First Organoid Intelligence (OI) workshop to form an OI community

Itzy E. Morales Pantoja; Lena Smirnova; Alysson R. Muotri; Karl J. Wahlin; Jeffrey Kahn; J. Lomax Boyd; David H. Gracias; Timothy D. Harris; Tzahi Cohen-Karni; Brain S. Caffo; Alexander S. Szalay; Fang Han; Donald J. Zack; Ralph Etienne-Cummings; Akwasi Akwaboah; July Carolina Romero; Dowlette-Mary Alam El Din; Jesse D. Plotkin; Barton L. Paulhamus; Erik C. Johnson; Frederic Gilbert; J. Lowry Curley; Ben Cappiello; Jens C. Schwamborn; Eric J. Hill; Paul Roach; Daniel Tornero; Caroline Krall; Rheinallt Parri; Fenna Sillé; Andre Levchenko; Rabih E. Jabbour; Brett J. Kagan; Cynthia A. Berlinicke; Qi Huang; Alexandra Maertens; Kathrin Herrmann; Katya Tsaioun; Raha Dastgheyb; Christa Whelan Habela; Joshua T. Vogelstein; Thomas Hartung

doi:10.3389/frai.2023.1116870

First Organoid Intelligence (OI) workshop to form an OI community

Itzy E. Morales Pantoja
, Lena Smirnova
, Alysson R. Muotri
, Karl J. Wahlin
, Jeffrey Kahn
, J. Lomax Boyd
, David H. Gracias
, Timothy D. Harris
, Tzahi Cohen-Karni
, Brain S. Caffo
, Alexander S. Szalay
, Fang Han
, Donald J. Zack
, Ralph Etienne-Cummings
, Akwasi Akwaboah
, July Carolina Romero
, Dowlette-Mary Alam El Din
, Jesse D. Plotkin
, Barton L. Paulhamus
, Erik C. Johnson

Frederic Gilbert, J. Lowry Curley, Ben Cappiello, Jens C. Schwamborn, Eric J. Hill, Paul Roach, Daniel Tornero, Caroline Krall, Rheinallt Parri, Fenna Sillé, Andre Levchenko, Rabih E. Jabbour, Brett J. Kagan, Cynthia A. Berlinicke, Qi Huang, Alexandra Maertens, Kathrin Herrmann, Katya Tsaioun, Raha Dastgheyb, Christa Whelan Habela, Joshua T. Vogelstein, Thomas Hartung^*

^*Corresponding author for this work

Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
Center for Academic Research and Training in Anthropogeny (CARTA), Archealization Center (ArchC), Kavli Institute for Brain and Mind, University of California, San Diego, San Diego, CA, United States
Viterbi Family Department of Ophthalmology & the Shiley Eye Institute, UC San Diego, La Jolla, CA, United States
Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, United States
Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
Mark Foundation Center for Advanced Genomics and Imaging, Johns Hopkins University, Baltimore, MD, United States
Department of Statistics and Economics, University of Washington, Seattle, WA, United States
Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
Philosophy Program, School of Humanities, University of Tasmania, Hobart, TAS, Australia
AxoSim Inc., New Orleans, LA, United States
Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
Department of Chemistry, School of Science, Loughborough University, Loughborough, Leicestershire, United Kingdom
Clinic Hospital August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
Department of Molecular and Comparative Pathobiology, Johns Hopkins University, Baltimore, MD, United States
Department of Biomedical Engineering, Yale Systems Biology Institute, Yale University, New Haven, CT, United States
Department of Bioscience and Biotechnology, University of Maryland Global Campus, Rockville, MD, United States
Cortical Labs, Melbourne, VIC, Australia
Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States
Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
Center for Alternatives to Animal Testing (CAAT)-Europe, University of Konstanz, Konstanz, Germany

Research output: Contribution to journal › Review article › peer-review

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Abstract

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Original language	English
Article number	1116870
Number of pages	15
Journal	Frontiers in Artificial Intelligence
Volume	6
Early online date	28 Feb 2023
DOIs	https://doi.org/10.3389/frai.2023.1116870
Publication status	Published - 28 Feb 2023

Bibliographical note

Copyright © 2023 Morales Pantoja, Smirnova, Muotri, Wahlin, Kahn, Boyd, Gracias, Harris, Cohen-Karni, Caffo, Szalay, Han, Zack, Etienne-Cummings, Akwaboah, Romero, Alam El Din, Plotkin, Paulhamus, Johnson, Gilbert, Curley, Cappiello, Schwamborn, Hill, Roach, Tornero, Krall, Parri, Sillé, Levchenko, Jabbour, Kagan, Berlinicke, Huang, Maertens, Herrmann, Tsaioun, Dastgheyb, Habela, Vogelstein and Hartung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Funding Information:
The workshop was financially supported by the Doerenkamp-Zbinden Foundation through the Transatlantic Thinktank for Toxicology (t4). The workshop was cohosted the Johns Hopkins Whiting School of Engineering and Frontiers. Preliminary work was financed by a Johns Hopkins Discovery Grant [TH, (PI), BC, DG, and LS] and T32ES007141-38 grant.

