Automating and improving GHG emissions calculation in pharma/fine chemicals synthesis R&D: GreenSpeed as a digital tool to navigate complex value chains

Abstract

As the pharmaceutical and fine chemicals industries strive to meet climate goals, optimizing the environmental impact of chemical synthesis during the research and development (R&D) phase becomes crucial. This paper demonstrates the challenges involved in evaluating climate change impacts due to lack of harmonization in calculation standards, missing raw material data in environmental footprint (EF) databases, and common mistakes to choose proxy data when closing data-gaps in manual calculations. As one approach to mitigate this situation, we introduce GreenSpeed, a digital tool developed by Merck KGaA, Darmstadt, Germany, that automates the assessment of greenhouse gas (GHG) emissions and resource consumption metrics, such as Product Carbon Footprint (PCF) and Process Mass Intensity (PMI). By integrating with Electronic Laboratory Notebooks (ELNs) and automatically matching environmental footprints based on chemical structure and molecular complexity, GreenSpeed enhances data accuracy and accessibility, empowering researchers to make informed decisions that promote sustainability aspects. The tool provides an overview of the three main contributions to climate change impacts relevant to R&D and process chemists: raw materials, waste treatment, and energy consumption. In addition, GreenSpeed features functionalities for direct route comparisons, scenario modeling, and recycling assessments, enabling a fit-for-purpose evaluation of environmental impacts across complex value chains. This approach addresses the intricacies of complex molecule manufacturing, where multiple synthesis pathways can lead to varying environmental footprints. Through a detailed case study focused on an API precursor synthesis as well as the underlying chemical building blocks used as raw materials, this work demonstrates GreenSpeed's capability to improve accuracy in PCF calculations. Potentials for GHG emissions reduction are presented as well, considering the complexities of pharma and fine chemicals supply chains. The study highlights the complexity to perform such assessments and the necessity of digital solutions in advancing emissions reduction initiatives within the pharmaceutical and fine chemicals sector. Guidance on how to create datasets for PCF calculations with reasonable quality and how to close data-gaps is presented as well.