Can an innovative novel patent searching app strengthen your inter partes review (IPR) petitions?

Demand for inter parte reviews IPRs has been three times higher than the USPTO expected, with 3,277 IPR reviews filed in the last 3 years. This was according to a recent blog published by the director of the USPTO. The director also pointed that to dated only 12 % of claims available to be challenged in the contested patents (4,496 out of 38,462) have been invalidated in a written decision. Other claims were either not challenged, cancelled, resolved by settlement or upheld. This perhaps contrasts with the view of the PTAB as a ‘patent death squad’ as pushed by some.

The 12% ‘success rate’ suggests that the IPR process is far from a walkover. The IPR process allows the petitioner to submit either new or known prior art. Known (or previously cited) prior art is easy to find, but in some cases this can involve reviewing a long lists of prior art citations.

Similarly it can be tempting to look at the published final or non-final rejection reports for the patent to see which prior art was used as the basis of 102 (novelty) or 103 (obviousness) rejection. While this is always going to be an important step, it is entirely possible that the examiner has missed or ignored other cited patents that are also relevant, particularly if combined with other art in an 103 objection,

Alternatively the position of the petitioner can be strengthened by finding new prior art needs to be found, but this can be costly and require time and delays to find.

But what we could both, and in a matter of seconds and using a web application as easy to use as Google patent:


  • Quickly rank what can be a long list of known prior art in a manner that puts both a fresh and objective ranking of the known prior art ?
  • Find not previously cited prior art at the same time?

Would this be a new, disruptive and cost effective process for strengthening the filing IPR petitions?

The pursuit of this objective had led Ambercite to develop the process of Cluster Searching achieve both of these objectives, using a web application as easy to use as Google searching. We will demonstrate this using two case studies recent IPRs.


First case study – US7597502, Jet Blast Resistant Vehicle Arresting Blocks, Beds and Methods

US7597502 is a patent filed by Engineered Arresting Systems Corporation. This patent has a priority date of September 2001, and claims a foam unit for slowing down out of control vehicles, which include a deformable ceramic foam and a frangible cover on top of the foam. Materials referred to in the specification as frangible covers include the likes of cement board.

This patent has attracted a couple of IPRs from a company called Runway Safe.

The patent itself has 24 listed prior art citations. Of course a diligent reviewer would look at every one of these known citations, but it could be helpful to know which of these 24 known prior art citations is most likely to be similar – particularly in cases where there are a lot more than 24 prior art citations.

A search query in Cluster Searching can be as simple as entering US7597502 into Cluster Searching, and setting to date filter to only show patents filed before the patent’s priority date of September 2001. This query looks like this.


And the result? The three most similar patents in ranked order are:

  • US5193764, Aircraft arresting system, filed in 1991. This disclosed the use of a phenolic foam, but without a cover
  • US3066896  Method and means for decelerating aircraft on runways, filed in 1959. This includes a disclosure for a flexible, compressible material with a flexible cover.
  • US5902068, Vehicle arresting unit fabrication methods, filed in Feb 1997. This discloses a concrete foam, which can include a hard coat layer of a thin layer of cellular concrete having a higher dry density.

So how does compare with the examiner found? In this case, the examiner cited US4007917 as being the basis for a 103 objection. This disclosed a ceramic foam covered with a plastic film. This is also relevant, but shows the first benefit of cluster searching – a different ranking is produced (and in an objective manner), which may produce new insights on the known prior art.

And what about unknown (not previously cited) prior art? Near the top of our list of unknown prior art is:

  • US3967704 Vehicle decelerating means, filed in 1971. This discloses a bed of crushable rigid foamed material, which can include a protective covering such as paints, lacquers, bitumen and waxes.
  • GB1122297, Improvements in arrester pads for aircraft runways, filed in 1968. This discloses an arrester pad made from Improvements in arrester pads for aircraft runway, made from honeycomb construction ,..of foam material, synthetic plastics or aerated concrete, along with an upper skin,

So as you can see, Cluster Searching was able to list a series of patents that are very similar to the patent being contested, at least as similar as what is previously known.

