Autonomous MicroScale Manufacture of Active Pharmaceutical Ingredients (APIs)

Aims and Objectives

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.