Development and Improvement of In Silico Toxicity Screening Algorithms
242,849
2023-07-01 to 2024-03-31
Collaborative R&D
AbsoluteAi is a Machine Learning PharmaTech startup developing innovative data-driven tools to disrupt the discovery toxicology market. Our tools enable early-stage drug discovery scientists to gain drug safety insights not possible with traditional methods, **making drug discovery more efficient**.
This project will build on AbsoluteAi's early-stage proof-of-concept suite of toxicity prediction tools (where feasibility of machine learning algorithms to predict _in vitro_ toxicity endpoints has been demonstrated) to develop _**TOXSCAPE**_ - a user-centric suite of tools and algorithms across a range of toxicity endpoints. This is a huge step forward in the field of discovery toxicology and will turbo-charge AbsoluteAi's path to commercialisation.
The project comprises:
1. **High Content Screening:** Newcastle University will use their novel, multi-parametric high-content-imaging platform to test world-leading industry compound libraries for toxicity endpoints, creating gold-standard datasets to train AbsoluteAi's algorithms.
2. **_TOXSCAPE_** Development: AbsoluteAi will improve and expand the suite of tools and algorithms to cover a wide range of toxicity endpoints using existing public datasets (Tox21, ChEMBL).
3. **Commercial Testing:** To ensure that our algorithms work in a real-world drug discovery setting and to validate our understanding of the needs of our customers, we will test _TOXSCAPE_ through strategic partnerships with biotech companies, helping them with their discovery toxicology challenges.
The outcomes of this project will be cutting-edge, novel toxicity datasets, world-leading prediction tools across a range of endpoints, and commercial validation of our innovative approach with biotechs - opening up revenue-generating work in the future and private sector funding.
These tools have the potential to **unlock over £10bn of value** annually across the pharmaceutical industry through cost-effective **replacement of _in vitro_ screening** and **reduced failure rates** in preclinical trials.
There is a strong return on public investment through **increased efficiency** and greater private investment into the UK pharmaceutical sector, **boosting the UK economy and supporting jobs.**
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