig. 2b). Applications

802 Nature Biotechnology | VOL 39 | July 2021 | 799–808 | www.nature.com/naturebiotechnology feature at some patent offices, such as Australia, institution—academic, commercial and (compounds containing elements of groups Europe and Japan, were started earlier governmental—was determined by matching 5 or 15 of the periodic table). Three ipc1 than those at other patent offices. PCT applicants with search terms provided in segments characterizing patent applications applications and US patent applications Supplementary Table 1 (Fig. 4b). The cumu by Harvard College (the second-ranked peaked after 2001 and 2014, similarly to lative rate of patent applications over the applicant) were C12N15 (genetic the pattern of total patent applications years for each type of applicant is shown engineering), C12Q1 (measuring or testing (Fig. 1a). This pattern was not shown by in Fig. 4c. processes involving enzymes) and A61K39 applications filed in other patent offices. The terms ‘univ’ and ‘inc’ were the most (medicinal preparations containing antigens Patent applications that were filed before used terms in the word cloud, indicating that or antibodies). Patents by Novartis showed 1976 at the UK patent office were verified as academic and commercial institutions were a different distribution of ipc1 segments, search engine errors, since EBOV had not the most common applicants for patents concentrated on heterocyclic compounds been discovered before 1976. On the basis related to EBOV (Fig. 4a). Commercial (C07D401, C07D403 and C07D405). of this information, we can conclude that institutions led with 43 percent of the total An abstract view of Fig. 5 suggests that PCT and USPTO are the favored offices applications. Moreover, commercial and efforts to develop MCMs against EVD were for patent applications related to EBOV. In academic institutions and their collaborations most focused on medicinal preparations addition, the pattern of applications at these together accounted for 77.2 percent of total containing antigens and antibodies and also two offices determines the total application applications (Fig. 4b), in line with the results on antiviral drugs. However, the approach pattern over the years. from the word cloud (Fig. 4a). In addition, the of each applicant was different in developing cumulative application rate by commercial these MCMs. Applicants. Identification of applicants institutions had a sharper slope after 2001 and with the most patent applications related 2014 than other types of applicants (Fig. 4c), Network analysis. When two IPCs are to EBOV can help to determine major which indicates a greater increase in patenting used to classify a patent, those IPCs can be contributors to the development of MCMs activity in response to EVD outbreaks in this assumed to be linked by that patent. These against the virus. Here, applications by each sector than among other types of applicants. links (edges) connecting ipc1 segments applicant were counted and applicants with Altogether, commercial institutions (nodes) are shown in Fig. 6a. A node is more than five applications were sorted have had the greatest contribution to considered a member of a community on (Fig. 3a). Applications by major applicants technological developments against EBOV the basis of the number of connections it were also plotted by year (Fig. 3b) and and increased their patenting activity more has with other nodes in the community. jurisdiction (Fig. 3c). than other types of applicant in response to Community membership of the most linked Three US institutions—the University EVD outbreaks (Fig. 4). nodes is summarized in Supplementary Fig. 1. of California, Harvard College and Emory Moreover, communities can be clustered University—applied for the most patent Technological area. To extract technological on the basis of the number of nodes that families in the dataset (Fig. 3a). The top information about patents, we used IPC they share (Fig. 6b). The nodes in each non-US institution with the most patent classifications because of their prevalent community, communities in each cluster, applications in the field was Novartis, use in patent documents. We split IPCs into and a definition for each node—whether ranked 13th. Each institution showed a two parts (before and after the “/”, or ipc1 unique in the community or shared by distinct application pattern over the years, and ipc2), which allowed the formation other communities within the cluster—are and its relation to EVD outbreaks could not of more inclusive and general groups. The provided in Supplementary Table 4. be established (Fig. 3b). Applicants ranked occurrence of each ipc1 was then counted A61P31 (anti-infectives) was the node 43–45 were co-applicants for the same in both total (Fig. 5a) and by year (Fig. 5b). with the most community memberships, patent families, which resulted in the distinct The most prevalent classifications in followed by A61K31 (medicinal preparations pattern seen for these applicants. PCT was applications by each of the major applicants containing organic active ingredients) and the favored patent application jurisdiction are shown in Fig. 5c. A61P35 (antineoplastic agents) (Fig. 6a for major applicants (Fig. 3c). However, The most prevalent ipc1 among and Supplementary Fig. 1), implying that some applicants preferred to apply in the patents related to EBOV was A61K39 anti-infectives are the common theme of jurisdiction where they were located. For (Fig. 5a). Considering the most prevalent all but two communities (communities example, the US Army applied eight times ipc2 segments of this classification number 1 and 9). These two communities through USPTO and three times through (Supplementary Table 2), this classification formed one cluster together (Fig. 6b and PCT, and the Institute of Microbiology and was related to medicinal preparations Supplementary Table 4), sharing the C12Q1 Epidemiology, Academy of Military Medical containing antigens or antibodies. A61P31 (measuring or testing processes involving Science in China (ranked 40th) applied six (antiviral drugs) and A61K31 (medicinal enzymes, nucleic acids or microorganisms) times through the Chinese patent office. Of preparations containing organic active node. The rest of the communities shared the most active applicants, US scientific and ingredients) were the second and third the A61P31 node. It can be assumed commercial institutions were the dominant most prevalent ipc1 segments. Distributions that all these communities were about applicants for patents related to EBOV. of the ten most prevalent ipc1 segments anti-infectives. Communities number 2, 3 over the years were similar to that of total and 4 have a single unique (not shared by Applicant type. Distinguishing the types patent applications (Fig. 5b). This pattern other communities within the cluster) node of institutions applying for patents related was not uniformly followed by other ipc1 each. These nodes were C07K1 (general to EBOV can help understand each sector’s segments. The three most prevalent ipc1 methods for the preparation of peptides) for level of contribution in developing MCMs segments in patent applications by the number 2, A61K33 (medicinal preparations against the virus. The most common words University of California (the first-ranked containing inorganic active ingredients) among applicant names were identified applicant) were A61P31 (antiviral drugs), for number 3, and C07D487 (heterocyclic by generating a word cloud (Fig. 4a). A61K31 (medicinal preparations containing compounds containing nitrogen atoms as The ratio of applications by each type of organic active ingredients) and C07F9 the only ring hetero atoms in the condensed

