Safe and Sustainable Pharmaceutical Manufacturing Using Digital Twins, Computer-Assisted Retrosynthesis, and Life Cycle Assessment (Ref: CG-BB-2507)

About the Project

This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end digital twins, and life cycle assessment (LCA). A central component of the research will be the development of digital twins to simulate the entire production process, from raw materials to final product formulation. These models will enable rapid scenario testing, predictive analysis, and early decision-making, thereby reducing experimental workload and accelerating development timelines.

Life cycle assessment tools will be integrated from the outset to evaluate and minimize environmental impacts across all stages of synthesis and formulation. The project will align with industrial standards and regulatory frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible.

Multiobjective optimization algorithms will be employed to balance key performance indicators such as yield, cost, safety, environmental footprint, and process robustness. By embedding SSbD principles throughout, the project ensures that newly developed production routes are not only technically sound but also socially and environmentally responsible.

This PhD project is part of PHARMECO, a large research consortium involving more than 30 industrial and academic partners from 14 countries. The consortium aims to address the urgent need for sustainability in the healthcare industry by integrating environmentally friendly technologies, innovative processes, and standardized sustainability assessment methods.

The ideal candidate will operate at the intersection of synthetic organic chemistry, chemical engineering, and digital process modelling. This interdisciplinary project is particularly well-suited for individuals with a strong interest in artificial intelligence, machine learning, process systems engineering, and pharmaceutical manufacturing. The expected outcomes will contribute to more resilient, sustainable, and digitally enabled drug production platforms, supporting the global transition to eco-efficient pharmaceutical development.

Name of primary supervisor/CDT lead:
Prof Brahim Benyahia b.benyahia@lboro.ac.uk

Entry requirements:
Applicants should have or are expected to have at least a 2:1 in Chemical Engineering or a related discipline.

English language requirements:
Applicants must meet the minimum English language requirements. Further details are available on the International website (http://www.lboro.ac.uk/international/applicants/english/).

Funding information:
The studentship is for 3 years and provides a tax-free stipend of £20,780 per annum for the duration of the studentship plus tuition fees. Due to funding restrictions, this is only available to those eligible for UK fees.

Bench fees required: No

Closing date of advert: 31 May 2026

Start date: July 2026

Full-time/part-time availability: Full-time 3 years

Who is eligible to apply?: UK only

Project search terms:
artificial intelligence, data analysis, machine learning, manufacturing engineering, mathematical modelling, production, synthetic chemistry, computer-assisted retrosynthesis, life cycle assessment, pharmaceutical manufacturing, model-based optimisation