Try Ambercite patent search today! Online trial access now available, no payment required

Try Ambercite patent search today! Online trial access now available, no payment required

June 7 2018 Ambercite now offers the ability for new users to register online and start finding patents Amberc […]

Who invented Siri? Apple sued for patent infringement – who else might be in line?

Who invented Siri? Apple sued for patent infringement – who else might be in line?

Did Apple invent Siri? This is perhaps a conversation for another time, but movie fans might remember the all […]

Spending money on patent databases? What are you paying for and why?

Spending money on patent databases? What are you paying for and why?

Here at Ambercite we spend a lot of time talking to clients about our software. And because some of us are searchers ourselves, we also use and assess a range of other patent databases. And this is a good thing, as a different databases can give different results, and a broad range of perspectives can give the best results.

Based on all of this, we have picked up a bit of experience on how to assess a patent database – and this could be helpful for other people.

So what factors should be used to compare patent searching databases? We would suggest the following:

  • Subscription price: These can range from free for some popular databases, up to tens of thousands of dollars for some specialised databases.
  • Data coverage: The simplest databases can be for one jurisdiction only. A number of databases are based on global data available from the EPO (as per their Espacenet database), while some others supplement this with data from some of the national patent offices.
  • Available search options. The normal search options include keyword, ownership and class codes, and these are available from some free databases such as Google patent and Patentlens. Other databases allow semantic searching, where algorithms try to predict similarity based on shared terms or concepts. Ambercite takes a completely different approach, as will be explained below.
  • Ease of use in searching: Some databases are ridicously easy to use, while others get progressively more complex. One subscrciption database I have used in the past was particularly difficult to use because while it did have an internal logic, it would take me a few minutes to remember each time what this internal logic was. Eventually I stopped using this database for this reason.
  • Ease of use in reviewing results:. Some databases provide a simple list of results, while other provide a large amount of detail. There is a trade off here – more data can be slower download and review times.
  • Graphical perspectives: A number of databases include the ability to produce graphical perspectives of the results, often automatically generated. However – the limiation with automatically generated perspectives is that they can be of limited value, as the underlying data can be of mixed quality – for example in terms of relevance to the purpose of the study, or ownership accuracy. 
  • Overall speed of a patent search: How long does it take to run a search from start to finish – including formulating a query, reviewing the results? This can vary dramatically, particularly if you are forced to review what can be thousands of results in an unordered fashion, or a not neccessarily helpfully order – such as publication date for example (‘but I just want the best prior art – not the most recent…)
  • Confidentially: Only you should know what you have been searching for.


Having established this – how does Ambercite stack up in this comparison?

We would suggest very well:


How does Ambercite compare?

Benefits to users

Subscription price

Cluster Searching is available at a very competitive price per user, particularly for groups of users

High return on investment. Finding just one additional and relevant patent can more than pay back the subscription cost

Data coverage

Ambercite uses the same global data as found in the EPO patent database Espacenet. While this is not 100% of available patents, published citations are rarer for the missing patents

Broad coverage

Available search options

Ambercite is completely different to every other database out there, in that it searches for similar patents to one or more starting patents based on applying advanced algorithms to over 100 million citation links in our database. By doing so it can uniquely find relevant patents with unexpected keywords or class codes.


Finding additional patents means more informed and lower risk decisions being made as a consequence of your decisions.

Ease of use in running searches

Invalidation, portfolio review and  licensing searches can simply start from the patent numbers you would already know. Other searches can based on results found in a simple search of other databases

Less time spent formulating queries, and less chance of erroneous assumptions affecting your results.

Ease of use in reviewing results

Results in Ambercite are listed in order of similarity to the query patents, along with title and owner information. Hyperlinks provide detailed information for each patent listed

Less time spent reviewing patents 

Graphical perspectives

The Amberscope option available with Cluster Searching can provide a very unique perspective of the relationship of a patent to similar patents

Added insight into the importance of patents that you find

Overall speed of a patent search

Working from a good starting patent (for example a patent you may trying to invalidate) a search can take seconds to set up and run – there is no need to develop a query. Results are ordered by likely similarity, and you can quickly scroll through the simple list, or export the results into other applications.

