Textiles & Coatings – Subtopic Landscape

A synthetic biology perspective

The subset of SynBio – textiles & coatings related patents were further investigated to identify subtopics and assess trending areas. The topic model leverages a hybrid approach based on the optimised extractive summary for each publication. Using a combination of topic discovery via fine-tuned transformer based deep learning and ground truth cross referencing via keyword and classification codes. The process enables a patent to belong to more than one topic for accurate multi-classification trends, accounting for multiple invention embodiments. Please see the topic model page for further details regarding the topic model methodology to avoid duplication here.

Subtopic landscape

The synthetic biology – textiles & coatings topic model is visualised in figure 14.9, based on the dimensionality reduction of vector embeddings to map each patent to a contextually relevant x & y coordinate, the categorical clusters are colour coded to support review. The visual is based on patents assigned to one key subtopic for simplicity. However, trend analysis also enables a patent to belong to more than one subtopic which is consistent with the topic model methodology throughout this project.

Subtopic model – technology cluster totals

The hybrid topic model methodology identified 10 diverse topics which are ranked based on the total number of published applications in figure 14.10. A patent application can be counted more than once as it can belong to multiple topics.

In figure 14.10, the analysis enables multilabel classification for each patent application, to account for multiple invention embodiments. During the 20 year publication period 2004-2023, approx. 48% of documents identified were classified within the treatment of fibres subtopic such as biochemical treatment. Similarly approx. 48% of documents were related to polymers, of which polyesters (19%) represents a major subgroup. Synthetic or artificial textiles and coatings saw nearly 42% of documents classified in this subtopic. Cellulose related materials represent a major subtopic area which includes biopackaging and the processing of waste and recycling. The synthetic biology related textiles and coatings are commonly used in medical devices with nearly 44% of documents classified in this subtopic (43.7%).

The textiles & coatings subtopic publication year trends are shown in figure 14.11. Publication trends discussed below are based on EP A1/A2 applications, identified patents can belong to more than one subtopic due to multiple invention embodiments.

In figure 14.11, biopackaging is the fastest growing subtopic with a compound annual growth rate of 27.1% during 2014-23. The sustainable packaging industry is forecast to double by 2034. Notable UK businesses active in this area include Notpla based in London, producing sustainable packaging from seaweed. Pulpex based in Cambridge, producing eco-packaging from cellulose. HUID (Oban, Scotland) is developing a compostable packaging made from onion skins. Waste / recycling related is the second fastest growing subtopic at 14% CAGR. In this area UK based Fibrelean is a leading supplier of equipment for microfibrillated cellulose which can be used as pulps for paper, packaging, tissue speciality and pulp based industries.

Polymers are growing at 9.5% CAGR. UK based companies include BIOME BIOPLASTICS based in Southampton, developing natural bioplastics and ARDA BIOMATERIALS (London) creating novel biomaterials from plant based biopolymers. Within the polymers area, polyesters are a fast growing subtopic at 12.2% CAGR. Medical devices represent a growing market for bio-based material growing at 5.8% CAGR. UK businesses include 4D BIOMEDICINE producing bioabsorbable medical devices in Nottingham and MODERN SYNTHESIS based in London creating biobased textiles. The synthetic /artificial subtopic is growing at 8% CAGR. HIDE BIOTECH (Cambridge) is developing sustainable biomaterials such as leather alternatives from marine collagen and OXFORD SILK PHAGE TECHNOLOGIES pioneering an antibacterial bioactive textile technology integrating bacteriophages, providing solutions for surgical implant/wound infections.

Subtopic top 20 assignees distributions (2014-23)

The patent portfolios of the top 20 assignees within the SynBio – textiles & coatings dataset are analysed in figure 14.12. The portfolios are restricted to publications during 2014-23, mapped to the 10 subtopics identified, the counts represent total EPO publications.

The heatmap in figure 14.12 reveals the distribution of the top 20 textiles & coatings assignees during 2014-23, publications can be assigned to more than one subtopic, reflecting multiple invention embodiments. PULPAC is focused on biopackaging with the waste processing and recycling of cellulose feedstock. SPIBER is focused on synthetic or artificial materials and the treatment of fibres, producing high performance protein most notably spider silk. PROCTOR & GAMBLE has the largest distribution of polymers (33 applications) and is focused towards the biochemical treatment of fibres, etc. There also exists a notable distribution of waste / recycling based applications (15 applications) as PROCTOR & GAMBLE is active in biopackaging.

