CRISPR – Subtopic Landscape

A synthetic biology perspective

The subset of SynBio – CRISPR 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 – CRISPR topic model is visualised in figure 10.9, 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 15 diverse topics which are ranked based on the total number of published applications in figure 10.10. A patent application can be counted more than once as it can belong to multiple topics.

In figure 9.10, the analysis enables multilabel classification for each patent application, to account for multiple invention embodiments. During the 20 year publication period 2004-2023, almost 78% of the CRISPR dataset was classified within the top ranked subtopic (interfering nucleic acids – 2,356 publications). Approx. 70% were classified in the recombinant proteins and nucleic acids subtopic and 64.7% in the gene expression regulation subtopic. CRISPR is viewed as a potential tool for treating diseases reflected in the 4th placed ranking of gene therapy (49.6%). By correcting deleterious mutations or disrupting specific genes, CRISPR could deliver precision and efficiency for treating disease. The UK is the first country in the world to approve CRISPR based gene editing as a potential cure for two inherited blood disorders. The remaining subtopics reveal the uses of CRISPR based gene editing, etc. for various genetic engineering applications including the engineering of microorganisms. Due to the emerging nature of the technology there is no change in the rankings between the two time periods.

The CRISPR subtopic publication year trends are shown in figure 10.11. 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 10.11, there are a number of rapidly growing subtopic areas within the CRISPR landscape at the EPO. The broad gene expression regulation based subtopic publication trend has grown rapidly since 2017, with the fastest compound annual growth rate (CAGR) of 74.4% during 2014-23. All of the identified subtopics have shown rapid growth with a minimum of 40.3% CAGR. The cancer related topic (73.7%), interfering nucleic acids (71.4%) and engineered cells e.g. stem cells (71.3%) are all growing above the 70% CAGR threshold. The genetic engineering of viral cells is the fastest growing genetic engineering topic at 60% CAGR. The use of CRISPR for therapeutic applications is also rapidly growing amongst the t cell / immunotherapy topic (64.9%) and the fusion protein topic (63.7% CAGR).

Subtopic top 20 assignees distributions (2014-23)

The patent portfolios of the top 20 assignees within the SynBio – CRISPR dataset are analysed in figure 10.12. The portfolios are restricted to publications during 2014-23, mapped to the CRISPR subtopics identified; the counts represent total EPO publications.

The heatmap in figure 10.12 reveals the distribution of the top 20 CRISPR assignees during 2014-23, publications can be assigned to more than one subtopic, reflecting multiple invention embodiments. The BROAD INSTITUTE (colab between MIT & HARVARD) is the largest assignee identified with a broad base of expertise across the subtopics identified with the exception of chimeric antigen receptors. Outside of the universities and research institutions, EDITAS MEDICINE is developing therapies for rare diseases using CRISPR gene edit technology. In figure 10.12 EDITAS has the largest company portfolio within the gene therapy subtopic, the cancer subtopic, fusion proteins and the t-cell / immunotherapy subtopics. CRISPR therapeutics has expertise in the chimeric antigen receptors subtopic. Beyond MIT and HARVARD, PIONEER HI-BRED INT are a leading company establishing a CRISPR-CAS breeding platform to develop sees, etc. INSCRIPTA has specific expertise in the genetic engineering of bacteria, especially E.coli, utilising CRISPR based gene editing for the editing of genomes at scale for applications such as biomanufacturing.

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 CRISPR 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 10.13, 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 CRISPR field, based on 2014-23 publications for a relatively recent perspective.

In figure 10.13, approx.85% of the patent families identified had at least one US (84.8%) national filing. Other key territories with at least one national filing include; China (61%), Canada (57.5%) and Japan (57.3%). Below the 50% threshold, key territories include Australia (48.4%) and Republic of Korea (35.1%).

Investigating keyword trends provides a different perspective beyond the CRISPR 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 10.14. 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 10.14, the following key findings are observed and also support the trending areas identified by the subtopic modelling:

  • Diverse range of keywords which have all shown increasing trends when comparing 2014-18 with 2019-23, including niche areas such as fusion protein (182 publications), tcell (160 publications), stem cell (119 publications) and chimeric antigen receptor (94 publications).
  • Genome editing (298 publications) and gene editing (295 publications) are almost at the 300 publications threshold during 2019-23. Cancer (219 publications in 2019-23) represents a major therapeutic focus.

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 10.15. 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 10.15, 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:

  • Genetically modified microorganisms – use of CRISPR in a variety of microorganisms including bacteriophages, yeast, etc. One of the applications includes food, CRISPR can be used in the food industry to manage food bacteria, probiotics, genome editing, etc.
  • Gene therapy – CRISPR used for gene editing in plant cells as well as to treat therapeutic conditions (dystrophy). T cell / Immunotherapy – cancer is highlighted as an important therapeutic area.
  • Engineered cells e.g. stem cells – a variety of conditions are highlighted such as muscular dystrophy, thalassemia, sickle cell anemia.

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.