You can also see in one of these unknown citaiton documents in a non-US document. You may be surprised how often examiners appear to avoid citing prior art outside of their own jurisdiction. In contrast Cluster Searching can be excellent at finding and ranking highly relevant prior art from other jurisdictions. This is an important benefit. 


Second case study – US6291966, Method and an apparatus for storing and communicating battery information

US6291966 was filed by Ericsson with a priority date of January 1998, and claims a battery with a separate system to log battery information, suitable for use in a mobile phone.

This patent has attracted an IPR from Apple.

The patent itself has just two listed known citations – and yet Cluster Searching was able to return many ‘unknown’ citations in a simple search



Heading the list of unknown (rior art patents returned by this query are

  • US5939856, Battery and charging system using switchable coding devices, which also discloses a battery information circuit, and was filed by Motorola in May 1997.
  • US5606242, Smart battery algorithm for reporting battery parameters to an external device. This was filed by Duracell in October 1994.
  • US6104967, Fault-tolerant battery system employing intra-battery network architecture. This was filed by 3M in July 1997.

And there are many others in this list along a similar vein.

Compared to the just two known prior art patents, this list of unknown and yet potentially relevant prior art patents could help strengthen IPR petitions for this case.


Benefits of Cluster Searching

These two case studies start to illustrate the benefits of cluster searching.

  • An objective perspective is used to rank the known prior art in a new way, so providing new insight on existing information.
  • A list of unknown prior art is also produced. In some cases this can include patents from other jurisdicitons that can also be highly relevant. 

Together, this can greatly expand the patent list for an attorney to base an IPR on. Best of all, this list can be produced in seconds from any computer, and without having to instruct others and wait for the results. Even if other search processes such as outsourcing are used, Cluster Searching can be used to augment relevant patents found by other searchers or processes.


Want to try Cluster Searching for yourself?

Cluster Searching is a very fast and easy to use web application. Free demonstrations and confidential trials are available to qualified applicants – please contact us to arrange a short demonstration and trial. You may be surprised (and impressed) by just how much time and money you may save.

Matter pricing is available to patent litigators. 


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Patent vs scientific literature – a comparison

We have had some questions recently from the likes of universities and even come companies about why they should look in the patent literature when assessing inventions,  when they could look in the scientific literature instead.

To me this is a false dichotomy – ideally a diligent searcher would look at both. But putting this aside – how do they compare? To help answer this question, I have prepared the table below:



Scientific literature

Patent literature

Total number of publications

~50 to 60 million.


This is based on an estimate of ‘up to 50 million’ published in 2010, and allowing for growth since there

~93 million  in 51 million families


As at September 2015. They may be more than this, but this figure is based on publications available online

Annual number of publications

(in 2014)

~3 million

~4.4 million in 3.4 million families

Types of disclosures

Scientific papers are published for a variety of reasons. Sometimes these disclose new concepts or inventions, often they contain new data or reviews of old data.

Patents in every case contain inventions, and are published in a form designed to make the scope of the invention easy to understand

Ease of online access

Scientific papers can be more difficult to obtain online, and where available online can require access to paid databases.

There are a number of free and paid online databases that can give full and immediate access to 93 million patent records


(ability to apply a unique identifier to support further analysis)

Scientific papers can have inconsistent bibliographical details, meaning that they can hard to index.

Patents publications have a (more or less) standardised numbering system, meaning that it is possible to fully index them

Commercial relevance

Scientific papers for a whole range of reasons, many of them for non-commercial purposes such as advancing in their academic career.

Patents cost more money to file, and so only tend to be filed for inventions where the inventor or applicant thought at the time there was commercial merit in the invention

Which organisations publish their ideas?

Generally written by staff or students working in research organisations and universities.


Companies may baulk at publishing their best ideas

Companies of all sizes, research organisations, universities and individual inventors.


Even the most secretive of companies can publish plenty of patents, for example the likes of Apple.

