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Reaction Discovery & Development Optimization

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Reaction discovery identifies new tools for organic chemists to access novel scaffolds/molecules. It is often difficult, time-consuming, expensive, and wasteful to identify hits and optimize reactions. In C-CAS, we strive to use and develop computational and ML tools to expedite the process of reaction optimization.

Publications

  • Gensch T, dos Passos Gomes G, Friederich P, Peters E, Gaudin T, Pollice R, et al. A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis. J. Am. Chem. Soc. 2022, 144 ASAP  https://pubs.acs.org/doi/full/10.1021/jacs.1c09718

  • Andrzej M. Żurański, Shivaani S. Gandhi, and Abigail G. Doyle. A machine learning approach to model interaction effects: development and application to alcohol deoxyfluorination. J. Am. Chem. Soc. 2023, 145,14,7898-7909. https://doi.org/10.1021/jacs.2c13093

  • Torres, Jose Antonio Garrido; Lau, Sii Hong; Anchuri, Pranay; Stevens, Jason M; Tabora, Jose E; Li, Jun; Borovika, Alina; Adams, Ryan P; Doyle, Abigail G. A Multi-Objective Active Learning Platform and Web App for Reaction Optimization. J. Am. Chem. Soc. 2022, 144,43,19999-20007. https://pubs.acs.org/doi/10.1021/jacs.2c08592

  • Haas, B.C., Kalyani, D., Sigman, M.S. Applying statistical modeling strategies to sparse datasets in synthetic chemistry. Sci. Adv. 11 (1) doi: 10.1126/sciadv.adt3013

  • Ma, Y. Huang, X.; Nan, B.; Moniz, N. Zhang, X.; Wiest, O.; Chawla, N.V. “Are we making much progress? Revisiting chemical reaction yield prediction from an imbalanced regression perspective” Proc. ACM WebConf 2024 790-793. https://doi.org/10.1145/3589335.3651470

  • Shen, Y., Borowski, J., Hardy, M., Sarpong, R. Doyle, A., Cernak, T. Automation and computer-assisted planning for chemical synthesis. Nat Rev Methods Primers, 2021, 23, 1.    https://www.nature.com/articles/s43586-021-00022-5

  • Boiko, D.A., MacKnight, R., Kline, B. and Gomes, G., 2023. Autonomous chemical research with large language models. Nature, 624(7992), 570-578. doi: 10.1038/s41586-023-06792-0

  • Shields, B.J. ; Stevens, J.; Li, J.; Prarasram, M.; Damani, F.; Martinez Alvaro, J., Janey, J. Adams, R.P., Doyle, A. Bayesian Reaction Optimization as A Tool for Chemical Synthesis. Nature 2021, 590, 89-96.  https://www.nature.com/articles/s41586-021-03213-y

  • Ortiz, K.; Dotson, J.; Robinson, D. J.; Sigman, M. S.; Karimov, R. R. “Catalyst-controlled enantioselective and regiodivergent addition of aryl boron nucleophiles to N-alkyl nicotinate salts,” J. Am. Chem. Soc. 2023, 145, 21,11781-11788. https://doi.org/10.1021/jacs.3c03048

  • Stenfors, B.A.; Cadge, J. A.; Aikonen, S.; Luchini, G.; Wahlers, J.; Koh, K. H.; Murronen, M.; Menche, M.; Pfeifle, M.; Keto, A.; Paton, R.; Sigman, M.S.; Wiest, O. “Conformation Dependent Features of Bisphosphine Ligand.” J. Org. Chem 2025, 90, 13874–13884 doi.org/10.1021/acs.joc.5c01682

    DOI of dataset(s): doi.org/10.5281/zenodo.17086568

  • Zacate, S.B., Dantas, J.A., Lin, S., Doyle, A.G.; Sigman, M.S. Considerations in Pursuing Reaction Scope Generality. Angew. Chem. Int. Ed. 2025 e202511091. https://doi.org/10.1002/anie.202511091

  • Matthews, A.D., Peters, E., Debenham, J.S., Gao, Q., Nyamiaka, M.D., Pan, J., Zhang, L.K., Dreher, S.D., Krska, S.W., Sigman, M.S. and Uehling, M.R., 2023. Cu Oxamate-Promoted Cross-Coupling of α-Branched Amines and Complex Aryl Halides: Investigating Ligand Function through Data Science. ACS Catalysis, 13(24), 16195-16206. doi https://doi.org/10.1021/acscatal.3c04566

  • Gandhi, S.S., Brown, G.Z., Aikonen, S., Compton, J.S., Neves, P., Martinez Alvarado, J.I., Strambeanu, I.I., Leonard, K.A., Doyle, A.G. Data Science-Drivin Discovery of Optimal conditions and a condition-Selection Model for the Chan-Lam Coupling of Primary Sulfonamindes. ACS Catal. 2025. 15, 2292-2304. https://doi.org/10.1021/acscatal.4c07972?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as

