During months 19 to 36, SusPharma achieved substantial scientific progress across its nine work packages, translating conceptual innovation into practical demonstration. The research on heterogeneous for C-X bond formation led to the development of novel single-atom and oxide-based materials synthesized by homogeneous precipitation methods. Among the most significant results, the copper single-atom catalyst demonstrated outstanding recyclability and no measurable metal leaching, providing direct applications in the synthesis of intermediates for antidepressant and antipsychotic drugs. Further progress was achieved in the design of green catalytic methodologies, where photocatalytic and electrocatalytic transformations were coupled with renewable carbon sources to generate building blocks from bio-based substrates. This bridge between biomass valorization and fine chemistry represents a major step toward the integration of green feedstocks in drug synthesis. Continuous-flow synthesis was also at the core of SusPharma’s success. A unified automated flow platform delivered several first-in-class achievements, including Ir-free carbon-carbon coupling using carbon nitrides and metal-free aziridination reactions with drastically reduced carbon footprints. Reactor design was supported by computational fluid dynamics to optimize light penetration and mixing, achieving 80% emission reductions compared to traditional reactors. In parallel, the project pioneered an artificial intelligence-driven crystallization ecosystem capable of linking machine-learning-based solvent selection with digital twins for process optimization. This approach was further enhanced by the creation of a multi-objective Bayesian framework that ensured impurity control and scalability. A major milestone was the development of the hybrid Jouyban-Acree neural network, the first predictive model for green solvent design trained on over 30,000 solubility data points. Automation was advanced through a fully autonomous laboratory platform integrating robotics, AI, and real-time analytics. Digital twins were used to perform Bayesian discrimination and automated design of experiments, allowing self-optimization in reactions such as the Claisen-Schmidt condensation. The project also introduced robotic chromatography capable of error-free purification and traceable analytics. In the area of drug repurposing, SusPharma developed solvent-free mechanochemical routes for the co-crystallization of NSAIDs, such as ketoprofen-lysine-gabapentin. Machine learning models accurately predicted co-crystal formation probabilities, while Raman and solid-state NMR provided in situ monitoring. Finally, research on advanced encapsulation resulted in low-permeability alginate and poly-L-lysine capsules post-treated with tannic acid to achieve pH-responsive, linear diffusion. Altogether, these achievements illustrate SusPharma’s shift from an ambitious concept into a tangible, integrated technological reality that merges catalysis, process intensification, and digitalization.