SLAS Technology Vol. 36 charts the next era of intelligent laboratory automation

The volume spans drug discovery, synthetic biology, laboratory digitalization and a perspective on how advances in life sciences are impacting aging.

SLAS (Society for Laboratory Automation and Screening)

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SLAS Technology Vol. 36 Charts the Next Era of Intelligent Laboratory Automation

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Credit: SLAS Publishing

Oak Brook, IL – Volume 36 of SLAS Technology includes two editorials, one literature highlight, two original research articles, two reviews and two Special Issue (SI) features.

Editorials

• Mass Spectrometry Applications for High-Throughput Experimentation in Supporting Drug Discovery
  High-throughput experimentation paired with mass spectrometry (MS) is accelerating drug discovery by enabling rapid, parallel analysis of thousands of chemical reactions and biological assays. While challenges such as data management and matrix effects remain, advances in MS technology, direct-to-biology workflows and AI integration are driving end-to-end optimization of the drug discovery process.
• 2nd EUOS/SLAS Joint Challenge: Prediction of Spectral Properties of Compounds
  The Second Joint Machine Learning Challenge, built on the success of the first EU-OPENSCREEN/SLAS challenge, demonstrates how open, well-curated experimental datasets can accelerate the development of advanced machine learning methods for drug discovery. The editorial outlines the challenge–the full technical descriptions of the winning solutions will be published in SLAS Technology later this year.

Reviews

• Guide to Liquid Volume Measurements: A Review of Methods and Technologies
  This review surveys liquid volume measurement methods and technologies for life science laboratories, covering volumes from picoliters to milliliters across applications in biopharmaceutical and clinical settings. Key attributes evaluated include volume range, precision, accuracy, workflow integration and regulatory compliance.
• Toward Full Automation in Synthetic Biology: A Progressive Conceptual Framework Integrating Robotics and Intelligent Agents
  This article examines the role of robotics and AI in automating synthetic biology workflows, covering progress of physical and cognitive automation in synthetic biology. The authors propose a dual framework for both total automation of the full Design-Build-Test-Learn cycle and progressive automation that can be adapted to diverse laboratory contexts, while addressing the ethical considerations of increasingly autonomous biological research.

Original Research

• Implementation of a Modular Digital Laboratory Infrastructure for SiLA2 Based Devices
  This article presents a laboratory digitalization framework using open-source software and hardware, demonstrated through a SiLA-based continuous chromatography system for Green Fluorescent Protein (GFP) purification. The framework includes device control, data management, evaluation, and maintenance strategies for software and hardware.
• Low-Cost CNC-Based Media Dispensing System for Biotechnology Laboratories
  A custom Computer Numerical Control-based Automated Media Dispensing System was developed and validated over two years for a plant biotechnology lab, outperforming manual dispensing while maintaining efficiency At approximately one-fiftieth the cost of comparable commercial systems, the modular design offers an accessible and ergonomic automation solution for research laboratories.

Literature Highlight

• Life Sciences and Aging
  This entry in the Life Sciences and Society series by SLAS Technology Associate Editor Kerstin Thurow, PhD, centers on advances in genomics, AI, and senolytic therapies that are giving life sciences increased power to intervene in the aging process, shifting the focus toward extending healthy lifespan rather than longevity alone.

Special Issues

• Robotics in Laboratory Automation
  This editorial introduces the Special Issue (SI) Robotics in Laboratory Automation, which highlights advances in robotic systems that improve experimental precision, reproducibility and throughput. The SI addresses key developments in standardization and intelligent automation while acknowledging current limitations and emerging trends shaping the field.
• Revolutionizing Transcriptomics from Single-Cell Insights to RNA-Based Interventions
  This SI on systems genetics examines gene and molecular interaction networks, utilizing high-throughput sequencing and multi-omics technologies to understand how genetic networks influence phenotypes. It emphasizes the significance of personalized medicine, therapeutic target discovery and biomarker identification through integrated genomic and epigenomic approaches.

All active SLAS Discovery and SLAS Technology call for papers are available at: https://www.slas.org/publications/call-for-papers/

This volume of SLAS Technology is available at https://www.slas-technology.org/issue/S2472-6303(25)X0007-8

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SLAS Technology reveals how scientists adapt technological advancements for life sciences exploration and experimentation in biomedical research and development. The journal emphasizes scientific and technical advances that enable and improve:

• Life sciences research and development
• Drug delivery
• Diagnostics
• Biomedical and molecular imaging
• Personalized and precision medicine

SLAS (Society for Laboratory Automation and Screening) is an international professional society of academic, industry and government life sciences researchers and the developers and providers of laboratory automation technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.

