Thomas Hartung ^1* Michael Taynnan Barros ² Brett J. Kagan ³ Lena Smirnova ¹

• ¹ Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, United States
• ² University of Essex, Colchester, East of England, United Kingdom
• ³ Cortical Labs, Melbourne, Australia

At its core, synthetic biological intelligence seeks to enhance the functionality of biological systems by integrating artificial intelligence (AI) technologies. Organoid Intelligence (OI) (Smirnova et al., 2023), a subset of SBI, demonstrates the potential to revolutionize biomedical research by leveraging organoids-miniature, lab-grown versions of human organs derived from stem cells-as computational models. These models o^er unparalleled insights into human biology and disease mechanisms. This Research Topic is part of the attempts of establishing a community to realize this promise (Morales Patoja et al., 2023;Hartung et al., 2023).The ability to use organoids as personalized disease models is a significant advancement.They provide a platform to test drug e^icacy and toxicity in patient-specific contexts, moving us closer to truly individualized medicine. Moreover, the potential to model rare diseases and genetic disorders, which often lack e^ective animal or in-vitro analogs, underscores the societal and medical value of this research. While the promise of SBI and OI is immense, the field faces several challenges. This starts with a lack of common nomenclature, aka ontology (Kagan et al., 2024). Reproducibility of synthetic biological models, the e^iciency of AI algorithms in interpreting complex biological data, and the integration of these systems into existing research and clinical pipelines remain hurdles. Additionally, interfacing and controlling these biological systems from a bioengineering perspective is still largely uncharted.The research presented in this Topic demonstrates that these challenges are not insurmountable. Innovative experimental frameworks and novel in-vitro models inspired by in-silico solutions provide a roadmap for overcoming these barriers. Engineering advancements in interfaces and hardware will further accelerate progress in this domain. As we stand on the brink of creating living, thinking systems that merge biological and digital realms, ethical considerations are paramount. The implications of SBI and OI extend beyond medicine and research to broader societal concerns, including privacy, consent, and the security of biological data. These topics require multidisciplinary dialogue and the establishment of robust ethical frameworks. This Research Topic highlights the transformative potential of combining synthetic biology and artificial intelligence. It lays the groundwork for future exploration of themes such as unconventional computing, in-vitro modeling, and the integration of biology with digital engineering. As SBI and OI evolve, they will redefine our understanding of intelligence and push the boundaries of what is possible in technology and medicine.As Topic Editors, we are inspired by the breadth of work showcased in this collection and the passion of the researchers contributing to this burgeoning field. With continued collaboration, innovation, and ethical stewardship, synthetic biological intelligence and organoid intelligence will undoubtedly revolutionize our approach to understanding and solving complex biological challenges.