The analysis does not account for earlier publications prior to 2014, which may have contributed to companies developing market share, etc. and potential licensing and acquisitions (subsidiaries). Data cleaning was carried out to clean names and consolidate. The analysis is an informative guide as some specific subtopics have strict content boundaries to enable differentiation, whilst others are broader to capture more generic areas.

Patent family territory analysis

The INAPDOC patent families comprising the identified textiles & coatings related EPO patents were analysed to identify the top 30 territories where patents are filed. Analysing the publication countries alone is insufficient as major countries such as France, the UK, Germany, etc. may not publish patents going through the European (EPO) route, especially when pending. To further supplement the available data, a bespoke analysis was conducted standardising the publication countries and including ‘protected countries’ to include patent rights which are pending or granted based on legal status. There are caveats which include:

  • The study methodology is focused on EPO patents and may not capture assignees/applicants that file only in home territories or don’t file in Europe via EPO filings.
  • The protected country data may not be fully up to date, due to INPADOC data availability and where EPO patents are recent filings.

The standardisation procedure ensures a territory is only counted once per family. The territory analysis is visualised in figure 14.13, EPO and WO (PCT) patents have been included for reference purposes. Despite the caveats, the analysis provides useful indicators regarding territories where applicants are filing patents within the textiles & coatings field, based on 2014-23 publications for a relatively recent perspective.

In figure 14.13, 92.3% of the patent families identified had at least one US national filing. Other key territories with at least one national filing include China (63.6%) and Japan (55.6%). Below the 50% threshold, key territories include Canada (38.4%), Germany (34.3%), the UK (29.2%), India (28.9%) and Republic of Korea (28.4%).

Investigating keyword trends provides a different perspective beyond the textiles & coatings subtopic model. The smart summaries used during the topic model stage were data mined for the most contextually important keywords leveraging transformer based embeddings. Identifying keywords and phrases most similar to the document plus manual auditing for relevance to the SynBio project, visualised in figure 14.14. The visualisation indicates how the cumulative publication counts have changed between the publication periods during 2014-18 & 2019-23. The methodology aims to identify contextually relevant and reliable keywords as a source of ground truth, signify important keywords within the corpus and audit the topic model subtrend analysis already carried out.

In figure 14.14, the following key findings are observed and also support the trending areas identified by the subtopic modelling:

  • Hydrogel increased from 31 applications in 2014-18 to 52 publications in 2019-23, the matrix keyword may be related, increasing to 50 publications during 2019-23.
  • Fibers grew from 54 to 79 publications during 2019-23, antimicrobial may be related, growing to 78 publications during 2019-23.
  • Growth of polymer (94 to 123 publications), textile (83 to 118 publications) and fabric (57 to 99 publications).

Subtopic keyword analysis

For a further perspective of contextually important keywords, a statistical procedure was applied selecting six subtopics from the corpus. The analysis contrasts how the usage or frequency of the keywords / phrases differs across the subtopics using a weighted log odds ratio. This aims to identify which differences are meaningful and weight the log odds ratio by a prior outlined in Monroe, Colaresi, and Quinn (2008). The statistical procedure requires the prior is estimated from the data itself rather than an uninformative prior, such as a Dirichlet prior. The procedure is an empirical Bayes approach with results identified in figure 14.15. A further motivation is to audit the subtopics for result relevance and transparency and provide insights into content. As a sidenote the transformer based keyword analysis provides powerful methods to review subtopics and extend the analytical power beyond procedures of evaluating a corpus such as TF-IDF (term frequency-inverse document frequency).

In figure 14.15, the keywords outlined are most characteristic of each subtopic based on the weighted log odds score which is labelled. Another implication of higher log odds scores is the ability to define the keyword identified as more likely to be used within the specific subtopic. This is interesting as some of the log odds scores are not very high, which is not surprising given the overlap encountered between the multiple subtopics identified within the specific topic landscape.

Some key findings observed are:

  • Synthetic or artificial – highlighting the use of recombinant proteins, a specific niche including recombinant spider silk protein.
  • Waste / recycling related – production of textiles from polymers, feedstocks can include cellulose.

It is difficult to distil and characterise the coverage of the subtopics via restricted keywords and phrases, this is also complicated by the weighting not always being frequency led but reflective of the terminology and context which is more characteristic of one subtopic in relation to others. It is fair to conclude that the subtopic model has successfully captured an extensive set of subtrends which are distinct, overlap exists but the trends are accurate once audited. The keywords are relevant to real word applications and suggest the insights identified are a useful tool to examine the specific topic landscape.