I am Layla Hosseini-Gerami, a passionate advocate for diversity in tech and science and a proud co-founder of Ignota Labs. As a female ethnic minority with a PhD in AI for Drug Discovery from Cambridge University, where I won the Outstanding Thesis of the Year, I am committed to being a role model for women in tech. My journey has been driven by a desire to address inequalities in the scientific community and improve patient outcomes across diverse populations. Our Minimal Viable Product (MVP) **_SAFEPATH_** leverages cutting-edge AI technology to understand molecular mechanisms of drug toxicity. We seek to extend our platform to address the significant gap in drug safety understanding in diverse populations. Traditional drug studies predominantly involve white male participants, leading to known oversight of toxicity risks in women and ethnic minorities. Our project aims to address this disparity by utilising patient-derived data, in partnership with Genomics England and Cytochroma, to predict Gefitinib-induced liver toxicity risks in sub-populations, building on a recent case study where we identified a novel mechanism. This grant will enable us to expand **_SAFEPATH_** in two crucial areas: **Understanding Population Differences:** By integrating comprehensive patient-derived genomics data, we aim to understand the drivers of toxicity in diverse populations. This will help in identifying genetic variations that contribute to differential drug responses. Utilising our partnership with Genomics England, we will incorporate known pharmacogenomic variations to predict and analyse toxicity risks specific to various sub-populations and validate our findings on Cytochroma's cell lines derived from diverse donors. Addressing the overwhelming bias for white, European males in drug studies, our project will ensure that the risks for women and ethnic minorities are adequately assessed and mitigated. **Towards Personalised Medicine:** Our approach is a significant step towards the development of safer and more effective drugs tailored to the genetic profiles of diverse populations. By reducing adverse drug reactions in underrepresented groups, we aim to improve public health outcomes and promote equity in medical treatments. This initiative not only strives for scientific excellence but also emphasises the importance of diversity and inclusion in research. Through the successful execution of this project, I aim to inspire future generations of women and underrepresented minorities to pursue careers in science and innovation. With the support of this grant, SAFEPATH will advance the field of personalised medicine, ensuring that drug development is both inclusive and equitable, ultimately benefiting society as a whole.

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.**