Language of publication

Can vary, although English language abstracts of non-English papers can be published


Even where English language abstracts are published, the rest of the paper may only be available in PDF format and machine translation may be difficult

Can vary, although English language abstracts of non-English papers can be published.


In addition the most important patents tend to be published in multiple countries, which can be multiple languages if not originally in English.


The free patent search database Espacenet now includes on-demand machine translation, to/from multiple languages for many of the patents in its database

Publication and filing delay

Can be immediate for self-publications, although peer review can take slow publication


There can also be a delay if the invention is commercialised to allow for patents to be filed first

Generally 18 months from date of filing, although some utility patents are published soon after filing.


Patents are generally filed before the commercialisation of inventions.


Looking at this table,  the benefits of also searching in the patent literature for universities and companies considering new ideas become pretty clear.

A true story can also confirm this point. A patent attorney colleague told me of a university client who had spent three years working on an invention, and had taken it to the  patent attorney to be filed as an new patent.  But a simple patent search quickly revealed knockout prior art, being some patents filed in Japan.

The inventor was upset of course – and also surprised. He recognised the name of the Japanese patent filer, as being a leading academic in a related field. The university inventor was fully across the scientific literature in the specific field he was inventing in, but had not seen anything published by the Japanese academic in this specific field.

The reason why is that the japanese academic had not published any scientific papers in the area of his patents. Instead he had chosen to protect his obviously valuable invention with patents.


Is patent searching difficult?

Patent seaching can be as simple and fast as using Google. In addition Ambercite has developed Cluster Searching, which in a matter of seconds can find similar patents to relevant patents you have already found. Cluster Searching is available for a free and confidential trial – please contact us to arrange a demonstration.


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Do Segway have a valid patent over the self balancing wheel? A 1 minute patent search casts doubt on this.

Verve has just reported that Segway, maker of the Human Transporter




has just sued Hovertrax, maker of the popular Solowheel,




for infringement of five of their patents.

These patents are 

  • US6302230
  • US6651763
  • US7023330
  • US7275607
  • US7479872

The complaint specifically notes that: The ‘230 patent discloses and claims a personal transporter with a balance monitor and a method for using such a transporter”. These patents are all owned by the company Deka Products LP.

The earliest of these patents, US6302230 for a Personal mobility vehicles and methods  was filed in June 1999. But is this patent valid?

For a patent to be valid, it must be novel and inventive over the ‘prior art’. As part of the patent examination the examinder does a comprehensive search for earlier patent and non-patent publications. The applicant too needs to declare all of the prior art they would have known about.  In this case the US630.. patent has 126 prior art patents (backward citations) listed. These include 16 patents identified by the examiner (after an extensive search no doubt) and 110 nominated by the applicant.

Given this extensive existing prior art search, we would expect that finding new and relevant prior art would take many hours if not days?

This would of course depend on the method you use to search. Ambercite has recently developed Cluster Searching, which determines similar patents using algorithms that consider the similarity of patent citations to patents you may be interested in. The search returns a combination of ‘direct citations”‘ (already known) and indirect citaitons (new and not already cited prior art).

Arguably all of the known prior art has already been considered by the examiner, so it is the indirect prior art that may be most interesting.

Cluster Searching can work best if we start with a cluster of similar patents, so in this case we will use as starting patents the five asserted patents. We will restrict results to patents filed before the priority date of the US6302.. patent of June 1999. The search query looks like this


The results initially look like this, which shows you the most similar patents in order of likely similarity (only the five most similar are shown). Many of these are also filed by Deka



Of note is the last column, which shows whether the patent was an indirect or direct citation. From above we are mostly interested in indirect citations, so we will sort the results by this column (results can be sorted by clicking the column heading). Once sorted by this column heading, we also sort the first column Rank so that it the patents are sorted by the most likely be similar, to the worst. In the image below, only the four most likely to be similar patents are shown



Of note is the fourth listed patent, namely WO1998006117, filed for a  Process for stabilizing a single-axle wheeled vehicle and vehicle so stabilized. This was published in 1989, and discloses a:

A single-axle vehicle with one or two wheels arranged on the axle is characterized by high manoeuvrability. To stabilize the vehicle, a sensor produces a signal corresponding to the actual position, which controls in a closed control loop the direction and magnitude of the additional forces exerted on the vehicle


Or in other words, a uniaxle vehicle with a balance monitor. This patent is clearly relevant to the inventive concept of the Segway patent, and yet has not been recognised as such by any of the prior art searches. We do not know why, but this may be due to the inherent limitations of keyword searching.


