Supplementary Materials
The following supporting information can be found at: https://www.sciepublish.com/article/pii/900, the supplementary materials accompanying this study. Supplementary materials supporting this study provide detailed quantitative data, process schemes, and computational analyses that complement the main manuscript. Full details of model architecture, descriptor sets, and validation (R2 = 0.91; RMSE = 0.18), along with mass-balance calculations, descriptor matrices for cheminformatics modelling, and the LCA inventory datasets used to derive GWP and CED values, are included in the Supporting Information (SI). The SI also contains expanded explanations of the multi-metric framework, the digital solvent-ranking workflow, and the uncertainty analyses used to evaluate PMI, cPMI, and LCA variability. Together, these resources enhance transparency, reproducibility, and the interpretive depth of the solvent-focused sustainability evaluation. All data supporting this study—including normalized solvent-mass balances, descriptor matrices, and LCA inputs—are provided (cf. Datasets S1–S3), with additional data available on reasonable request. Table S1: Comparative sustainability metrics (PMI, E-factor, and energy intensity) for the conventional and green Sertraline synthesis routes, including contributions from solvent substitution, catalytic hydrogenation, and solvent recovery. Table S2: Life-Cycle Assessment (LCA) indicators—Global Warming Potential (GWP) and Cumulative Energy Demand (CED)—comparing halogenated and bio-based solvent systems (ethanol, isopropanol, 2-MeTHF, CyreneTM). Table S3: Alignment of redesigned Sertraline process with the 12 principles of green chemistry. Table S4: Classification of solvents according to ACS GCI, CHEM21, and GSK solvent selection guides, highlighting environmental, health, and safety (EHS) rankings and circularity potential. Table S5: Hybrid Sustainability Index (HSI)—summary of weighting factors and scoring rules used for multi-metric assessment. Table S6: Uncertainty Analysis for Key Sustainability Metrics. Table S7: Solvent Substitutions in the green Sertraline Process. Table S8: Predicted vs Measured Performance. Figure S1: Sustainable Pharmaceutical Production Framework. Figure S2: Integrated Sustainability Dashboard (PMI, cPMI, GWP, CED). Figure S3: Timeline of Key Green-Chemistry Metrics. Figure S4: Conceptual Roadmap for Sustainable, Circular, and Digitalized Solvent Management. Figure S5: Distinction Between GWP and CED in LCA. Figure S6: Solvent Substitution Strategy for Greener Sertraline Manufacturing. Figure S7: Digital Solvent Design Workflow. Dataset S1: Normalized process data from Pfizer’s Sertraline manufacturing runs (2018–2024), including solvent mass balances, recovery efficiencies, energy-use data, and emission profiles. Dataset S2: Machine-learning descriptor dataset comprising solvent physicochemical parameters (dipolarity, hydrogen-bonding capacity, viscosity, biodegradability) for predictive modeling of solvent performance. Dataset S3: LCA model inputs and cradle-to-gate inventory data were used to estimate GWP and CED for conventional and green solvent systems. Supporting Notes: 1. Detailed explanation of the multi-metric assessment framework, including equations for PMI, cPMI, E-factor, and life-cycle normalization. 2. Description of computational workflow for AI-assisted solvent ranking and uncertainty quantification. 3. Summary of regulatory cross-references (REACH, ICH Q3C, EPA Safer Choice) relevant to solvent classification and process validation.
Statement of the Use of Generative AI and AI-Assisted Technologies in the Writing Process
During the preparation of this manuscript, the author(s) used the Equations tool (mathematical formulae) from OpenAI in order to use it in the Supporting Information. Because these questions are not the original contribution from the authors, but have good reasons to be in front of the readers for educational purposes. After using this tool/service for generating equations, the author(s) reviewed the content as needed and, if the publisher wants, can remove that part from the submission. A couple of figures were also polished using MS-PowerPoint & Paint applications, but the content in the figures is their own.
Acknowledgments
The author gratefully acknowledges the institutional and library support provided by the participating universities and affiliated research centers/consortia, which enabled access to scientific databases, journals, and reference materials essential for the completion of this study. Technical and administrative guidance from laboratory and academic staff are also sincerely appreciated. The research was conducted independently using institutional resources and publicly available data.
Author Contributions
I.R.S. served as the lead researcher and corresponding author, responsible for overall study design, data interpretation, manuscript writing and coordination. Both authors have read and approved the final manuscript. In fact, I.R.S. mentored M.M.S. throughout the study. Conceptualization, I.R.S. and M.M.S.; Methodology, I.R.S.; Software, I.R.S.; Validation, I.R.S. and M.M.S.; Formal Analysis, I.R.S.; Investigation, I.R.S.; Resources, I.R.S.; Data Curation, I.R.S.; Writing—Original Draft Preparation, I.R.S.; Writing—Review & Editing, I.R.S.; Visualization, I.R.S.; Supervision, I.R.S.; Project Administration, I.R.S.; Funding Acquisition, none.
Ethics Statement
Not applicable. Ethical review and approval were waived for this study, as it did not involve any experiments on humans or animals. The research was conducted in accordance with institutional academic ethics and integrity guidelines and is based solely on secondary data sources, authors’ novel approach focusing on the published literature, and publicly available scientific information. Institutional compliance was maintained throughout all stages of the study.
Informed Consent Statement
Not applicable. This study did not involve humans, human participants, or patient data and was based entirely on secondary sources and published scientific literature.
Data Availability Statement
All relevant data supporting the findings of this study are included within the manuscript and its supplementary materials. The datasets generated and/or analyzed during the current study are made publicly available under license, CC BY 4.0.
Funding
This research received no external funding.
Declaration of Competing Interest
The authors conducted this study independently; however, Pfizer may provide feedback on the study outcomes related to their Sertraline process to ensure consistency with established chemical process methodologies and sustainability metrics. The authors declare no other competing financial interests or personal relationships that could have influenced the work reported in this paper.
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