Meaningful Steps Toward Organoid Intelligence Being Taken

Artificial Intelligence (AI) has become a familiar term in the technological world today, shaping numerous aspects of our daily lives. However, there's a new frontier emerging in the realm of science – Organoid Intelligence (OI) – which, though not as widely recognized as AI, holds remarkable potential. But what exactly is Organoid Intelligence, and why is it garnering attention in scientific circles?

The Institute of Electrical and Electronics Engineers (IEEE) defines Organoid Intelligence as a “collective effort to promote the use of brain organoids—tiny spherical masses of brain tissue grown from stem cells—for computation, drug research, and as a model to study at a small scale how a complete brain may function.”

The organization also points out two breakthrough research that have made the development of organoids possible. We will come to those researches in a while. But before that, we will delve deeper into understanding what the scientific community thinks about Organoid Intelligence's potential. 

A concerned team of researchers believes that OI-based biocomputing systems will allow faster decision-making. It will help learn continuously during tasks and introduce greater energy and data efficiency to the process. It would also help understand the pathophysiology behind severely damaging developmental and degenerative diseases such as dementia. Understandably, it will also aid the treatment of these diseases by identifying novel therapeutic approaches. 

Given the immense capability of OI to do good, multiple meaningful intelligences toward Organoid Intelligence (OI) are being taken. We will look at them in the coming segments. But we shall start with the two breakthrough pieces of research on organoid development we have already mentioned. 

Induced Pluripotent Stem Cell-Derived Organoids

IPSC-derived organoids came into discussions during the COVID-19 outbreak. A scientific research paper listed out details on IPSC-derived airway organoids, brain organoids, intestinal organoids, liver organoids, blood vessel organoids, kidney organoids, inner ear organoids, etc. Given this variety, our discussion will now narrow down to focus specifically on the brain organoids part.

The paper lists three crucial points: 

• For the first time, scientists developed brain organoids using spontaneous differentiation of embryoid bodies (EBs).
• The first brain organoids were highly heterogeneous. 
• The heterogeneity led to the researchers developing region-specific brain organoids by influencing specific signaling pathways. 

Another research that helped organoid development was around 3D-cell-culturing techniques. 

3D Cell Culture

The motivation behind developing 3D cell culturing techniques stemmed from the inadequacies observed in culturing cells in two dimensions. Two-dimensional cell culture practices and methods fail to reproduce the anatomy or physiology of tissue for informative or useful study.

3D cell culturing techniques – on the other hand – are closer to animal and human physiology. And as they become more mature, they will help to design and develop co-cultures. These techniques could prove useful in engineering tissues for clinical delivery and developing models for drug screenings.

Such advancements in 3D cell culturing are also pivotal in the research around IPSC-derived organoids and organoid intelligence. IPSCs, for instance, can develop into any cell found in an animal's body. 

3D culturing techniques and 3D-scaffolding methods, specifically, help biologists grow IPSC-derived neural tissues vertically and horizontally, paving the way to developing the interneuronal networks observed in an animal's brain.

Replicating this intricate network helps go deeper into organoid intelligence and develop more sophisticated methods.

Brain Organoid Reservoir Computing for AI

Research published in the journal Nature Electronics points out the achievements registered in brain-inspired computing hardware that emulates the structure and working principles of the brain. Researchers believe that this development has the potential to address the current limitations of AI. 

The research, in particular, reports an AI hardware approach that leverages adaptive reservoir computation of biological neural networks in a brain organoid. The approach goes by the name Brainoware. It pivots on performing computation by sending and receiving information from the brain organoid through a high-density multielectrode array. 

Organic Semiconductor Synthesis: Opening Up New Horizons for Super-Efficient Electronic Devices

A team of researchers at UNIST's Department of Chemistry facilitated the space to further open up to innovation opportunities achieving a breakthrough in organic semiconductor synthesis. The researchers reported the synthesis and characterization of a B2N2 anthracene derivative with a BNBN unit formed by converting the BOBN unit at the zigzag edge. The findings are expected to help develop larger acenes with multiple BN units that will have many applications in organic electronics. 

According to Songhua Jeong, the first author of this study:

“Our study on anthracene, a type of acene widely recognized as an organic semiconductor, has laid the groundwork for future advancements in the field.” 

Mr Jeong further went on to say: 

“The continuous BN bonding synthesized through this research holds great potential for applications in organic semiconductors.”

With diverse research opening up avenues for Organoid Intelligence to prosper, experts in this field say that organoid intelligence may become powerful enough to power our computers in the future. 

A future does not appear unrealistic anymore, where lab-grown brain cells would store and retrieve large amounts of data with smaller demands for energy. With further scale-up achieved, these solutions may even develop a consciousness to think or feel of their own. 

Organoid Intelligence: Workshops and Funding

Diverse efforts are underway to deliberate further on the potential of organoid intelligence. 

Between February 22nd and 24th, 2022, John Hopkins University held the first Organoid Intelligence workshop. The purpose was to form an OI community and formulate the foundation for establishing OI as a new scientific discipline. The motivation behind the workshop came from the belief that OI could radically alter computing, neurological research, and drug development. 

Further validation of the potential of OI came when the United States National Science Foundation Directorate for Engineering planned one new area for the Emerging Frontiers in Research and Innovation (EFRI) program in FY 2024, and it was called ‘Engineering Organoid Intelligence.' 

