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Recent and valuable discussions on Linked In regarding patent quality has reminded us that timing can be all important when assessing patent quality. The main elements of timing in relation to patent analysis are:

• Timing with respect to the expiry date of the patent. Patents have a maximum (except for some pharma patents) term of 20 years, but it is still possible to assert patents after they have expired, providing the assertion relates to commercial activity by the alleged infringer prior to the expiry date (Obviously an injunction becomes a moot point after expiry).
• Timing with respect to the commercial success of the patented technology. Some technologies take years to reach significant commercial volume. As just one example, Paice Corporation, the developer of the hybrid car patent that has been successfully asserted against Toyota and Ford, filed this patent in 1992, which happened to coincide with a long term low in oil prices. By coincidence, Toyota started developing their hybrid technology at about the same time, but it was 1997 before the first Japanese hybrid Toyota was sold, and 2001 before the Prius was available outside of Japan. In very recent times hybrid drive trains have been commercialised by a number of manufacturers. However Paicie may miss out on the bulk of this boom, with their key US5343970 patent due to expire in 2012 (although Paice have other patents they may assert).

The first of these elements should be straight forward for any patent analysis, and can be determined by comparing the expiry dates of the patents being analysed to the commercialisation timeframe of the patented technology.

The second factor can be analysed as well. Advanced patent analysis techniques such as NPA can be used to group patents into clusters of patents of related subject matter. Patents cost money to file, so a large amount of activity in a given area means that the area has  value. If lots of patents are being filed in a cluster at around the same time, this means that that area become commercially interesting for the patents to become commercially valuable. Since clusters in an NPA analysis can be dominated by highly ranked patents, we can start to undertand when the key technologies in each area have been developed, and this should correlate with a commercial or technology boom in this area.

The value of this type of analysis becomes very clear when we consider a comparison of the patent timelines for the top ranked patents in a few different technology areas we have looked, see the figure below. In this figure, we have identified when the highest rated patents in a given analysis were filed, and grouped these filing dates (after 1990) into 5 year groups. It is easy to seen when each of these area has attracted the most attention. 

This figure shows that:

• The three clusters from the smartphone report occupied three of out the top four positions. This is not surprising when we consider the recent innovation and legal developments in this area.
• Hybrid car patents were second on this list. Hybrid cars have become a lot more popular in recent years, and more importantly a range of car manufacturers are now introducing hybrid cars to help meet fuel efficiency targets set by governments.
• There were a lot of recent patents for Alzheimer's treatments. Although Alzheimer's has been known for over a century, there has been a large amount of medical research done in the last decade.
• The ICT project we looked at was for a very new area of technology, and hence there was nothing filed of consequence prior to 1995. However activity had appeared to have slowed down in this particular area of technology in the recent years. This shows that this particular technology had a relatively narrow peak of activity.
• The mining project had a number of older patents, but then an increasing number of newer patents. The reason for this is there was a new development in this particular tecnnology, and this has catalysed more recent activity.
• The heavy engineering project had a similar story to the mining project, but the new development peaked in the period between 1995 to 1999, when a lot of the key patents were filed.
• In contrast, the food technology project was in a very mature area, which was not surprising given the specific subject matter (which I can't discuss in detail, but I can say it was for a type of food that many of us eat almost every day).

Having said all of that, this comparison of technology timelines should be considered an example only of what is possible, as all of this data was collected in slightly different ways (apart from the three smartphone patent clusters). Nonetheless, this gives a good example of what might be discoverable from a NPA patent timeline analysis.

The recently published NPA white paper on Alzheimer's patents analysed the 48,000 Alzheimer's patents in a variety of ways. But which patent applicants had the strongest patent portfolios?

Traditionally such analysis has been done by counting the patents filed by different applicants. However it is self-evident that all patents are not equal in value or importance, and NPA uses the wealth of information contained in the citation links between patents to rank the expected relative value of patents. In this particular study we identified the leading 2,153 patents based on their strength of citation connections, and ranked all of these patents in order. A number of these patents were found to have equal rankings (for example, there were two 5th ranked patents, two 16th ranked patents, etc) meaning that there were 915 unique patent rankings. The highest ranked patent was given 915 'patent points' in our analysis, the second ranked patent 914 points, and so on until the last ranked of the 2153 leading patents was assigned 1 point. By adding up the patent points for given patent applicants, it is possible to rank patent portfolios in a way that takes into account the relative quality of the patents in these portfolios.

We also aimed to agglomerate the patent portfolios of subsidiaries of larger patent owners into the parent company. While is was impractical to determine the ultimate owner of all 2153 patents, we did identify the current ultimate owner of all of the largest portfolios. For example, Wyeth patents are now all controlled by Pfizer, and there are many other examples of similar consolidation. Similarily we combined all patents owned by agencies of the US Government under the one owner "US Goverment Agencies".

But enough of the background - what did we find? Details from the top 20 portfolios are shown in the table below.This shows the 20 patent applicants with the strongest portfolios, their relative strength in relation the leading applicant, the number of patents in the leading 2153 patents, and some details of their top ranked patent in this study. There are also some details of the patent cluster (grouping of similar patents as determined by the NPA algorithms) where the leading patent is found, along with the most important cluster for each applicant (further details of these clusters are found in the white paper).

