The field is moving towards integrating digital solutions and automation to enhance development processes. Predictive modeling, optimization algorithms, and machine learning are being leveraged to improve the design and manufacturing of pharmaceuticals and hardware. This shift enables faster and more efficient development, reducing the need for extensive experimentation and resources. Noteworthy papers include:

• A study presenting an integrated platform for tablet formulation and manufacturing, combining predictive modeling and automation to predict and optimize critical quality attributes.
• A novel design pipeline for varifocal optical devices, utilizing data-driven surrogates and differential modeling to achieve high accuracy and minimal training data.
• A CI/CD framework for open-source hardware designs, automatically generating specifications and deploying hardware specifications.
• A proposal for developing Digital Twins of build processes to enable global and continuous improvement of build optimization.