Meeting the growing global demand for affordable, high-quality medicines requires more efficient, agile, and resilient pharmaceutical manufacturing. This presentation will highlight how artificial intelligence (AI), advanced modeling, and digital design technologies are transforming pharmaceutical process development, enabling accelerated optimization, scale-up, and end-to-end optimal (E2EO) manufacturing.

The talk will describe a framework for the AI-enabled digital design and scale-up of crystallization processes. Machine-learning workflows incorporating Bayesian optimization, active learning, synthetic data generation, uncertainty quantification, and surrogate modeling will be presented for rapidly developing fit-for-purpose digital twins when fully mechanistic models are impractical or prohibitively expensive. AI-driven, physics-inspired compartmental modeling approaches, such as CompArt, will also be introduced to efficiently capture complex hydrodynamics and scale-dependent mixing effects for process design and scale-up.

These concepts will be illustrated through case studies ranging from individual crystallization processes to integrated manufacturing systems. Examples will include the digital design and scale-up of industrial crystallization processes and the development of the E2EO MiniPharm, a modular and reconfigurable mini-manufacturing platform for the chemotherapy drug lomustine. Integration of manufacturing models with tablet dissolution and pharmacokinetic/pharmacodynamic (PK/PD) models will demonstrate how formulation and process design can be linked with dose-regimen optimization to support personalized medicine.

PharmaPy, an open-source modeling and simulation platform, will be presented as an enabling technology for the digital synthesis and optimization of hybrid batch–continuous and end-to-end pharmaceutical manufacturing processes, including distributed, modular, and mobile manufacturing approaches for more resilient and sustainable pharmaceutical supply chains.

Microgravity will also be explored as an emerging process-intensification environment for pharmaceutical crystallization, including a novel modeling framework for the evaluation and design of crystallization systems under microgravity conditions.

Finally, an integrated case study spanning the complete manufacturing chain—from reaction and drug-substance production to drug-product processing and tableting—will demonstrate how these digital design methodologies can enable fully integrated DS–DP process development and optimization. Together, the examples illustrate how AI, mechanistic modeling, digital twins, and advanced manufacturing technologies can be integrated across scales—from crystal to tablet—to enable the next generation of intelligent pharmaceutical manufacturing.

Process simulation and digital design have become essential tools for accelerating process development, optimization, scale-up, and manufacturing system design across a wide range of industries.

PharmaPy is an open-source, Python-based process modeling and simulation platform originally developed for pharmaceutical manufacturing applications, but its modular, object-oriented architecture makes it readily adaptable to other chemical and process engineering systems.

The platform provides a library of interconnected unit-operation models and a flexible framework for developing customized models, enabling the simulation, design, and optimization of individual unit operations as well as integrated process flowsheets.

This hands-on workshop will introduce the structure, philosophy, and fundamental capabilities of PharmaPy and guide participants through practical examples demonstrating process modeling, parameter estimation from experimental data, prediction of the effects of operating conditions on process performance and product attributes, and optimization of operating conditions to achieve specified targets.

Participants will learn how to instantiate and configure unit operations such as reactors and crystallizers, develop and adapt models for specific applications, connect multiple unit operations into integrated flowsheets, and perform process and techno-economic optimization.

Through instructor-guided exercises, participants will gain practical experience with PharmaPy and develop the skills needed to apply the platform to digital process design and optimization, from individual unit operations to integrated end-to-end manufacturing systems across pharmaceutical, chemical, and other process industries.

The workshop From Research to Startup – Founding in Germany covers the following topics:

• Founding in Germany: Basics, legal forms, visas, and funding (EXIST)
• Problem–Solution Fit: Tech-push vs. market-pull and finding a real customer problem
• The Business Model: The St. Gallen magic triangle (Who, What, How, Value)
• Pitching: Pitch deck structure and elevator pitch training