Many of the leading applicants, such as Pfizer, GlaxoSmithKline, Merck, Astrazeneca, Johnson and Johnson, Bayer and Bristol Myers Squibb are well known pharmaceutical companies and their placement in this table may not surprise observers. The position of Pfizer and Johnson & Johnson is further enhanced by their share of the portfolios jointly owned along with Elan.  

There are also some smaller and more specialised companies with strong portfolios. These smaller companies are led by Elan, which describes itself as 'a neuroscience-focused biotechnology company headquartered in Dublin, Ireland', and which owns a strong portfolio of Alzheimer's patent both by itself and together with larger pharmaceutical companies. Other smaller companies include Vertex Pharmaceuticals and Acadia Pharmaceuticals, both of the US, Boehringer Ingelheim of Germany, Bellus Health of Canada, and Teva Pharmaceuticals of Israel.

The Alzheimer's NPA report also noted that the clusters formed into two 'Groupings' of clusters (best seen in the Alzheimer's NPA landscape plots). One grouping of clusters were related to the Amyloid protein, and the second grouping to the Tau protein. In the figure below, the leading ten applicants in the above list are compared in terms of where their patents fall within these two Groupings.

This image shows that the large pharmaceutical companies Pfizer, GlaxoSmithKline and Merck (and to a lesser extent AstraZeneca) all have patent portfolios divided between the two Groupings of clusters. In contrast, the other applicants in this top ten list are focussed in just one of these groupings. Elan (and its partners) and Acadia Pharmaceuticals are both focussed on the Amyloid Grouping, while Vertex Pharmaceuticals is focused on the Tau Grouping.

But will these patent portfolio's translate to commercial success? One of the pleasing results from the Alzheimer's NPA white paper was the relatively young (compared other NPA studies we have done) age profile of the leading patents, which suggests a lot of recent research and related patent filing activity. The flip side of this recent activity is that even the more promising of these patented drugs will still be going through drug trials, and so we can only wait to find out which of these patented drugs are commercially successful.

Invention never happens in a vacuum, and instead tends to build on earlier work done by either the inventor or other inventors. It is possible to track this 'knowledge flow' by looking at patent citations, which may be among the most reliable sources of innovation related data. While some other patent analysis techniques also analyse patent citations, NPA adds two improvements to this process:

• Only citations between patents in the study of interest are considered. Some broad patents have disclosures that may be relevant to a number of different fields. However, NPA is focused on finding the strongest patents within a specific field of interest, and so only takes relevant patent citations into account.
• In any case, patent citations are not treated equally. NPA has a process for weighting patent citations, and these weighted patent citations are used when assessing the relative importance of patents.

There are many other potential applications for knowledge flow analysis, including patent litigation. In the recently released report Clearing the fog: Patenting trends for the treatment of Alzheimer's disease, we have investigated which patents have had the strongest influence on other patents in this field. Clearing the fog identifed 23 clusters of patenting activity, which in turn formed into two groupings of clusters, which we names the Amyloid Grouping and Tau Grouping in relation to the proteins these patents were targeting. The top three foundation patents, or most influential, in each grouping of clusters is shown in the Table.

This table shows some interesting results. The most influential patent in the Amyloid Grouping, the now expired US4666829 filed by the University of California, discloses the Alzheimer's Amyloid Polypeptide (AAP) which is the precursor of beta amyloid, and had 94 forward citations in the dataset. The next most influential patent was the number one ranked NPA patent of all.

In the Tau Grouping, the two most influential patents, US7265148 and US7332521, were both invented by Baihua Hu, a principle scientist at Pfizer, and refer to substituted pyrrole-indoles.

It should be noted that this type of analysis should not be confused with the general NPA patent ranking process, which also takes into account other measures of patent 'popularity'. Nonetheless analysis of foundation patents can help provide a unique perspective on the history of a technology, and its key influences and influencers.

(This blog post was based on material previously presented in the Clearing the fog report: used with permission)

Ambercite is very proud to be associated with the latest Griffith Hack NPA white paper Clearing the fog: Patenting trends for the treatment of Alzheimer's disease, which was released today. In this white paper Griffith Hack, working very closely with and applying the Network Patent Analysis (NPA) process developed by Ambercite, analyses over 48,000 patents to fiilter, cluster and rank these patents. Two separate NPA maps accompany the white paper, one NPA map showing an cluster focused patent landscape map, and one NPA map showing a time scale patent landscape map.

Clearing the fog is also the best publically available demonstration yet of the powerful ability of NPA to precisely cluster patents with a precision unavailable with keyword or IPC patent code clustering. While we have seen this precise clustering for the majority of the confidential NPA client studies we have delivered, this degree of clustering is stronger than in our previous two NPA white papers on hybrid car and smartphone patents.

Clearing the fog also also demonstrates several other features of NPA:

• the power of associative searching (page 5)
• the value of a NPA time scale map (page 15, and available as a separate download)
• the concept of foundation patents (page 16)
• the ability of NPA to identify what could important future patents (page 17)
• and even some natural limitations of NPA (page 21)

As well as a detailed discussion of the leading patents, patent owners and inventors in the area of Alzheimer's disease, an increasing important disease which may impact many of our elderly and the people that care for them.

Interested in learning more, or how NPA can be applied into your business? Come back to us, and we can share more about the NPA process and deliverables.