SLAS Technology: Translating Life Sciences Innovation, 2024 Impact Factor 3.7. Editor-in-Chief Edward Kai-Hua Chow, PhD, KYAN Technologies, Los Angeles, CA (USA).

 

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Journal

SLAS TECHNOLOGY

 

New study identifies shared mathematical principle linking how cells, companies, and cities diversify

New research from MIT Sloan and the Santa Fe Institute shows common patterns in the growth of biological and social systems, offering insights into the challenge of introducing new functions

MIT Sloan School of Management

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The perspective of the research paper is through a complexity science lens, understanding the interaction between components and how this affects the overall system. Despite a lot of heterogeneity in the different types of systems the researchers studied, their analysis finds that many systems exhibit common patterns of behavior. This work references Heaps’ Law. The research team analyzed data from bacterial and microbial cells, US federal agencies, companies and universities, and metropolitan areas, and explained the commonalities and differences in the data with a mathematical model for function diversity growth.

 

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Credit: Jennifer Tapias Derch

Cambridge, Mass., March 25, 2026—When companies seek to grow their capabilities, such as by implementing AI or expanding their services, this might not be easily achieved by simply adding more employees to handle new tasks. New research presents a mathematical model analyzing a wide variety of complex systems — from bacterial cells to corporations to cities — finding, in most cases, the more systems grow, the fewer new functions are added.

The Proceedings of the National Academies of Sciences paper, “Scaling Laws for Function Diversity and Specialization Across Complex Systems,” was co-led by Vicky Chuqiao Yang, assistant professor at the MIT Sloan School of Management and a former Santa Fe Institute (SFI) Omidyar Fellow,  and SFI mathematical biologist James Holehouse, along with co-authors Hyejin Youn, José Ignacio Arroyo, Sidney Redner, Geoffrey B. West, and Christopher P. Kempes, all of whom are affiliated with the SFI.

“The perspective of this paper is through a complexity science lens, understanding the interaction between components and how this affects the overall system,” said Yang. “Despite a lot of heterogeneity in the different types of systems we studied, our analysis finds that many systems exhibit common patterns of behavior."

This work references Heaps’ Law, a formula developed in the field of linguistics, which finds that as the length of text grows longer, the rate at which new words are introduced decreases. The research team analyzed data from bacterial and microbial cells, US federal agencies, companies and universities, and metropolitan areas, and explained the commonalities and differences in the data with a mathematical model for function diversity growth.

Thinking of the distinct functions as the “unique words” and individual systems as “texts,” the researchers found that almost all of these systems followed the same pattern. For example, as a biological cell grows, it tends to produce more of the proteins it already uses rather than developing new ones. Similarly, as a company grows in size, the creation of new job functions slows down and employees will mostly be hired for established jobs rather than new ones.

Yang says this study can shape how companies think about growth and complexity, keeping in mind that increasing the size of systems does not proportionally increase the quantity of different functions within it. As most systems get bigger, the pace at which new functions are added slows at sublinear pace. 

“If an organization wants to add a new function category of AI, our research suggests that you can’t just hire a person or people for that role and be done,” said Yang. “To truly expand into a new function, it seems that you need certain infrastructure and existing functions to expand. If you want to become more complex, there’s a foundation you first have to set up.”

Across all of the different types of systems the researchers examined, the function diversity of cities didn’t seem to follow Heaps’ Law, like the others. Function diversity appears to grow more rapidly with population in smaller cities, but slows down as cities become larger. This may be due to the fundamentally different structure and goals of cities.

In addition to looking at “function diversity,” the research identified common patterns in “function abundance.” In corporations and organizations, this represents the number of employees performing each type of job. For example, an organization might have a high concentration of administrative or medical employees. Data showed that these common roles tend to increase more rapidly than less common roles, and remain in abundance over time. The organization grows by hiring more people into these established, abundant jobs rather than creating new ones.

Despite the very different systems analyzed,  the researchers’ new mathematical model reveals significant, underlying commonalities of how complexity grows.

“One key takeaway is a striking empirical regularity in the relationship between organizational size and functional complexity,” said Holehouse. “In other words, if an organization aims to be able to do a certain range of tasks, it needs to reach a certain size first.”

