Autonomous MicroScale Manufacture of Active Pharmaceutical Ingredients (APIs)

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This studentship will focus on developing agile, small-scale production facilities via creation of a unique autonomous microscale API manufacturing and testing system. The system will undertake process development to produce a stable active with desired critical quality attributes (CQAs) for subsequent secondary manufacture. Fundamental research will resolve complex, multi-length, and dimensional material process-product-performance relationships. Plus, integrating several industrial digital technologies (IDTs) will de-risk and accelerate drug manufacture, reducing experiments and dramatically reducing development time and raw material/solvents use by 60% . While CQA objectives are achieved by self-optimised crystallisation and process conditions. This will be co-developed with supporting industry partners focusing on 1) crystallisation and 2) spherical agglomeration.Objectives of the project include:Task 1 Build the Self Optimizing, MultiMode Crystallization/Particle Engineering and Testing Platform - Couple crystalliser; filtration and testing - selected sensors and actuators to explore knowledge space for selected API/solvent systems. Robotics required for offline tesing? What equipment is feasible?Objective = enable wide range of primary particle attainable region, extended by additives, external fields/mill, etc.Outputs = process conditions and particle attributes Task 2 Develop the Autonomous Particle Formation Digital Twin - Self-learning crystallisation AI via Bayesian optimisation from data extracted from feeds within accessible conditions within platform plus actuators and crystallisation modes. How many parameters? How to configure model? Selectively explore solvent only, external fields, additives to achieve engineered particle requirements. Identify and select accessible particle attributes for direct compression or flow or other targeted attribute.Outputs = materials with optimised properties; data; predictive design models and structure property process relationships.Deliverables: 1) Automated crystallisation and particle engineering manufacture and testing platform, 2) Autonomous IDT-driven manufacturing demonstrator to predictively design API particulates for optimum performance for rapid oral solid dose/capsule formulation 3) Use cases / 1st and 2nd generation IDT manufacturing demonstrators.