Less time searching can mean more time doing other things – so creating extra value


Ambercite does not record any patent searches or lists of results

Your searches can never be recalled from the Ambercite server


We should note that Ambercite Cluster Searching is best seen as a complement to your other search tools. And why not? I very rarely meet a patent searcher who only uses one patent database – just like doctors rarely really only on their stethoscope alone for diagnosing patients. 

In summary, when we look at the things that matter when choosing a patent database, Ambercite Cluster Searching can have substantial benefits – particularly the value of finding more of the patents that matter due to its unique searching approach.



Read More

An easy way to find keywords for your patent searches

An easy way to find keywords for your patent searches

Here at Ambercite we often talk about the limiatoins of keyword searching – but in fact we are happy to acknowledge that both conventional and Cluster Searching can be helpful in finding relevant patents – as suggested by the image below


Do you need insurance for your patent searches?

Do you need insurance for your patent searches?

We all know that patent searching matters. The results of our searches can affect what can multi-million investments in new products, outcome or settlements in litigation, expensive patent filings, or the reputation and repeat business of your organ…

Was the outcome of the CRISPR patent dispute predictable from advanced patent analytics?

Was the outcome of the CRISPR patent dispute predictable from advanced patent analytics?

CRISPR, which is short for Clustered Regularly Interspaced Short Palindromic Repeats, are segments of DNA containing repetitive base sequences. A simple version of CRISPR, known as CRISPR/Cas9 has been modifed to allow addition or removal of genes, so editing the genome of a cell. This ability to edit a genome is a big deal, and not surprisingly was the choice of Science magazine for the Breakthrough of the Year in 2015.


Not surprisingly with such a potentially important invention, there have been disputes over ownership. In particular there has been a high profile dispute between the Broad Institute (MIT) and University of California.  The University of California had filed first, with a priority of date of May 2012 for their published application US20140068797, which is yet to be granted.

 The Broad Institute first filed a little later in December 2012, but then pushed the examination process so that the first of their patents was granted in April 2014. Since then the Broad Institute has gone onto to receieve more than 50 granted patents for this technology.

In response, the University of California launched a patent interference process to determine who was the first inventor of this technology.  Given the nature of patent litigation in the US, and the commercial value of this technology, it is more than than possibloe that several million dollars might have been spent collectively by the parties in legal fees in relation to this case.

On 15th February the USPTPO handed down its decision on this case, finding that there was no intererence-in-fact between the patents, namely US20140068797 and a group of patents filed by the Broad Institute in December 2012:

..we conclude that the parties’ claims are not drawn to the same patentable subject matter and that there is no interference-in-fact between them.

There is a 51 page judgment to this effect, and here at Ambercite we will leave ithe judgement and others to explain the reason for this.

But we were curious – what would advanced patent analytics tell us about this case? 

To answer, we will use our the Family Cluster Searching patent analytics tool. This can find similar patents to one or more ‘seed patents’. Essentiallly all of the patent citaitons in the area of a patent or a group of patents are combined together to identify these similar patents. Because every patent in this area may have its own search report, this network represents the opinion of every applicatn and every examiner in this area about which individual patents are similar. 

We call it ‘Family Cluster Searching’ because each patent in our network is  in fact a family of patents. And so even a single point in the network can combine the opinions of say the PCT patent examiner, the US examiner, the EP, JP and even Chinese examiners. A lot of data is combined in this ‘collective wisdom approach, and this helps to produce a statistical robust approach. 

So what can advanced patent analytics tells us about this case?


Was the potential for ligitation predictable?

Family Cluster Searching comes with the ability to identify similar patents to one or more starting patents. To answer this question, we took the Broad Instittute patents mentioned in the litigation, and ran a search for the most similar patents.