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a A61K39 415 b A61K39 1 1 1 1 1 2 1 4 3 7 5 16 23 16 18 13 12 22 21 15 17 12 18 12 33 55 41 26 17 1 A61P31 346 A61P31 1 1 2 2 2 7 10 4 11 11 7 4 16 9 21 17 17 16 5 12 11 33 52 31 28 16 A61K31 336 A61K31 1 1 1 1 4 5 5 10 11 12 11 14 9 12 16 11 11 8 24 8 44 42 25 34 16 C12N15 300 C12N15 1 1 4 2 3 2 8 2 10 22 23 12 14 6 10 8 13 11 11 8 10 13 20 28 18 23 17 C07K14 209 C07K14 1 1 1 1 4 1 2 3 5 3 7 16 26 6 16 4 4 12 9 9 11 4 5 10 10 11 9 9 9 C12Q1 203 C12Q1 2 2 1 3 5 1 4 6 14 10 8 5 6 6 8 5 7 4 5 20 31 19 13 10 8 A61K38 191 A61K38 1 1 3 3 2 2 1 2 12 18 8 13 6 6 19 9 9 7 5 4 7 20 19 5 6 3 C07K16 183 C07K16 1 1 2 3 2 4 9 10 4 4 2 10 6 1 3 3 6 25 34 26 16 10 1 G01N33 165 G01N33 1 2 1 2 2 2 2 2 3 8 8 9 7 2 4 6 5 5 3 6 4 11 19 21 11 12 6 1 C12N7 113 C12N7 2 2 2 1 3 6 11 2 8 3 5 1 4 5 4 3 7 7 8 17 2 6 4 A61P35 99 A61P35 1 2 1 5 2 4 2 4 2 8 4 9 7 3 4 1 6 2 4 12 5 9 2 A61K9 99 A61K9 2 1 5 5 6 3 4 3 1 2 3 3 1 4 9 20 11 10 6 C12N5 93 C12N5 1 1 1 1 1 3 2 4 6 7 2 2 4 3 6 5 5 3 1 1 1 7 8 8 6 4 A61K48 86 A61K48 1 1 2 1 1 4 7 11 4 10 3 3 3 6 1 4 1 3 3 9 2 4 2 1 1 3 2 3 2 5 3 1 2 1 1 3 1 3 5 13 10 1 8 2 A61K45 71 A61K45 1 1 3 1 1 4 3 3 1 1 9 9 7 4 1 1 1 5 4 5 1 A61P37 66 A61P37 A61K35 1 1 1 3 1 3 2 6 2 2 3 1 4 2 2 6 10 4 9 3 A61K35 66 IPC classifications C07H21 1 1 2 5 3 4 4 3 4 8 3 6 2 1 1 2 2 4 4 1 C07H21 61 A61K47 3 3 4 2 1 1 2 1 2 1 3 1 2 3 4 10 3 10 4 1 A61K47 61 C12N9 1 2 1 3 5 1 1 3 2 2 1 2 1 4 3 5 3 4 2 First part of IPC classification C12N9 46 C12P21 1 1 1 1 1 1 1 1 2 5 2 2 2 1 1 4 2 1 2 1 1 2 C12P21 36 A61P25 1 1 1 3 1 1 9 3 2 2 2 2 3 3 A61P25 34 C07F9 1 4 3 4 2 1 2 3 1 1 2 3 2 1 1 C07F9 31 C12N1 1 1 2 1 2 3 3 1 1 2 2 1 2 1 1 1 3 1 C12N1 29 C07K7 1 1 1 3 3 1 1 3 1 1 1 6 2 2 C07K7 27 A61P33 1 4 5 3 1 1 1 1 1 3 2 3 1 A61P33 27 A61P9 1 3 1 1 2 1 8 1 2 2 3 1 A61P9 26 C12R1 1 1 1 1 1 2 2 1 1 1 3 4 2 2 1 C12R1 24 G06F19 1 2 2 1 2 2 2 1 2 4 2 2 G06F19 23 A61K33 1 3 1 1 1 1 6 2 1 6 A61K33 23