  • van Dijk, Lucy, Brittany C. Haas, Ngiap-Kie Lim, Kyle Clagg, Jordan J. Dotson, Sean M. Treacy, Katarzyna A. Piechowicz et al. "Data Science-Enabled Palladium-Catalyzed Enantioselective Aryl-Carbonylation of Sulfonimidamides." J. Am. Chem. Soc. 2023, 145 ASAP. https://doi.org/10.1021/jacs.3c06674

  • Cadge, J.A.; Lozano, C.; Merriman, M.T.; Oblad, P.; Sigman, M.S.; Reisman, S.E. A Data Science-Guided Approach for the Development of Nickel-Catalyzed Homo-Diels–Alder Reactions. J. Am. Chem. Soc. 2025, 147, ASAP. doi.org/10.1021/jacs.5c09948

  • Romer, N.P., Min, D.S., Wang, J.Y., Walroth, R.C., Mack, K.A., Sirois, L.E., Gosselin, F., Zell, D., Doyle, A.G. and Sigman, M.S., 2024. Data Science Guided Multiobjective Optimization of a Stereoconvergent Nickel-Catalyzed Reduction of Enol Tosylates to Access Trisubstituted Alkenes. ACS Catalysis, 14, pp.4699-4708. https://pubs.acs.org/doi/10.1021/acscatal.4c00650

  • Raghavan, P.; Haas, B.C.; Ruos, M.E.; Schleinitz, J.; Doyle, A.G.; Reisman, S.E.; Sigman, M.S.; Coley, C.W.  Dataset Design for Building Models of Chemical Reactivity. ACS Cent. Sci 2023, 9, ASAP https://doi.org/10.1021/acscentsci.3c01163
















  • Gensch, T.; Smith, S.R; Colacot, T.J.; Timsina, Y.; Xu, G.; Glasspoole, B.W.; Sigman, M.S, Design and Application of a Screening Set for Monophosphine Ligands in Metal Catalysis. ACS Catal. 2022. 12, 13, 7773-7780.  https://doi.org/10.1021/acscatal.2c01970

  • Silva, J. D. J.;  Bartalucci, N.;  Jelier, B.;  Grosslight, S.;  Gensch, T.;  Schünemann, C.;  Müller, B.;  Kamer, P. C.;  Copéret, C.; Sigman, M. S., Development and Molecular Understanding of a Pd-catalyzed Cyanation of Aryl Boronic Acids Enabled by High-Throughput Experimentation and Data Analysis. Helv. Chim. Acta 2021. https://doi.org/10.1002/hlca.202100200

  • Feng, K., Raguram, E.R., Howard, J.R., Peters, E., Liu, C., Sigman, M.S.; Buchwald, S.L., Development of a Deactivation-Resistant Dialkylbiarylphosphine Ligand for Pd-Catalyzed Arylation of Secondary Amines. J. Am. Chem. Soc. 2024, 146 ASAP . https://doi.org/10.1021/jacs.4c09667

  • Wang JY, Stevens JM, Kariofillis SK, Tom MJ, Golden DL, Li J, Tabora JE, Parasram M, Shields BJ, Primer DN, Hao B. Identifying general reaction conditions by bandit optimization. Nature. 2024, 626, 1025-1033  https://doi.org/10.1038/s41586-024-07021-y

  • Crawford, J.M.; Gensch, T.; Sigman, M.S.; Elward, J.M.; Steves, J.E.  Impact of Phosphine Featurization Methods in Process Development. Org. Proc. Res. Dev. 2022, 26, 4, 1115-1123  https://doi.org/10.1021/acs.oprd.1c00357

  • Raghavan, P., Rago, A.J., Verma, P., Hassan, M.M., Goshu, G.M., Dombrowski, A.W., Pandey, A., Coley, C.W. and Wang, Y., Incorporating Synthetic Accessibility in Drug Design: Predicting Reaction Yields of Suzuki Cross-Couplings by Leveraging AbbVie’s 15-Year Parallel Library Data Set. J., Am Chem. Soc. 2024, 146, 15070–15084. https://doi.org/10.1021/jacs.4c00098

  • Newman-Stonebraker, Samuel; Smith, Sleight; Borowski, Julia; Peters, Ellyn; Gensch, Tobias; Johnson, Heather; Sigman, Matthew; Doyle, Abigail. Linking Mechanistic Analysis of Catalytic Reactivity Cliffs to Ligand Classification. ChemRxiv, May12, 2021. https://doi.org/10.26434/chemrxiv.14388557.v1

  • Gardner, K.E., De Lescure, L., Hardy, M.A., Tan, J., Sigman, M.S., Paton, R.S., Sarpong, R. Modular synthesis of aryl amines from 3-alkynyl-2-pyrones. Chem. Sci. 2024. doi: 10.1039/d4sc04885g

  • Wright, B.A., Sarpong, R. Molecular Complexity as a Driving Force for the Advancement of Organic Synthesis. Nat Rev Chem (2024). doi:10.1038/s41570-024-00645-8

