• A new approach for process development via integrated molecular modeling, process integration and mathematical optimization. • Integration of multiscale modeling and optimization as the cornerstone. • Incorporating fundamentals into process development for the best molecular transformation route. • Process integration for selecting fit-for-purpose technologies. • Mathematical optimization based on fundamental models for identifying technological breakthrough ideas. The new approach for process development proposed in this article is based on integrated molecular modeling, process integration and mathematical optimization. Molecular modeling is about achieving the best molecular transformation to maximize desired products and minimize by-products, which is accomplished via reaction chemistry optimization and catalyst development. Process integration is about selecting fit-for-purpose technologies for reaction, separation, and heat transfer systems, while mathematical optimization is about obtaining the optimal process flowsheeting and conditions to achieve the desired products with the lowest capital and operating costs as well as minimal footprint such as plot space, various emissions and wastes, hydrogen, water, and energy. When all these are integrated seamlessly, the true optimal process design can be achieved for practical applications, which will benefit the companies, communities, and environment at the same time. The cornerstone of this novel approach is the multiscale modeling and optimization integration via integrating fundamentals with the power of system integration and optimization, more specifically, integrating molecular analysis, quantum chemistry and transport mechanics with process integration and mathematical optimization for clean process development. By incorporating fundamentals into process development, it can identify the best molecular transformation routes by optimizing reaction pathways. Furthermore, mechanistic kinetic modeling such as microkinetic modeling and molecular-based kinetic Monte Carlo, which is enhanced by quantum chemistry, can help predict yield selectivity for different catalyst formula. By process integration , fit-for-purpose technologies are selected for developing hybrid systems. By mathematical optimization based on fundamental models, it can identify technological breakthrough ideas . For given multiple objective functions, mathematical combinatory optimization of the fundamental models not only determines the best-fit technology profile for an overall process based on techno-economic criteria, but also allow the process to deal with different feedstocks and make product shift based on market needs as well as the best environmental performance. In turn, this approach enables more effective feedback from development to research, as it integrated molecular based fundamentals.