Keywords

Artificial Intelligence
microphysiological systems
brain
electrophysiology
cognition
artificial intelligence
biological computing
Organoid Intelligence

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frai-06-1116870.pdf
Copyright © 2023 Morales Pantoja, Smirnova, Muotri, Wahlin, Kahn, Boyd, Gracias, Harris, Cohen-Karni, Caffo, Szalay, Han, Zack, Etienne-Cummings, Akwaboah, Romero, Alam El Din, Plotkin, Paulhamus, Johnson, Gilbert, Curley, Cappiello, Schwamborn, Hill, Roach, Tornero, Krall, Parri, Sillé, Levchenko, Jabbour, Kagan, Berlinicke, Huang, Maertens, Herrmann, Tsaioun, Dastgheyb, Habela, Vogelstein and Hartung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Final published version, 712 KBLicence: CC BY 4.0

Cite this

Morales Pantoja, I. E., Smirnova, L., Muotri, A. R., Wahlin, K. J., Kahn, J., Boyd, J. L., Gracias, D. H., Harris, T. D., Cohen-Karni, T., Caffo, B. S., Szalay, A. S., Han, F., Zack, D. J., Etienne-Cummings, R., Akwaboah, A., Romero, J. C., Alam El Din, D.-M., Plotkin, J. D., Paulhamus, B. L., ... Hartung, T. (2023). First Organoid Intelligence (OI) workshop to form an OI community. Frontiers in Artificial Intelligence, 6, Article 1116870. https://doi.org/10.3389/frai.2023.1116870

@article{c12f2c043a6648938c7504fe938601cb,

title = "First Organoid Intelligence (OI) workshop to form an OI community",

abstract = "The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.",

keywords = "Artificial Intelligence, microphysiological systems, brain, electrophysiology, cognition, artificial intelligence, biological computing, Organoid Intelligence",

author = "\{Morales Pantoja\}, \{Itzy E.\} and Lena Smirnova and Muotri, \{Alysson R.\} and Wahlin, \{Karl J.\} and Jeffrey Kahn and Boyd, \{J. Lomax\} and Gracias, \{David H.\} and Harris, \{Timothy D.\} and Tzahi Cohen-Karni and Caffo, \{Brain S.\} and Szalay, \{Alexander S.\} and Fang Han and Zack, \{Donald J.\} and Ralph Etienne-Cummings and Akwasi Akwaboah and Romero, \{July Carolina\} and \{Alam El Din\}, Dowlette-Mary and Plotkin, \{Jesse D.\} and Paulhamus, \{Barton L.\} and Johnson, \{Erik C.\} and Frederic Gilbert and Curley, \{J. Lowry\} and Ben Cappiello and Schwamborn, \{Jens C.\} and Hill, \{Eric J.\} and Paul Roach and Daniel Tornero and Caroline Krall and Rheinallt Parri and Fenna Sill{\'e} and Andre Levchenko and Jabbour, \{Rabih E.\} and Kagan, \{Brett J.\} and Berlinicke, \{Cynthia A.\} and Qi Huang and Alexandra Maertens and Kathrin Herrmann and Katya Tsaioun and Raha Dastgheyb and Habela, \{Christa Whelan\} and Vogelstein, \{Joshua T.\} and Thomas Hartung",

note = "Copyright {\textcopyright} 2023 Morales Pantoja, Smirnova, Muotri, Wahlin, Kahn, Boyd, Gracias, Harris, Cohen-Karni, Caffo, Szalay, Han, Zack, Etienne-Cummings, Akwaboah, Romero, Alam El Din, Plotkin, Paulhamus, Johnson, Gilbert, Curley, Cappiello, Schwamborn, Hill, Roach, Tornero, Krall, Parri, Sill{\'e}, Levchenko, Jabbour, Kagan, Berlinicke, Huang, Maertens, Herrmann, Tsaioun, Dastgheyb, Habela, Vogelstein and Hartung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Funding Information: The workshop was financially supported by the Doerenkamp-Zbinden Foundation through the Transatlantic Thinktank for Toxicology (t4). The workshop was cohosted the Johns Hopkins Whiting School of Engineering and Frontiers. Preliminary work was financed by a Johns Hopkins Discovery Grant [TH, (PI), BC, DG, and LS] and T32ES007141-38 grant. ",