Want to try Cluster Searching for yourself?

Cluster Searching is a very fast and easy to use web application. Free demonstrations and confidential trials are available to qualified applicants – please contact us to arrange a short demonstration and trial. You may be surprised (and impressed) by just how much time and money you may save.

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How to quickly find potential licensing options for patent portfolios – Case study on Aurora Algae

Licensing managers are often called upon to identify potential licensing options for portfolios of patent they might manage. There are a variety of ways of doing this, but perhaps the easiest way, and a very simple starting point, is to start with the patents themselves.

Ambercite has recently developed Cluster Searching, which is a web application for finding the most similar patents to one or more starting patents. This is done using advanced analytics which are applied to patent citations. Each patent citation is an opinion by an expert (being the patent applicant or examiner) that two patents are similar. The advanced analytics within Cluster Searching then combine these opinions to work out which clusters of patents are most similar to the starting patents, irrespective of the keywords or patent class codes that are use. Date filters can also be applied to focus the search. The search can take seconds to run working from the patent numbers themselves.

As an example of this, consider Texan company Aurora Algae, which builds and operates algae farms, as shown below. Aurora claims that its algae can be used to produce pharmaceuticals, health foods, fish feed and biofuels.



Aurora have filed a significant number of patent applications to protect their technology – we estimate that in the key US market they have filed 14 granted patents and 21 patent applications. There are also 9 WO patents and 2 EP patents.

EP, US and WO patents or patent applications are ideal starting patents to be used for Cluster Searching. These can be pasted and copied into a data entry box process, as we have done in the image below, which only shows some of the known Aurora patents. Note the selection of a date filter – in the case we limited the search for similar patents to those filed after November 2007, being the filing date of the earliest Aurora patent we found. We also put an upper limit of the most similar 1000 patents.



The five most similar patents found, out of the 408 returned by this query, are shown here (click on image to get full size version):



You will note a series of columns:

  • Rank shows our overall ranking of results
  • Similarity shows the predicted similarity of the patents found to the seed patents
  • L.P. is short for ‘Licensing Potential’. This value suggests which patents found have the best combination of similarity to the seed patents, and commercial importance of the patent found, to be worthwhile investigating further as a licensing option. Higher values are better, and Licensing Potential values for different patents owned by the same applicant can be added together
  • Number is patent number, Owner and Title are exactly that, and Filed is filing date
  • Citation tells you if the patents found have direct citation connections to the starting patents, or instead are indirect ‘citations of citations’.  Both can be relevant. In this case, we returned 106 direct citations and 302 indirect citations. The highest ranked indirect citation was US8967402, filed by Solazyme for a process to convert algae into biodiesel.
  • Amberscore is our citation based prediction of the commercial importance of a patent. Higher values are better, and anything above 1 is above average.

Of these values, Licensing Potential is perhaps the most efficient way of reviewing the results. If we add the values together (this is easily done by exporting the results table to Excel, and using an Excel function such as Pivot-tables to add together Licensing Potential values), we can see that the following companies are among those with the best Licensing Potential for the Aurora patent portfolio:


Total Licensing Potential from Aurora patents

Number of similar patents found

About the company

Haliae   (Arizona)



“Heliae is an applied life sciences and technology company focused on researching and developing algae and other cutting edge biological platforms for commercial scale production of useful products.”

Solazyme (California)



“Starting with microalgae, the world’s original oil producer, Solazyme creates new, sustainable, high-performance products. These include renewable oils and powerhouse ingredients that serve as the foundation for healthier foods; better home, personal care and industrial products; and more sustainable fuels.”