0 100 200 300 400 19861987199019921993199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020 Count Year

c Univ California 1 9 4 5 3 2 3 3 3104 3 3 2 2 3 3 1 6 5 1 2 1 2 4 1 2 1 Harvard College 2 1 1 8 2 2 1 2 1 1 1 9 4 2 8 2 Univ Emory 7 1 5 9 2 1 2 2 9 2 1 1 1 1 1 3 3 1 1 3 1 3 1 2 3 Massachusetts Inst Technology 2 1 3 3 1 1 1 1 1 10 4 6 1 2 US Gov Health & Human Serv 1 2 3 5 3 2 3 3 2 1 4 1 3 1 2 1 Univ Vanderbilt 1 2 3 5 2 3 4 4 3 6 1 4 2 1 Univ Texas 2 4 2 1 3 6 2 1 1 4 1 1 1 3 2 4 1 2 1 2 1 2 4 Dana Farber Cancer Inst Inc 3 6 1 2 1 1 1 1 2 3 1 1 1 US Health 1 1 8 1 1 2 2 4 3 1 1 1 2 2 Univ Pennsylvania 1 1 4 5 2 2 1 3 3 8 2 1 Broad Inst Inc 1 1 1 1 6 1 4 7 Biocryst Pharm Inc 1 9 2 3 2 1 1 3 2 1 Novartis AG 1 7 2 2 2 2 1 4 2 2 2 2 2 2 5 3 3 2 2 3 2 1 1 1 1 1 1 1 1 1 US Army 1 2 5 1 2 1 1 3 2 1 1 2 Univ Michigan 3 6 1 1 2 4 2 2 1 Curevac AG 3 8 1 4 2 2 1 1 3 7 2 1 Coyote Bioscience Co Ltd 3 7 2 Bavari Sina 3 6 1 2 2 3 2 4 2 Univ Rochester 1 4 1 1 1 1 1 1 3 1 Univ Leland Stanford Junior 1 2 1 3 2 2 1 2 Univ Duke 1 1 1 2 1 1 1 1 1 1 1 1 2 Nabel Gary J 1 4 2 1 3 1 1 Integrated Biotherapeutics Inc 5 1 1 5 1 2 1 Hodge Thomas 3 2 4 4 4 1 5 1 2 1 GPC Biotech AG 5 1 1 1 1 2 2 1 1 2 1 1 2 2 Applicant Curevac GmbH 2 1 2 4 1 1 3 5 Crucell Holland BV 3 5 4 1 6 1 2 Commw Scient Ind Res Org 1 1 1 1 1 1 4 1 1 2 Chimerix Inc 5 2 3 1 2 2 Bevec Dorian 1 6 1 6 6 1 6 6 6 6 6 Zirus Inc 2 2 3 3 4 1 3 3 1 Univ Johns Hopkins 1 1 1 1 2 1 1 1 1 Univ Columbia 4 2 2 2 2 3 3 3 2 3 2 1 1 1 3 3 3 4 Rubin Donald 3 2 4 4 4 1 5 1 2 1 Replicor Inc 6 2 2 4 2 3 1 6 2 3 2 2 Murray James 3 2 3 3 3 1 4 1 1 Mondobiotech Lab AG 6 6 6 6 6 6 6 6 Massachusetts Gen Hospital 1 1 3 1 3 1 1 1 2 1 Interdigital Tech Corp 4 3 Inst of Microbiology and Epidemiology the Acad of Military Medical Sciences 1 6 2 5 Gen Hospital Corp 1 2 2 1 2 1 1 1 1 2 1 2 1 1 Centre Nat Rech Scient 4 3 1 1 1 1 1 1 1 Cavalli Vera 6 6 6 6 6 6 6 6 Cavalli Fabio 6 6 6 6 6 6 6 6 Bacher Gerald 6 6 6 6 6 6 6 6 Aquinnah Pharmaceuticals Inc 2 6 3 1 1 1 1 1 2 1 1 1 1 C07F9 A61P3 A61P9 H04B7 C07K7 C12R1 C12N1 C12N5 C12N7 C12N9 A61K9 C12Q1 H01M8 C12M1 A01K67 A61K31 A61K33 A61K35 A61K38 A61K39 A61K45 A61K47 A61K48 A01N25 A01N43 H04L27 A61P11 A61P19 A61P25 A61P29 A61P31 A61P35 A61P37 A61P43 G06F19 C12P21 C07K14 C07K16 C07K19 C07H19 C07H21 C12N15 G01N33 C07D213 C07D231 C07D241 C07D277 C07D401 C07D403 C07D405 C07D407 C07D409 C07D413 C07D417 C07D487 C07D491 C07D495 IPC

