Final results for the year ended 31 January 2023
e-therapeutics plc announces its audited final results for the year ended 31 January 2023.
- RNAi strategy delivering a rapidly growing in-house pipeline of early first-in-class candidates, against target genes discovered using our HepNetTM computational platform. Comprehensive in vivo proof-of-concept data packages being generated.
- Active across a variety of areas of high unmet medical need, including cardiovascular disease, non-alcoholic steatohepatitis (“NASH”) and haematology. Investing in the cardiometabolic space as a key focus area.
- Expansion of world’s most comprehensive knowledge base of hepatocyte-centric biology to capture and model complex biological processes in the liver and tissues influenced by the liver, completing proprietary curation of 100s of data sources.
- Increased integration of HepNetTM functionality and continued validation of our tools, in particular our hepatocyte-specific knowledge graph and proprietary target identification approaches.
- Mapping of human genetic validation of potential targets completed for more informed target triage.
- Integration of large language models (“LLMs”), such as such as OpenAI’s GPT model, to radically enhance computational capabilities and transform HepNetTM into a dynamic knowledge resource.
- Expansion of artificial intelligence (“AI”) approaches that learn from experimental data deployed into siRNA (short interfering RNA) drug design.
- Sustained intellectual property (“IP”) activity with patent applications filed on eight further inventions arising from the Company’s proprietary GalNAc-siRNA technology, GalOmicTM.
- New collaboration with iTeos Therapeutics in immuno-oncology announced on 5 April 2022. Several milestone payments received since, in addition to upfront consideration, following the successful identification of potential targets and small molecule compounds.
- Successful completion of Galapagos NV collaboration in idiopathic pulmonary fibrosis (“IPF”), with all near-term milestones achieved demonstrating our ability to effectively identify potential therapeutic strategies and targets.
Post Period Highlights
- Filing of four new patent applications to protect innovation around novel gene targets and associated disease relevant biology as well as proprietary siRNA stabilisation chemistries.
- Additional milestone achieved in collaboration with iTeos Therapeutics, resulting in an additional payment to the Company.
- Successful fundraise of £13.5 million announced in September 2022
- Cash and short-term investment bank deposits at 31 January 2023 of £31.7 million (2022: £26.4 million)
- Revenues of £0.5 million (2022: £0.5 million)
- R&D spend of £7.2 million (2022: £6.1 million)
- Operating loss of £10.2 million (2022: £9.6 million)
- Loss for the year of £8.3 million (2022: £8.1 million)
- £1.5 million R&D tax credit receivable (2022: £1.5 million)
Ali Mortazavi, Chief Executive Officer of e-therapeutics, commented: “2022/23 was a pivotal year for e-therapeutics as we made significant progress towards realising our goal of Computing the Future of Medicine. Through our innovative computational approach and RNAi-based therapeutic modality, we were able to rapidly identify and pursue promising targets in multiple disease areas. We are now well-positioned to advance our pipeline of first-in-class preclinical RNAi candidates, making significant progress in just one year.
By placing LLMs at the core of our computation and harnessing GPT-4’s capabilities, we can now create specialised LLM “agents” which will transform HepNetTM into a dynamic knowledge resource. GPT-4 and LLM integration will provide a unifying framework from which to drive every aspect of our pipeline and position e-therapeutics as a global leader in hepatocyte biology and related diseases.
Our long-term vision is to fully automate the preclinical drug discovery process, using GPT-4 and LLMs to access real-time information and interface with external applications, ultimately accelerating the development of life-saving treatments. Through our computational approach, we have been able to generate a multitude of potential target hypotheses and progress an in-house pipeline. Given our established position in computational drug discovery, we are ideally positioned to capitalise on this opportunity and look forward to the future with great confidence”.
Chief Executive's Statement
2022/23 was a pivotal year for e-therapeutics as we made significant progress towards realising our goal of Computing the Future of MedicineTM. Through our innovative computational approach and RNAi-based therapeutic modality, we were able to rapidly identify and pursue promising targets in multiple disease areas. We are now well-positioned to advance our pipeline of first-in-class preclinical RNAi candidates across multiple therapeutic areas, making significant progress in just one year.
Pivot from small molecules to RNAi: GalOmicTM
The opportunity to pivot into RNAi as a modality of choice to prosecute our novel target ideas presented several key advantages. In particular, focussing on GalNAc-conjugated siRNA, using our proprietary GalOmicTM platform, allows us to leverage the existing safety and performance precedent of a commercial-stage technology and take more biological risks by pursuing novel targets. In addition, RNAi enables rapid and comparatively inexpensive candidate generation once a target is selected. This allows us to have multiple ‘shots on goal’ for the same cost as a single small molecule programme with a much higher probability of success. Critically, domain knowledge of the RNAi therapeutics space is extremely niche, and I believe that the previous experience in the field of our senior leadership team will prove to be a crucial component of our success.