The NSF is known for supporting science and engineering research and people related to it by providing facilities, instruments, and funding. The NSF had a budget of US$9.5 billion in the fiscal year 2023. These funds reach all fifty states in the US through grants given out to nearly 2,000 colleges, universities, and institutions. 

The ‘Engineering Organoid Intelligence' topic is aimed at supporting fundamental research on the development of engineered biocomputers through brain organoids. The NSF believed that Organoid cultures would soon have interfaces with electronics to deliver input and export output to external digital systems.  

Apart from universities, research institutions, and government departments, many companies have taken up the cause of advancing organoid intelligence. We will now look into some such companies and their endeavors. 

#1. Final Spark

Founded by Martin Kutter and Fred Jordan in 2014 and based out of Switzerland, Final Spark advocates for biological chip processors that consume much less energy. 

As claimed by the startup, it has tested 10 million neurons already in its endeavor to build thinking machines from live human neurons derived from skin. 

The startup is leveraging sophisticated cell-culturing techniques to exhibit the self-sustaining computing capability for the creation of future AI models. 

#2. BiologiC and NVIDIA

BiologiC Technologies, a company based out of Cambridge, UK, is known for its biocomputers, which the company defines as an “automated programmable and reconfigurable bioprocessing platform for multiple biological applications.” 

The solution's patented hardware architecture has four core modules: 

• The advanced routing core helps transport liquids and biogases through the system. 
• The input and output block helps control the loading of raw materials and the output of the final bioproduct. 
• The BPU model helps with bioprocessing activities such as cell growth, in-vitro transcription, etc. 
• Finally, the sensor core module helps with real-time monitoring of the bioprocess environment. 

On March 13, 2023, BiologiC Technologies joined NVIDIA Inception, a program that will help BiologiC integrate edge computing and AI into its biocomputers. This integration will eventually help BiologiC's biocomputers bring revolutionary improvements in its biology processing facilities and reduce the threat of diseases in a sustainable, accessible, and affordable way. 

According to available information, CPI Enterprises invested in BiologiC. CPI invests in high-potential deep tech for companies to scale up fast, playing the dual role of an investor and a technical support provider. 

According to Frank Millar, the chief executive of CPI: 

“Having collaborated closely over an extended period, we are impressed at the speed of execution and commercial traction of BiologIC. We see strong advantages in BiologIC's bio-computer system and the ability to increase bioprocess productivity relative to the competition in the sector.”

On November 21, 2023, NVIDIA reported revenue for the third quarter ended October 29, 2023, of $18.12 billion, up 206% from a year ago and up 34% from the previous quarter.

#3. BioMap and MBUZAI: Joint Efforts on Creating a Biocomputing Lab 

On March 14, 2023, BioMap struck a strategic collaboration with Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) to introduce the first biocomputing innovation research laboratory in the Middle East and address the needs of life science scenarios in the region. 

The cooperation would explore BioMap's cross-modal bio-computing model, xTrimo (Cross-model Transformer Representation of Interactome and Multi-Omics), in achieving large-scale life science models in protein generation, protein structure prediction, cell function prediction, and other life science tasks. 

The focus will be on achieving breakthroughs in AI-generated proteins (AIGP) to help with the Middle East's need for medical health, drug design, energy, and environmental protection.

Apart from protein design, BioMap's capabilities will also help achieve strong cell characterization capabilities, precise first-time modeling of immune cells, and more. 

Co-founded by Baidu CEO Robin Li, BioMap helps combine best-in-class AI and biotech capabilities to combat the most crucial problems in the life sciences industry, such as target discovery, de-novo drug design, and enzyme optimization.

The biological computing Chinese startup raised more than US$100 million in series A funding, according to reports published in August 2021. The round was led by CGV Capital. Other investors included Baidu, Legend Capital, Bluerun Ventures, and Xianghe Capital.

Which Way OI is Headed to?

Undoubtedly, OI has captured the scientific community's imagination. Sophisticated technological companies and minds are investing resources as well. How the future will shape out for OI would, however, depend on a few crucial aspects that relate to its developmental nature. 

The success of OI as a revolutionary technological innovation would depend on how fast, efficient, and powerful it might become in comparison with silicon-based computing and AI. Moreover, enhanced standards of speed, efficiency, and power would have to have lower demands for energy to make it more attractive and cost-effective. 

In the future, OI needs to become truly multidisciplinary since it is a highly complex and intricate exercise to scale current brain organoids into durable 3D structures. These structures will be full of cells and genes that help humans learn new, complex things. 

Moreover, devising the ideal biocomputers would require connecting these organoids with cutting-edge input and output devices, particularly electronic ones equipped with high-end AI and machine learning systems. 

Researchers in the field believe that there is a great need for new and sophisticated models, algorithms, and interface technologies to establish effective and meaningful communication with these brain organoids. To make the output best-in-class, creators need to know how they learn, compute, process, and store the data. 

The scope of data, as evident already, will be massive and immense in volume. 

In the interim period, OI research will also help improve our understanding of how the brain and its deep and intricate neurological network functions. These understandings will help treat patients who suffer from neurological diseases better.

Finally, replicating the capabilities of a human brain in a lab environment could become an achievement with humongous consequences. The potential for misuse could be significantly high. Therefore, from the very early days, the scientific community must ensure that research and development around OI stay very sensitive to our society's ethical systems. The ethical framework should be no less than a defining paradigm for OI to thrive in the future. 

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