Fig. 5 | Analysis of technological areas of patent applications. a, Patent families were grouped based on their inclusion in one of the IPCs. Only the first part of the classification code (the part before “/”, herein identified as ipc1) was used, to obtain more inclusive groups. The occurrence in each patent family was counted as 1, regardless of the number of times ipc1 was repeated in that family. Patent families related to antigen and antibody preparations are the most prevalent, followed by patent families related to medicinal preparations containing organic materials and patent families related to antiviral agents. Other prevalent patent families are summarized in Supplementary Table 3. b, The distribution of the most prevalent patent classifications over years. The most prevalent classification groups match the pattern of distribution of total families (Fig. 1a). However, the least prevalent classifications do not match this pattern. c, The distribution of applications by the top 30 applicants over different patent classifications. The most prevalent patent classification among the top 30 applicants is those related to medicinal preparations containing antigens or antibodies (A61K39, with 111 instances), followed by those related to genetic engineering (C12N15, with 76 instances) and those related to medicinal preparations containing organic active ingredients (A61K31, with 71 instances).

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a 4 3 with the other communities in the cluster, C07D487 A61K33 their themes can be considered ‘synthetic compounds’ and ‘biological materials’,

A61P29 respectively. C07D413 C07D239 Analysis of link communities showed C07D403 A61P11 C07D401 A61P25 ‘detection systems’ and ‘anti-infectives’ as 10 A61P43 8 A61P9 C07D417 two major themes in the development of A61P19 A61P3 C07D409 C07D405 A61P7 MCMs against EBOV, which was in line with information gained from analysis of the prevalence of ipc1 segments in patent families (Fig. 5). Anti-infectives can be divided further into biological C40B40 A01N57 A61K31 (communities number 2, 5 and 7), synthetic C07H19C07F9 A61P31 (communities number 4, 6 and 8) and 6 A61P35 1 inorganic (community number 3) materials. A61K47 A61P37 Community number 10 might be defined A61K9 A61K38 as inventions that claim to treat other A61K45 A61P33 C12N9 disorders as well as EVD or inventions A61K35 C12Q1 G01N21 A61K48C07K16C07K14 G06F19 that were aimed at complications caused C12N5 G01N33 C12P21A61K39 C12N15 by the disease. For example, nucleoside C07K7 C12N7 C07H21 derivatives that target viral polymerases might also be claimed as antineoplastic C12N1 C07K1 7 9 agents, and an invention might claim to C12R1 C07K19 alleviate immunological or cardiovascular complications of EVD rather than being a direct antiviral.