We have now shown across multiple targets that we can design and synthesise lead GalNAc-conjugated siRNAs in approximately 6 months and at a cost of c. $500K (including healthy in vivo pharmacology). This capability has enabled us to generate and progress drug candidates at a greatly accelerated pace and scale compared to more traditional modalities, and we believe that RNAi-based therapeutics have the potential to transform the treatment landscape across multiple disease areas.
Significant progress in RNAi IP, drug design and speed of execution
During the year, we have also made significant progress in our intellectual property (“IP”) portfolio, with the filing of multiple patent applications to protect both our RNAi platform (GalOmicTM) inventions and novel targets. We have gained significant new know-how whilst optimising our drug design process and reducing the associated timelines. These include the protection of siRNA chemical modification “stamps” thereby reducing the number of permutations and combinations in our screening cascades as well as predictive methodologies to reduce the number of sequences that need to be tested for in vivo studies.
This is part of our goal to apply computation across all aspects of our business, eventually allowing us to confidently predict the attributes of our siRNA molecules without the need for cell-based or in vivo screening. This will allow us to progress our siRNA molecules from in silico drug design straight to in vivo experiments, increasing our speed of execution. In addition, following the success of the mRNA-based COVID-19 vaccines, we have noted a significant change in policy from regulators to use compelling computational data to help reduce preclinical timelines and start first in human (“FIH”) clinical trials as quickly as possible. We believe, given that computation and data is used at every step of our drug discovery efforts, ETX is extremely well-positioned to take advantage of the changing regulatory landscape going forward.
HepNetTM: Our computational solution to human biology modelling and novel target ID
We continue to make significant strides in our expansion of HepNetTM, the most comprehensive hepatocyte data and analytics resource in the world. HepNetTM enables generation and analysis of biological network models, providing a novel and mechanistic approach to drug discovery that explicitly considers the true complexity of biology. Our computational network models represent, as closely as possible, the biological systems ETX is seeking to impact. The approach allows us to identify, prioritise and test millions of hypotheses in silico to make more reliable predictions with higher confidence and generate gene target hypotheses based on large complex data sets.
HepNetTM was built on the Company’s previously established proprietary network biology knowledge, tools and algorithms to model and interrogate human biology. This powerful modular platform was originally cell type agnostic. Extensive work has recently been undertaken to extend its capability and to leverage the focus on a single modality, RNAi, to create the most comprehensive and integrated proprietary hepatocyte-centric data resource.
We have invested in the licensing and generation of a range of proprietary liver omics data resources to support disease related process and target discovery, particularly in the realm of cardiometabolic disorders. The Company’s proprietary hepatocyte-focused Knowledge Graph has been further enhanced with additional data derived from both experimental Natural Language Processing (“NLP”) approaches and through AI-driven predictive approaches to knowledge inference. This allows the discovery of hidden relationships in data whilst providing the capability to impute missing information. Furthermore, the application of robust standards of validation for all our tools and approaches remains an important focus, and this rigour will continue to be a critical part of our development going forward.
In terms of scalability, the HepNetTM platform and data resources are now entirely cloud-based, ushering in a new era of effectively unlimited computational power and data storage. Using cutting-edge technologies we have been able to speed up our analytical pipelines by orders of magnitude, reducing compute times from weeks or months to a few hours. This has enabled the development of proprietary large-scale statistical approaches to analysis that were previously unfeasible.
HepNetTM has been instrumental in enabling us to develop a deep understanding of hepatocyte biology and giving us the ability to identify novel targets for potential drug candidates. We have continued to build on the platform, generating proprietary data inputs, exploring additional datasets of interest and keeping our data foundation updated. Through this, we have been able to generate a multitude of potential target hypotheses, enabling us to rapidly prosecute many high conviction, computationally-derived gene targets in relevant disease areas as possible.
Target nomination and pipeline
We believe that we now have a robust process to assess and prosecute any hepatocyte gene target from idea to FIH studies. In addition, we are continually refining and improving our methodologies, algorithms, datasets and implementing one of the fastest cascades in preclinical drug development. This has resulted in the Company having a number of high conviction therapeutic target-indication pairs which can be prosecuted at speed, dependent on our capital position.
Our preclinical pipeline has progressed at a rapid rate and we have initiated preclinical activities for additional targets while continuing to pursue previous projects. We expect to nominate our first candidate for IND/CTA enabling studies before the end of 2023, while we continue to advance projects through construct design and in vitro studies into in vivo testing. Cardiometabolic indications continue to be a key focus, but we remain open to pursuing promising hepatocyte-expressed targets identified by our computational methods that have effects in other disease areas, as exemplified by our active haematology programmes.
