About the project
Create new computational methods for the prediction of materials structure to transform the development of medicines. Pharmaceutical scientists routinely screen large numbers of potential crystal forms to improve drug performance, but experimental screening is time-consuming and resource intensive. This project will develop new computational methods to rapidly screen pharmaceutical materials.
Many active pharmaceutical ingredients can be co-crystallised with another small molecule (coformer) to produce materials with improved solubility, stability or manufacturability. However, identifying which coformer will produce suitable crystal forms remains a major challenge. Existing computational screening approaches provide useful guidance but often do not explicitly assess crystal packing and solid-state stability. Crystal structure prediction (CSP) can provide this information but is currently too computationally expensive for routine large-scale screening.
In this project, you will develop accelerated CSP workflows that retain predictive accuracy while dramatically reducing computational cost. Working with newly developed methods and machine-learned interatomic potentials, you will create tools capable of screening large libraries of coformers. You will investigate whether stable cocrystals or the propensity to form a cocrystal can be identified without performing a complete CSP study for every candidate system.
The research combines computational chemistry, machine learning, crystal engineering and scientific software development. You will work with the open-source mol-CSPy software package that we develop in our research group, and will collaborate closely with researchers at AstraZeneca, gaining exposure to industrial pharmaceutical development and real-world solid-form challenges. You will also have opportunities for visits or placement activities with AstraZeneca.
The outcomes of this project will include new computational methodologies for pharmaceutical crystal screening, published research papers, and software tools that support the development of future medicines.
You will receive training in:
- crystal structure prediction and molecular simulation
- machine learning methods for molecular and materials modelling
- crystal engineering and solid-state chemistry
- scientific software development in Python
- high-performance computing
- scientific communication and presentation skills
- industrial pharmaceutical research through collaboration with AstraZeneca
The School of Chemistry & Chemical Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