year = "2023",

month = feb,

day = "28",

doi = "10.3389/frai.2023.1116870",

language = "English",

volume = "6",

journal = "Frontiers in Artificial Intelligence",

issn = "2624-8212",

publisher = "Frontiers Media S.A.",

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Morales Pantoja, IE, Smirnova, L, Muotri, AR, Wahlin, KJ, Kahn, J, Boyd, JL, Gracias, DH, Harris, TD, Cohen-Karni, T, Caffo, BS, Szalay, AS, Han, F, Zack, DJ, Etienne-Cummings, R, Akwaboah, A, Romero, JC, Alam El Din, D-M, Plotkin, JD, Paulhamus, BL, Johnson, EC, Gilbert, F, Curley, JL, Cappiello, B, Schwamborn, JC, Hill, EJ, Roach, P, Tornero, D, Krall, C, Parri, R, Sillé, F, Levchenko, A, Jabbour, RE, Kagan, BJ, Berlinicke, CA, Huang, Q, Maertens, A, Herrmann, K, Tsaioun, K, Dastgheyb, R, Habela, CW, Vogelstein, JT & Hartung, T 2023, 'First Organoid Intelligence (OI) workshop to form an OI community', Frontiers in Artificial Intelligence, vol. 6, 1116870. https://doi.org/10.3389/frai.2023.1116870

TY - JOUR

T1 - First Organoid Intelligence (OI) workshop to form an OI community

AU - Morales Pantoja, Itzy E.

AU - Smirnova, Lena

AU - Muotri, Alysson R.

AU - Wahlin, Karl J.

AU - Kahn, Jeffrey

AU - Boyd, J. Lomax

AU - Gracias, David H.

AU - Harris, Timothy D.

AU - Cohen-Karni, Tzahi

AU - Caffo, Brain S.

AU - Szalay, Alexander S.

AU - Han, Fang

AU - Zack, Donald J.

AU - Etienne-Cummings, Ralph

AU - Akwaboah, Akwasi

AU - Romero, July Carolina

AU - Alam El Din, Dowlette-Mary

AU - Plotkin, Jesse D.

AU - Paulhamus, Barton L.

AU - Johnson, Erik C.

AU - Gilbert, Frederic

AU - Curley, J. Lowry

AU - Cappiello, Ben

AU - Schwamborn, Jens C.

AU - Hill, Eric J.

AU - Roach, Paul

AU - Tornero, Daniel

AU - Krall, Caroline

AU - Parri, Rheinallt

AU - Sillé, Fenna

AU - Levchenko, Andre

AU - Jabbour, Rabih E.

AU - Kagan, Brett J.

AU - Berlinicke, Cynthia A.

AU - Huang, Qi

AU - Maertens, Alexandra

AU - Herrmann, Kathrin

AU - Tsaioun, Katya

AU - Dastgheyb, Raha

AU - Habela, Christa Whelan

AU - Vogelstein, Joshua T.

AU - Hartung, Thomas

N1 - Copyright © 2023 Morales Pantoja, Smirnova, Muotri, Wahlin, Kahn, Boyd, Gracias, Harris, Cohen-Karni, Caffo, Szalay, Han, Zack, Etienne-Cummings, Akwaboah, Romero, Alam El Din, Plotkin, Paulhamus, Johnson, Gilbert, Curley, Cappiello, Schwamborn, Hill, Roach, Tornero, Krall, Parri, Sillé, Levchenko, Jabbour, Kagan, Berlinicke, Huang, Maertens, Herrmann, Tsaioun, Dastgheyb, Habela, Vogelstein and Hartung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Funding Information: The workshop was financially supported by the Doerenkamp-Zbinden Foundation through the Transatlantic Thinktank for Toxicology (t4). The workshop was cohosted the Johns Hopkins Whiting School of Engineering and Frontiers. Preliminary work was financed by a Johns Hopkins Discovery Grant [TH, (PI), BC, DG, and LS] and T32ES007141-38 grant.

PY - 2023/2/28

Y1 - 2023/2/28

N2 - The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

AB - The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22–24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

KW - Artificial Intelligence

KW - microphysiological systems

KW - brain

KW - electrophysiology

KW - cognition

KW - artificial intelligence

KW - biological computing

KW - Organoid Intelligence

UR - https://www.frontiersin.org/articles/10.3389/frai.2023.1116870/full

UR - https://www.scopus.com/pages/publications/85150177741

U2 - 10.3389/frai.2023.1116870

DO - 10.3389/frai.2023.1116870

M3 - Review article

C2 - 36925616

SN - 2624-8212

VL - 6

JO - Frontiers in Artificial Intelligence

JF - Frontiers in Artificial Intelligence

M1 - 1116870

ER -

First Organoid Intelligence (OI) workshop to form an OI community

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