  • LeSueur, A., Tao, N., Doyle, A., Sigman, M. Multi-Threshold Analysis for Chemical Space Mapping of Ni-Catalyzed Suzuki-Miyaura Couplings. Chemistry Europe. Eur. J. Org. Chem. 2024 e202400428. doi:10.1002-ejoc.202400428

  • Saebi, M.;  Nan, B.;  Herr, J.;  Wahlers, J.;  Guo, Z.; Zuranski, A. M.;  Kegej, T.;  Norrby, P.-O.;  Doyle, A. G.;  Wiest, O.; Chawla, N., Wiest, O. On the Use of Real-World Data Sets for Reaction Yield Prediction.  Chem. Sci., 2023, 14, 4997-5005.  https://doi.org/10.1039/D2SC06041H

  • Hall, J.R., Romer, N.P., Spiller, T., Sigman, M.S., Sanford, M.S., 2025. Pd-Catalyzed Desulfonylative Fluorination of Electron Deficient (Hetero) Aryl Sulfonyl Fluorides. Chem. Sci. 2025, 16, 18936-18941 https://doi.org/10.1039/D5SC00912J

  • Bartholomew, G.L., Kim, S.F., Oyamada, Y., Sbordone, F., Carroll, J.A., Jurczyk, J.E., Yeung, C.S., Barner-Kowoliik, C., Sarpong, R. Phototransposition of Indazoles to Benzimidazoles: Tautomer-Dependent Reactivity, Wavelength Dependence, and Continuous Flow Studies. Angew. Chem. Int. Ed. 2025. e202423803. https://doi.org/10.1002/anie.202423803

  • Żurański, A.M., Martinez Alvarado, J.I., Shields, B.J. and Doyle, A.G..  Predicting Reaction Yields via Supervised Learning. Acc. Chem. Res. 2021, 54, 1856-865. https://pubs.acs.org/doi/10.1021/acs.accounts.0c00770

  • Wang, J. Y.; Stevens, J. M.; Kariofillis, S. K.; Tom, M.-J.; Li, J.; Tabora, J. E.; Parasram, M.; Shields, B.; Primer, D.; Hao, B.; Del Valle, D.; DiSomma, S.; Furman, A.; Zipp, G. G.; Melnikov, S.; Paulson, J.; Doyle, A. Reinforcement learning prioritizes general applicability in reaction optimization.  ChemRxiv 2023 10.26434/chemrxiv-2023-dcg9d

  • MacKnight, R.; Boiko, D. A.; Regio J. E.; Gallegos, L.C.; Neukomm, T.A, Gomes, G. Rethinking chemical research in the age of large language models Nature Comp. Sci. 2025, doi.org/10.1038/s43588-025-00811-y

  • Zell D; Kingston C; Jermaks J; Smith S.R.; Seeger N; Wassmer J; Sirois, L.E.; Han, C.; Zhang, H.; Sigman, M.S.; Gossling, F., Stereoconvergent and -divergent Synthesis of Tetrasubstituted Alkenes by Nickel-Catalyzed Cross-Couplings. J. Am. Chem. Soc. 2021, 143, 45,19078 -19090. https://doi.org/10.1021/jacs.1c08399

  • Novicki, J.R.; Teeter, M.D.; Baldwin, N.J.; Am Ende, C.W.; Puleo, T.R.; Richardson, A.D.; Ball, N.D. Sulfur fluoride exchange with carbon pronucleophiles. Chem. Sci.2025 ASAP doi.org/10.1039/d5sc03893f

  • Liu, Zhen, Yurii S. Moroz, and Olexandr Isayev. "The Challenge of Balancing Model Sensitivity and Robustness in Predicting Yields: A Benchmarking Study of Amide Coupling Reactions." Chem.  Sci. 2023, 14, 10835-10846.  doi https://doi.org/10.1039/D3SC03902A

  • Williams, W.L.; Zeng, L.; Gensch, T.; Sigman, M.S.; Doyle, A.G.; Anslyn, E. V. The Evolution of Data-Driven Modeling in Organic Chemistry.  ACS Cent. Sci. 2021, 7, 1622-1637. https://doi.org/10.1021/acscentsci.1c00535

  • Chen, J., Guo, K., Liu, Z., Isayev, O. and Zhang, X., 2024, March. Uncertainty-Aware Yield Prediction with Multimodal Molecular Features. Proc. AAAI Conf. AI 2024 38, 8274-8282. https://doi.org/10.1609/aaai.v38i8.28668

  • Newman-Stonebraker, S. H.;  Smith, S. R.;  Borowski, J. E.;  Peters, E.;  Gensch, T.;  Johnson, H. C.;  Sigman, M. S.; Doyle, A. G., Univariate classification of phosphine ligation state and reactivity in cross-coupling catalysis. Science 2021, 374, 301-308  science.org/doi/10.1126/science.abj4213

  • Kariofillis S, Jiang S, Żurański A, Gandhi S, Martinez Alvarado J, Doyle A. Using Data Science to Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical Sources. J. Am. Chem. Soc. 2022, 144 ASAP . https://pubs.acs.org/doi/10.1021/jacs.1c12203

Experimental Chemistry

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