Understanding Microbial Metabolism of Pharmaceuticals to Facilitate Design for Degradation in Medicinal Chemistry

Background The pharmaceutical industry has to date had relatively limited engagement with the concept of benign by design. With estimated costs of £1.15 billion to bring a drug to market, there has been little appetite for exploring anything which might make that task even slightly harder, far less something which can seem counter intuitive to drug discovery where

chemists are often actually seeking to block potential sites of degradation in the molecular design. However, public focus on issues of Pharmaceuticals in the Environment, probable future legislation, and increased availability of big data, mean the time is right to seek improved tools for Designing for Degradation, without jeopardising human metabolic stability.

Objectives Pharmaceuticals are considered a significant micropollutant and we need to design for degradation of future medicines. In three stepwise activities the studentship will identify the existing moieties that increase persistence when pharmaceuticals reach the environment from patient excretion, and seek to investigate which moieties that increase environmental

degradation could be designed in to future pharmaceuticals. 1. Identify and characterise pharmaceutical degradation in wastewater treatment works from existing datasets of measured influent and effluent concentrations. 2. Identify structural moieties associated with persistence and degradation in the

measured dataset more or less than predicted by current approaches. 3. Identify approaches that could be integrated into typical medicinal chemistry multiparameter optimisation. Experimental Approach The student will combine data from existing public and archived data held by the University of York supervisors. They will also draw on the supervisors' connections to a large EU

project (https://imi-premier.eu/) with data gathering activities. Using these data and a machine learning approach they will then identify structural moieties associated with persistence and degradation in an unstructured/unbiased analysis. Working with medicinal chemists they will then compare these moieties with those typical of pharmaceuticals and

use these to design hypothetical pharmaceuticals, synthesise these molecules and test the machine models with laboratory scale wastewater treatment. Novelty This project, an ICASE PhD with the global pharmaceutical company AstraZeneca, covers a highly challenging and as yet under-researched and unsolved problem of significant interest

to industry, regulators and the general public. Scientific Training Training will include database generation, machine learning, medicinal chemistry, molecular design, chemical synthesis, high throughput screening, laboratory wastewater treatment simulations. The student will also be included in a wider cohort of students connected to the

academic and industrial supervisors' network.