Over the past decade, collective intelligence, i.e., the intelligence that emerges from collective efforts, has transformed complex problem-solving and decision-making. In drug discovery, decision-making often relies on medicinal chemistry intuition. The present study explores the application of collective intelligence in drug discovery, focusing on lead optimization. Ninety-two Sanofi researchers with diverse expertise participated anonymously in an exercise centered on ADMET-related questions. Their feedback was used to build a collective intelligence agent, which was compared to an artificial intelligence model. The study led to three major conclusions: first, collective intelligence improves decision-making in optimizing ADMET endpoints, compared to individual decisions. Second, collective intelligence outperforms artificial intelligence for all other endpoints but hERG inhibition. Finally, we observe complementarity between collective human and artificial intelligence. Overall, this research highlights the potential of collective intelligence in drug discovery and the importance of a synergistic approach combining human and artificial intelligence in project decision making.
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http://dx.doi.org/10.1021/acs.jmedchem.4c03066 | DOI Listing |
Sci Rep
March 2025
Amrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Amritapuri, Kerala, 690525, India.
This study examines the imperative to align artificial general intelligence (AGI) development with societal, technological, ethical, and brain-inspired pathways to ensure its responsible integration into human systems. Using the PRISMA framework and BERTopic modeling, it identifies five key pathways shaping AGI's trajectory: (1) societal integration, addressing AGI's broader societal impacts, public adoption, and policy considerations; (2) technological advancement, exploring real-world applications, implementation challenges, and scalability; (3) explainability, enhancing transparency, trust, and interpretability in AGI decision-making; (4) cognitive and ethical considerations, linking AGI's evolving architectures to ethical frameworks, accountability, and societal consequences; and (5) brain-inspired systems, leveraging human neural models to improve AGI's learning efficiency, adaptability, and reasoning capabilities. This study makes a unique contribution by systematically uncovering underexplored AGI themes, proposing a conceptual framework that connects AI advancements to practical applications, and addressing the multifaceted technical, ethical, and societal challenges of AGI development.
View Article and Find Full Text PDFNat Commun
March 2025
School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, China.
Monolayers of confluent elongated cells are frequently considered active nematics, featuring topological defects. In extensile systems, where cells extend further along their long axis, they can accumulate at defects and escape from defects. Nevertheless, collective dynamics surrounding integer defects remain insufficiently understood.
View Article and Find Full Text PDFJ Med Chem
March 2025
Molecular Design Sciences, Integrated Drug Discovery, Sanofi, 1 Imp. Des Ateliers, Vitry-sur-Seine 94400, France.
Over the past decade, collective intelligence, i.e., the intelligence that emerges from collective efforts, has transformed complex problem-solving and decision-making.
View Article and Find Full Text PDFJ Chem Phys
March 2025
Department of Biological Science, Indian Institute of Science Education and Research (IISER), Kolkata, India.
Membrane protein folding in the viscous microenvironment of a lipid bilayer is an inherently slow process that challenges experiments and computational efforts alike. The folding kinetics is moreover associated with topological modulations of the biological milieu. Studying such structural changes in membrane-embedded proteins and understanding the associated topological signatures in membrane leaflets, therefore, remain relatively unexplored.
View Article and Find Full Text PDFFront Pharmacol
February 2025
Organon, Jersey City, NJ, United States.
Experience with the use of biosimilars in real-life practice provides an excellent opportunity to collect real-world evidence aimed at addressing residual uncertainties about biosimilars. Hence, this aims to explore the role of real-world evidence on biosimilars by showcasing how real-world evidence studies have contributed to addressing key questions affecting biosimilar market access. We find that the comparable efficacy and safety of a biosimilar and the reference product is corroborated by real-world evidence.
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