DuPont Pioneer



Producer of glyphosate resistant seeds – and Aurora has developed glyphosate resistant algae

Genifuel  (Utah)



“Genifuel Corporation produces equipment to make renewable fuels from wet organic material by a highly efficient process known as Hydrothermal Processing (HTP).”

DSM (Netherlands)



Has filed patents for the production of fatty acids from algae

Sapphire Energy (California)



“Sapphire is a venture capital backed company founded in 2007 for the purpose of growing and processing micro-algae into products that serve very large and diverse markets where the unique attributes of algae provide valuable solutions.”

Bionavitas (Washington state)



“Innovations for more efficient growth of algae for use in biofuels, nutraceuticals, and environmental remediation.”

Livefuels (California)



“LiveFuels taps the power of natural aquatic life to produce renewable fuels from algae.”

Algae Systems (US)



“Algae Systems’ technology captures what others discard -untreated wastewater and atmospheric CO2 – and produces renewable fuels and fertilizers, leaving behind only clean water for beneficial reuse”

Pond Biofuels (Ontario)



“Pond Biofuels converts raw smokestack emissions from heavy industry into algal biomass”


As you can see, a range of companies using similar technologies is quickly found. In most cases the links back to the technologies being patented by Aurora Algae are quite obvious.

The link to Du Pont Pioneer is less obvious, but comes because a number of Aurora patents deal with the use of glyphosate to help manage weed growth in algae farms – and Du Pont Pioneer is filing patents and developing technologies for the use of glyphosate to help manage weed growth in agriculture. This example proves how this sort of analysis can easily be used to find ‘parallel’ technologies, i.e. similar technologies that may not be picked up conventional patent searching – but still can be relevant to your licensing objective.


How does this analysis compare to other patent searching techniques?

There are other vendors that offer searching systems that can be used to find licenisng opportunites. In comparison to these other systems, our customers have been telling us that Cluster Searching is:

  • Easy to use – there is no need to spend time building complex queries that require you to try to guess what the most appropriate queries are
  • Easy to learn – There is no need to spend many hours learnng how to use complex multi-screen systems. Instead Cluster Searching simply requires a list of starting patents, which are often to easy find. This in turn can lead to much lower training costs 
  • Cost effective – Ambercite offers corporate subscriptions that are very competitive compare to some other searching systems, and allow unlimited usage within your corporate environments
  • Capable of finding patents missed by other techniques – which comes from being to able to avoid the limitations and risk of keyword searching


Want to try this for yourself?

Ambercite offers free and completely confidential two week trials to Cluster Searching – please contact us to arrange a demonstration and trial. Testimonials for Cluster Searching are found here, including:

“Ambercite Clustering has managed to create a tool to enhance chemical patent due diligence in a remarkable way…revealing art which may cover compounds in discovery within claims of a generic scope.  Congratulations!” – Patent Analyst, global pharmaceutical company, USA


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Why can’t patent searchers rely on keyword or semantic searching to find all relevant patents?

Most patent searching is based on keyword or semantic searching. I understand this fully and use keyword searching a lot myself.  

However from long experience, I have learnt that relying on keyword searching alone will see a lot of highly relevant patents missed or incorrectly ranked in a relevancy list of patents found.  For this reason, we recommend to all searchers that they supplement their keyword or semantic searches with a citation based search such as Cluster Searching (where the seed patents for the Cluster Search could be the best hits they find using other search methods). 

There are four good reasons for this.

1) Patent applicants can be very inconsistent with their use of technical words. 

2) Semantic or keyword searching can return thousands or hundreds of thousands of irrelevant hits

3) Semantic searching can be misled by different languages 

4) Even if keyword searching finds relevant hits, the order of result can be misleading


1) Patent applicants can be very inconsistent with their use of technical words 

As one example alone, consider this following list synonyms for the humble cardboard ‘box’ :

  • carton
  • carrier 
  • container
  • package 
  • packaging
  • receptacle
  • case 
  • pack  
  • crate

In some cases, it might be possible for search engines to understand every possible synonym for some technical concepts, but this is unlikely for all technical concepts. As one real world client example from a real world example a key prior citation for a patent that referred to ‘carbon dioxide’ was missed by USPTO examiners and a major patent law firm because it instead referred to the very rare synonym ‘carbonic acid gas’.

