AdhesionTx was known as CelerisTx until April 2024

Collaborative role at the intersection of drug discovery, CADD, and product development. I contributed to ensuring that targets entering the BenevolentAI portfolio were progressable, and developed tools to make this happen. Led cross-functional teams to conduct suitability and feasibility assessments of diverse targets for both our internal pipeline and external collaborations, including as a key contributor to the recent BenevolentAI–Merck KgAa partnership. I championed two targets that have entered the BenevolentAI Discovery Pipeline.Provided analysis on the druggability of targets being considered for portfolio entry across multiple modalities including analysis of structured/unstructured literature data, generation of structural models, MD simulations and other appropriate analysis. This included development of project plans and timelines for internal HitID projects. Standardised the evaluation of targets by developing workflows (Python) for assessment of public and proprietary ligand data; building visualisations and proof-of-concept QSAR/ML models. Additionally I developed and deployed standalone apps to enable drug discovery scientists to use these workflows in a no-code environment. Co-designer and primary point of contact for the development of the BenevolentAI target progressability assessment platform; working closely with product managers, UX researchers, informaticians and AI scientists to communicate requirements, prototype solutions and negotiate priorities. Closely involved in the development of several features, including the contribution of code to the BenvolentAI codebase. Strengthened processes and capabilities, including parts of the TargetID exist stage criteria, and how first-in-class targets / IP landscape were assessed. I conduced research (user interviews, workshops, and journey mapping) to identify gaps and pain points in the workflows, then evaluated and licensed multiple external products that were rolled out across the team.

Senior medicinal chemist at BenevolentAI, working as part of cross-functional project teams applying tech approaches to meet accelerated project timelines.Contributed to several active programmes across multiple target classes and indications, from HitID through to lead-optimisation and candidate seeking. I am a named inventor on BenevolentAI’s PDE10A/Ulcerative Colitis patent (WO2023007184A). Implemented an internal chromLogD assay, providing access to high-throughput lipophilicity measurement to aid project progression and improve internal predictive models.

Represented BenevolentAI on the SCI Young Chemists Panel (YCP), including being part of the organising committee for the “New Approaches in Medicinal Chemistry” conference in 2022.

Medicinal chemistry role within an academic drug-discovery environment. I developed compounds to target APOBEC3B, a cytidine deaminase implicated in cancer evolution through the use of fragment-based drug discovery and structure-based design. Identified a lead series through close collaboration with computational chemistry and structural biology colleagues. Proactive in compound design, including enumerating and docking potential targets to prioritise compounds for synthesis.Progressed targets across multiple series simultaneously, and was responsible for collating and analysing complex data from a variety of sources (biochemical assays, LO-NMR, SPR, TSA, x-ray, physicochemical properties).

Industrial placement project working towards the design and synthesis of drugs against the integrin αvβ6 for the treatment of idiopathic pulmonary fibrosis.