Through this pipeline, we aim to translate our discoveries into real-world, highly specific, and effective medicines in record time. We have also continued to nominate new targets, with a key pipeline priority being targets within cardiometabolic indications, such as cardiovascular disease (“CVD”) and non-alcoholic steatohepatitis (“NASH”). We have active programmes in these areas, and we plan to continue to add projects across metabolic syndrome indications.
Non-dilutive funding opportunities via collaborations/partnerships remains a key component of the Company’s strategy. Future collaborations will be in line with our current liver and RNAi focus, with an expectation for later-stage partnerships that maximise value retention and reflect the development of ETX’s early in-house RNAi pipeline. A balance will be found between preclinical assets to partner and assets that the Company will progress to early clinical trials to reach a more significant value inflection point.
Large Language Models and GPT-4
I believe that the most significant development at e-therapeutics over the past year occurred during Q4 2022, when we began investigating the integration of large language models (“LLMs”) and GPT-4 as a core component and enabling technology within all of our computational efforts. The drug discovery landscape is on the brink of a transformative revolution, driven by LLMs such as GPT-4. As I have already stated, e-therapeutics has made remarkable progress in multiple discovery programs, transitioning from small molecule discovery to hepatocyte-targeted GalNAc-siRNA drugs and our HepNetTM proprietary platform for insights and predictions.
Nevertheless, a weakness in our computation has been the immaturity of NLP algorithms to couple large corpora of text alongside our machine learning (“ML”) and statistical approaches. However, LLMs, such as GPT-4, now offer a unique opportunity to revolutionise e-therapeutics’ text capabilities and materially enhance HepNetTM’s capabilities.
By placing LLMs at the core of our computation and harnessing GPT-4’s capabilities, we can create specialised LLM “agents” and transform HepNetTM into a dynamic knowledge resource. Integration of GPT-4 and LLMs integration will provide a unifying framework from which to drive every aspect of our pipeline and position e-therapeutics as a global leader in hepatocyte biology and related diseases. Our long-term vision is to fully automate the preclinical drug discovery process, using GPT-4 and LLMs to access real-time information and interface with external applications, ultimately accelerating the development of life-saving treatments.
Immediate use cases for LLMs include our “Straight to In Vivo” project, target identification, patent extraction and an in silico cell type delivery project. We aim to create a robust pipeline and business model leveraging GPT-4 and LLMs' full potential, ensuring our place at the forefront of the AI-driven drug discovery revolution. By integrating GPT-4 and LLMs, e-therapeutics will continue to break new ground in drug discovery, create novel therapeutic strategies, and improve patient outcomes. Central to this vision is the ongoing advancement of our RNAi chemistry platform (GalOmicTM) for developing hepatocyte targeted GalNAc-siRNA drugs. These cutting-edge AI technologies hold the key to unlocking new treatments for various diseases and conditions, transforming the future of medicine.
In conclusion, integrating GPT-4 and LLMs into our drug discovery pipeline will revolutionise hepatocyte biology, RNAi chemistry, and the development of novel therapeutics. By harnessing these AI technologies, we can accelerate the development of life-saving treatments, improve patient outcomes and realise our vision of computing the future of medicine.
In April, we announced a new collaboration with iTeos Therapeutics. We are using our unique computational methodology to enable the discovery of highly differentiated novel immuno-oncology therapeutics. The work is progressing well against pre-defined plans and milestones. As well as receiving near-term cash payments material to the revenue of the Company, we are eligible to receive undisclosed milestone payments through preclinical and clinical development, in addition to regulatory milestones, per programme. Several milestone payments have been received since we first announced this collaboration and, after the period, we have achieved an additional success milestone associated with a further cash payment to the Company.
The collaboration with Galapagos NV (“Galapagos”) in idiopathic pulmonary fibrosis (“IPF”) has now successfully concluded and offers further evidence and third-party validation of our ability to effectively identify potential therapeutic strategies and targets computationally. We achieved all near-term milestones resulting in several cash payments to the Company. The future of the identified hits and targets will be determined by Galapagos according to its strategic priorities. If progressed, we are eligible to receive further milestones throughout development and commercial stages.
2022/23 was an extremely difficult year for the biotechnology sector. However, in September 2022 we successfully raised £13.5m through a share placing and subscription with M&G Investments which we believe is a recognition of our unique business model. This capital injection enables us to continue our growth and development. I would like to take this opportunity to thank M&G for their continued support.
In conclusion, I believe that 2022/23 will be seen as a transformative year for e-therapeutics. Through our computational approach, we have been able to generate a multitude of potential target hypotheses and progress an in-house pipeline of preclinical RNAi candidates across multiple therapeutic areas. I would like to reiterate that we believe that LLMs such as GPT-4 are a new enabling technology that will completely transform our business. Given our established position in computational drug discovery, we are ideally positioned to capitalise on this opportunity and look forward to the future with great confidence.
Chief Executive Officer