This query looked like this:



Note that we had changed the application # 14,704,551 to its published version US2015024710 – and that we had requested the most similar 2000 patents

And what did we find?

Not suprisingly, the three most similar patents found were are filed by the Broad Institute



And this continued down to the 9th position. But in this list of 2000 patents, there are many other similar patents, such as these ones:


And this list goes all the down to position #1993



But the real question is, as hinted by the image above, is ‘does this list include the University of California patent?


To answwer this questoin run a filter for patents filed by the University of California:


Which produces this list of patents:


In fact the full list is somewhat longer than this, but at  the top is the entry WO2013176772.

This is in the same family as US20140068797, which is the  published form of the litigated patent 13/842,859. And according to this analysis, there is a total similarity score of 102.5 to the Broad Institute patents shown/ This is a relatively high figure, and suggest strong similarity between the Broad Institute patents and the University of California patent. 

So no surprises about the litigation then – they are in very similar fields. The University of California patents was the 15th most similar patent, and in fact the second most similar non-Broad patent filed, with only US9023649 filed by Harvard in December 2012 only being ranked higher 11th place, with a slightly higher score of 106.5.

Of course, this is a bit of a ‘so-what’ analysis – a number of different pathways would have produced a similar outcome, including the litigation history itself. But – this analysis was quick and simple, and so a useful example of the potential of patent analysis to at least identify the potential for litigation (or licensing), based on patent numbers alone. This can reduce the time and cost needed for other, more time-consuming and expensive forms of analyis

So who else filed the most similar non-Broad Institute patents?

To answer this question, we can filter out the Broad patents:



Which leads to the following list:



So a big range of applicants. From these results as a whole, we can make a range of analysis

Who has the most commercially similar patent portfolio?


We can predict this from our Licensing Potential metric, again which is based on the Broad Institute patents listed in the ligitation:



Sangemo Therapeutics describes itself as “Developing the most advanced and precise genomic medicines“, while Arbustus Biopharma is primarily focused on Hepatitus B, that is also  developing a pipeline of Non-HBV Assets that leverage our expertise in RNA interference (RNAi) therapeutics

Perhaps what is most surprising is that the the patents belonging to the University of California have a comparably low Licensing Potential compare to some other companies.

We should note that this analysis, like any analysis, is limited by the assumptions used. In this case one of the key assumptions is that the Broad Institute portfolio is the patents listed in the litigation. These were all the early patents filed by the Broad Institute, and they have filed many since. Ideally we would rerun this analysis with the more recent Broad Institute patents, but such an analysis would sit outside the scope of this blog.


What are the most similar prior art patents? 

By looking for earlier priority date patents filed prior to December 2012, and say looking for patents filed after 2002 to allow for the rapid advances in this field, we would suggest that the most similar prior art patents would be:

Patent family (representative patent)





Priority date






Methods and compositions for RNA-directed target DNA modification and for RNA-directed modulation of transcription







Transgenic animals secreting proteins into milk







solation of exogenous recombinant proteins from the milk of transgenic mammals







N[ omega ,( omega -1)-dialkyloxy]- and N-[ omega ,( omega -1)-dialkenyloxy]-alk-1-yl-N,N,N-tetrasubstituted ammonium lipids and uses therefor







RNA-directed dna cleavage by the Cas9-crRNA complex







Targeted genomic modification with partially single-stranded donor molecules







CRISPr-based genome modification and regulation







Methods and compositions for delivery of biologics







Multiple domain proteins







Methods and compositions for targeted cleavage and recombination




Not surprisingly, the litigated University of California patent was at  the top of the list, but there were many others – and this is only a top 10 list. 

Note too that the list comprised a mixture of ‘Known’ and ‘Unknown’ citations. An unknown citaiton is a patent family which has never been cited against the patent family being examined. While not all unknown citations in a Family Cluster search are relevant, many are


Next steps?

This is what we could learn from just Family Cluster Search. Just like any other searching system, we recommend running a range of different queries to end up a range of different results – you may be suprised what you can find. 

Read More