Discussion 5 2 We analyzed patents related to EBOV in b areas of total and granted counts by year, jurisdiction, applicant and technological area. Our results show an increased number of patent applications after the 2001 and 1.2 2014 Ebola outbreaks. Applicants had a preference for PCT as their first office of application, although some major applicants preferred their national patent office for 1.0 the first application. US commercial and t h

g academic institutions were the major i e

H applicants. Counting IPC classifications of 0.8 patent families showed that the development 9 1 of MCMs against EVD was mainly focused 8 10 3 on medicinal preparations containing antigens and antibodies and also on 0.6 2 antiviral drugs. These results were also

6 4 confirmed with network analysis of patent classifications. 7 5 Patenting activity on a disease reflects global efforts to alleviate threats to public Fig. 6 | Network analysis of IPCs. a, Communities generated by the ‘linkcomm’ package on the basis health imposed by that disease. The shift of co-occurrence of ipc1 segments in each patent, as visualized by ‘spencer.circle’ layout. A61P31 in patenting activity on EVD shows the (anti-infectives) and A61K31(medicinal preparations containing organic active ingredients) are mobilization of global capacities toward two central nodes that connect all but two communities (communities 1 and 9). b, Visualization R&D caused by the 2014 West African EVD of communities from a clustered on the basis of their common nodes (ipc1 segments) using the outbreak. The increase in patenting activity ‘getClusterRelatedness()’ function from the ‘linkcomm’ package. There are two large clusters, which can was matched by global investment, with further be divided into smaller ones. total investment on EVD nearly quadrupling from $165 million in 2014 to $631 million in 2015 (refs. 22,23). However, patenting activity system) for number 4. Therefore, these that have a common technological theme: did not increase at the same rate, with only communities can be defined by those ‘microorganisms’, ‘heterocyclic compounds’ a 2.6-fold increase over the same period nodes (Supplementary Table 4). Other and ‘drugs for various disorders’, respectively. (Fig. 1a), possibly because the majority of communities could not be defined by a Communities number 6 and 7 did not funding in 2015 was dedicated to vaccine single node. However, community numbers have a technological theme in their unique clinical trials ($388 million), which would 5, 8 and 10 are populated with unique nodes nodes. On the basis of their shared nodes not result in patent applications.