In contrast, the citation searching approach used by Cluster Searching relies the expertise of a number of patent examiners and applicants in the immediate field to recognise rare synonyms for technical concepts  – this greatly increases the probability that at least one of the searchers makes the link between patents that would be missed by semantic analysis alone.


2) Semantic or keyword searching can return thousands or hundreds of thousands of irrelevant hits 

Again if we return to the simple example of cardboard boxes, a search for prior art based on the main technical keywords used for cardboard boxes (for example ‘box’, ‘lid’, ‘flap’, etc) will return thousands or tens of thousands of patents – almost all not very relevant to the patent application that you may be looking for – as is shown by the results for this query shown by the seach engine “The Lens” 



In order to deal with these large amounts of irrelevant hits, searchers and examiners are forced to apply assumptions about which keywords are important – and every such assumption risks filtering out irrelevant patents.

As an example of this, consider the feedback from a patent examiner for a major patent office after trialling Cluster Searching:

The top ranked [prior art] patent, USxxxxxxx, was very good because it found an element that is hard to search for, i.e. ‘independent power settings’.  The ‘independent power settings’ are hard to search for because searching for something like “power near2 settings” would return several thousand hits and most of them would not be for independent power settings and limiting that search with an adjective like “independent” would filter out a lot of good results.  And it’s amazing that it came up first in your search…   .”  – Patent Examiner of a world leading patent office


3) Semantic searching can be misled by different languages

Semantic based searching is much less likely to pick up similar patents in different languages – self-evidently semantic searching will likely struggle to recognise synonyms in foreign languages. Returning to the earlier, it is worthwhile considering some of its foreign language equivalents for the word ‘packaging’.

  • verpackung             (German)
  • conditionnement     (French)
  • imballaggio             (Italian)
  • embalaje                 (Spanish)
  • パッケージング         (Japanese)
  • 包装                         (Simplified Chinese)
  • 포장                         (Korean)

In contrast, we like to believe that Cluster Searching is ‘language agnostic’ as it relies on the ability of patent examiner to recognise similarities between patents that may even be filed in foreign languages. 


4) Even if keyword searching finds relevant hits, the order of result can be misleading

Semantic based searching tends to rank results based on the overall similarity of keywords. So even if a keyword semantic search tool will recognise that a box is also a carton and a carrier, it may rank patents that refer to ‘cartons’ and ‘carriers’ as being much less relevant than patents that refer to ‘boxes’. However In practice, many of the patents that refer to cartons may be much less similar than many patents that refer to boxes.

In contrast, patent examiners and applicants will identify and cite similar patents even these patents use different synonyms for the same concepts.



For all of the above reasons, we recommend to all clients that they use Cluster Searching to complement their existing semantic or keyword searching processes. Case studies have shown that it will produce results that are different and yet still very relevant, when compared to conventional searching. An example, consider the case study found here. While originally published in August 2014, these results are still very applicable to Cluster Searching. 

An example of a query from a recent blog on Cluster Searching is found below:




But doesn’t this produce a lot more work?

Cluster Searching has been carefully designed to be very easy and fast to use. You can obtain and review usable results in minutes. Considering the importance of many patent searches to their clients, and the genuine importance of not missing relevant patents in these searches, we think that this few minutes is well worth spending.


Want to know more?

Ambercite offers free and completely confidential two week trials to Cluster Searching – please contact us to arrange a demonstration and trial. Testimonials for Cluster Searching are found here, including:

“Ambercite Clustering has managed to create a tool to enhance chemical patent due diligence in a remarkable way…revealing art which may cover compounds in discovery within claims of a generic scope.  Congratulations!” – Patent Analyst, global pharmaceutical company, USA

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Viagra – boosting the patent literature

Viagra, which is a trade name for the drug sildenafil, has been a major bestseller for Pfizer earning it up to US$2 billion annually. Sildenafil was originally tested for use in dealing with hypertension, but the side effects on penile erections were soon noticed. 