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There is also a connection between might not be protected with a patent. common between assignees or inventors funding and patenting activity by various As stated earlier, patients who received is analyzed via network visualization applicants. US public and philanthropic REGN-EB3 or mAb114 therapeutics in the tools28. Patent documents are obliged to organizations funded 70 percent ($113 PALM clinical trial had a better survival cite prior documents that contributed to million) of the total investment on EVD rate than patients who received ZMapp or the development of the invention. Patent in 2014 and 50 percent ($306 million) in remdesivir24. This study led to FDA approval citation studies use network visualization 2015 (ref. 23). US dominance in R&D was of Inmazeb as the first approved drug to tools to analyze these citation networks29. also evident from applications that filed at treat EVD. Inmazeb, mAb114 and ZMapp Here, we employed network analysis on the USPTO (Fig. 2a) and the number of are based on monoclonal antibodies, and a different aspect of patent documents— US institutions among the top applicants patent applications related to these and namely, their classifications. Because of (Fig. 3a). Commercial institutions invested other similar drugs are classified under the diverse technologies involved in the 20% ($34 million) and 36% ($226 million) A61K39 and/or C07K16 (Supplementary development of MCMs against EVD, of the total investment on EVD in 2014 Table 3). Remdesivir, developed by Gilead we used this technique to differentiate and 2015, respectively. Since commercial Sciences, was not shown to improve various technological disciplines on the and academic institutions also received survival rate in the PALM trial but has basis of patent classifications and their a portion of the funding by public and now been approved by the FDA13 against co-occurrence in patent documents. We also philanthropic institutions, one can conclude SARS-CoV-2 as Veklury. Gilead Sciences used ipc1 segments to allow more inclusive that there is also a connection between the was not among the top 40 patent applicants; groups. Our results show the capability funding spent in commercial institutions however, the patent family protecting of network analysis to cluster patent and their dominant position as applicants remdesivir had the most family members documents in relevant clusters using their of EVD-related patents (Fig. 4). There in our dataset (Supplementary Table 2). IPCs (Fig. 6 and Supplementary Table 4). is a need, however, for inclusion of the The number of family members is a In network analysis of the co-occurrence development phase in R&D financial patent value indicator because it reflects of patent classifications, A61K31, A61K45, information to make an analysis of the the intention of the assignee to seek C07F9 and C07D487 were members of relationship between investment and protection in more jurisdictions. This communities number 4 and 6, which patenting more feasible. patent application is classified with the formed a cluster. These classifications Vaccines, drugs and diagnostic tests following IPCs25: C07H15/18, A61K31/00, were used to classify the patent protecting are major MCMs against EVD. However, A61K31/53, A61K31/675, A61K31/685, remdesivir. Similarly, IPCs starting with funding in each area does not appear to A61K45/06, C07D487/04, C07D519/00, A61K35, A61K39, C07K14 and C12Q1 be reflected in the number of patents in C07F9/24, C07F9/6561, C07H1/00, were used to classify the patent protecting that area. Vaccines received the major C07H1/02, C07H7/06 and C07H11/00. rVSVΔG-ZEBOV-GP and belonged to portion of funding related to EVD in 2014 From these classifications, those beginning communities number 2, 5 and 7, which also (43%) and 2015 (61%), followed by drugs with C07F9 were among the most frequent formed a cluster (Fig. 6 and Supplementary (42% and 16%) and diagnostic tests (4% classifications (Fig. 5 and Supplementary Table 4). These observations emphasize the in 2014 and 2015)23. It is challenging to Table 3). The FDA and EMA have approved applicability of network analysis of IPCs to find a relationship between investment in the rVSVΔG-ZEBOV-GP vaccine to prevent the clustering of patent applications related each MCM type and the number of patent EVD. The patent document protecting this to different MCMs. One can also use this applications related to that MCM because invention was classified into the following technique in multiple steps to study a subset most patent applications are classified by IPCs26: A61K39/12, A61K35/76, A61K39/00, of the dataset. For example, any community more than one IPC, making attribution of C07K14/08, and C12Q1/70. Here, described in Supplementary Table 4 can be the total number of patent applications for classifications starting with A61K39 and chosen and analyzed again using the whole each MCM type difficult. Moreover, the A61K35 were among the most frequent IPCs IPCs (ipc1 and ipc2 combined) to discover reported investments include amounts that (Fig. 5 and Supplementary Table 3). communities nested inside the chosen were spent in clinical trials, which are not A better understanding of the community. This could be the aim of reports necessary for diagnostic tests. Two different relationship between patenting activity on that are focused on a specific technological types of diagnostic tests are being used each MCM and funding in that area would area (for example monoclonal antibodies) in the field: rapid viral antigen detection require further analysis, which is beyond that are used to fight EVD. and PCR-based tests4. Patent applications the scope of this article. However, it is clear The vision of the Ebola/Marburg that are classified in IPCs beginning with that patents related to each MCM cannot R&D Roadmap document8 is as follows: G01N33 (immunoassay biospecific binding be counted merely on the basis of their “Robust MCMs to detect, control, and assay materials) are likely to include patents membership in specific IPCs, and more prevent outbreaks of EVD and MVD related to rapid viral antigen detection sophisticated clustering methods similar to that are available, affordable, and readily tests, and patents that are classified in the one proposed here are needed. deployable when needed.” Despite major C12Q1 (measuring or testing processes Our results also showed that network advances in the areas of detection, control involving enzymes, nucleic acids, or analysis of patent classifications can and prevention, many challenges remain. microorganisms) might include PCR-based be applied to cluster technologically The introduction of rapid point-of-care tests (Supplementary Table 3). Whether relevant patents. This technique is also tests, approval of a vaccine and conduct of the frequency of classification reflects the capable of revealing classifications that several clinical trials on experimental drugs number of R&D activities on these two connect multiple clusters and therefore for EVD was the result of unprecedented types of therapeutic activities is unclear multiple disciplines. Network analysis investment in R&D of MCMs against this because not all patent applications in has been extensively used in PLRs to disease. It is unlikely that this field can G01N33 and C12Q1 classifications are reveal collaboration networks and patent absorb the same amount of investment until related to rapid antigen detection and citations27. In collaboration networks, the next major EVD outbreak because of PCR-based tests. Furthermore, some tests the number of patents that are held in the reduction of investment by commercial

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