The first patent for sildenafil was US5250534, which was filed in 1992, expired in 2012 and covered sildenafil itself, but netheir its two family members cover its effect on erectile disfunction or impotence. Pfizer followed up this up with US6469012, filed in 1994 for Pyrazolopyrimidinones for the treatment of impotence and hence clearly targeted at impotence. Equivalants to US6469012 have been filed in a number of other countries, including in Europe and as a PCT patent. US6469012 is slated to expire in 2019. 

Not suprisingly given the huge commercial impact of sildanafil, there has been many later patents claiming similar compounds or their applications. There are various means of identifying these later patents, but among the easist method is the recently released web application of Cluster Searching. With Cluster Searching, we can run instant patent searches using little more than the numbers of some relevant ‘seed patents’. Cluster Searching uses advanced altogorihms that looks for similarity in citaiton profiles to suggest similar patent to one or more starting (or seed) patents, and then ranks the found patents according to predicted similarity. The overall concept is shown below:



In this case some good seed patents would be US5250534, US6469012, and the EP and WO equivalents of US6469012. Since we are looking for later patents, we might limit the search to patents filed after the priority date for US5250543, which is June 1990.

The resultant query would like this (see below), and takes a few seconds to run.


This query produced over 1700 similar direct and indirectly results. Along with metrics for similarity (to the seed patents) and likely commercial importance (our metric AmberScore) we also calculate “Licensing Potential“, which ranks patents based on both similarity and AmberScore. Licensing Potential values can be added together, and different patent owners can be compared based on total AmberScore values.

This is what we see below.



Not surprisingly, Pfizer was the leading owner of these later patents – it is well known for pharmaceutical companies to try to evergreen their own patents. Behind Pfizer came a mixture of large pharmaceutical companies, led by Boehringer Ingelheim, but also including Bayer, OSI Pharmaceuticals, Merck and GSK.

It can also be helpful to look at the leading patent (in term of Licensing Potential) filed by each of these companies. These are shown in the table below.


Total Licensing Potential

Number of direct and indirect forward citation patents

Forward cite patent with highest licensing potential


Filing date

Direct forward citation?

Licensing Potential of leading patent





Pyrazolopyrimidinone antianginal agents




Boehringer Ingelheim





8-[3-amino-piperidin-1-yl]-xanthines, their preparation and their use as pharmaceutical composition









2-phenyl substituted imidazotriazinones as phosphodiesterase inhibitors




OSI Pharmaceuticals




Lactone compounds for treating patients with precancerous lesions








Xanthine phosphodiesterase V inhibitors




Vivus Inc




Administration of phosphodiesterase inhibitors for the treatment of premature ejaculation








Use of CGMP-phosphodiesterase inhibitors to treat impotence








Delivery of caffeine through an inhalation route




Eli Lilly




Tetracyclic derivatives, process of preparation and use








Nitrosated and nitrosylated phosphodiesterase inhibitor compounds, compositions and their uses





It should be noted that not all of these patents will be directly related to sildenafil patents. However each patent has both a Licensing Potential for a reason, and each should have something in common with sildenafil patents – and each has been filed after the original priority date for the sildenafil patents.

It shoudl also be noted that the patents are a combination of directly and indirectly connected patents – so not all of these patents would have identified by a traditional forward citation analysis.


Want to know more?

This simple example shows how easy it can be to explore the patent landscape following on from some important patents such as the original patents filed for sildenafil . There are many other ways we could have run this analysis – for example we could have included some of later patents filed by Pfizer for sildenafil. Nonetheless, this does show what is possible.

Ambercite offers free and completely confidential two week trials to Cluster Searching – please contact us to arrange a demonstration and trial. Testimonials for Cluster Searching are found here, including:

“Ambercite Clustering has managed to create a tool to enhance chemical patent due diligence in a remarkable way…revealing art which may cover compounds in discovery within claims of a generic scope.  Congratulations!” – Patent Analyst, global pharmaceutical company, USA 

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