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Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.250972912 

Method of Research

Data/statistical analysis

Subject of Research

Cells

Article Title

Scaling laws for function diversity and specialization across socioeconomic and biological complex systems

 

Breakthroughs in wireless power and data transfer systems pave the way for advanced biomedical implants

ELSP

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The WPDT systems mainly consists of power amplifiers, coils, modulation/demodulation blocks, rectifier and voltage regulator. Modulation schemes (ASK, PSK, FSK) show data encoding methods. The review mainly introduces the circuit-level innovations of each module, the link optimization strategies for coil, as well as the core challenges faced by the WPDT systems and future outlook.

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Credit: Binyao Hong/Shenzhen International Graduate School, Tsinghua University, Songpin Ma/Shenzhen International Graduate School, Tsinghua University, Zhihua Wang/Tsinghua University

A comprehensive review published in Neuroelectronics sheds light on the latest advancements in wireless power and data transfer (WPDT) systems for implanted medical devices (IMDs), and outlines innovative solutions to enhance power transfer efficiency (PTE), data communication, and biosafety, thereby providing a reliable reference for the future design of IMDs.

Traditional IMDs rely on batteries that require surgical replacement, posing risks and inconveniences to patients. WPDT have emerged as a promising alternative, WPDT has emerged as a promising alternative, utilizing magnetic fields to transmit energy between external and internal coils, with data transfer realized via modulation and demodulation. Thus, ensuring efficient and safe wireless power and data transfer has become paramount. A recent review article, authored by a team of experts from Tsinghua University, provides a detailed analysis of the current state-of-the-art technologies and future directions in WPDT systems for IMDs.

Revolutionizing Power Transfer Efficiency

The review highlights significant innovations in the power path of WPDT systems, including reconfigurable power amplifiers, adaptive delay-compensated active rectifiers, and high-efficiency voltage regulators. Moreover, coil improvements are pivotal. Optimizing coil geometry, turns, and wire gauge, along with using advanced tech like Litz wire and 3D-printed coils, can greatly enhance magnetic coupling and reduce losses. These advancements have led to substantial improvements in PTE, with some systems achieving over 90% efficiency under optimal conditions.

"One of the key breakthroughs is the development of reconfigurable power amplifiers that adjust their operation modes based on load variations, resulting in over 20% improvement in overall PTE," explains one of the lead authors of the review. "Additionally, adaptive delay-compensated active rectifiers minimize turn-on/off delays and reverse current loss, further enhancing system efficiency."

Enhancing Data Communication Capabilities

Bidirectional data communication is essential for IMDs to transmit physiological signals and receive control commands. The review explores various modulation schemes, such as Amplitude-Shift Keying (ASK), Phase-Shift Keying (PSK), Frequency-Shift Keying (FSK), and Load-Shift Keying (LSK). These techniques enable reliable and efficient data transfer, even in challenging biological environments.

"Emerging techniques like Delay-Shift Keying (DSK) are particularly promising, as they allow for simultaneous voltage regulation and high-speed data transmission without compromising efficiency," states another author of the review. "Such innovations are crucial for enabling real-time monitoring and precise control of IMDs."

Addressing Biosafety Concerns

Ensuring the biosafety of WPDT systems is of utmost importance to prevent tissue heating, electromagnetic interference, and other potential risks. The review discusses strategies for optimizing thermal management and packaging materials to minimize these risks. For instance, the use of biocompatible and flexible packaging materials can enhance patient comfort and reduce the risk of tissue damage.

"We must ensure that WPDT systems adhere to strict biosafety standards to protect patients from any potential harm," emphasizes a co-author of the review. "This includes careful design of the electromagnetic fields, selection of appropriate packaging materials, and thorough testing in biological models."

Future Directions and Machine Learning Integration

Looking ahead, the review identifies several key research directions, including the development of miniature components, advanced circuit optimization, and the integration of machine learning algorithms. Machine learning techniques, in particular, hold great promise for optimizing coil design, predicting optimal parameter combinations, and compensating for misalignment and load variations.

"Machine learning algorithms can analyze vast amounts of data to identify patterns and optimize system performance in real-time," explains a leading researcher. "This could lead to significant improvements in the efficiency, reliability, and safety of WPDT systems for IMDs."

Conclusion

The comprehensive review article provides a valuable overview of the latest advancements and future directions in WPDT systems for biomedical implants. As research in this field continues to progress, these innovations promise to revolutionize the treatment and management of various medical conditions, ultimately improving the quality of life for patients worldwide.

This paper "A review of wireless power and data transfer systems for biomedical implants” was published in Neuroelectronics.

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Journal

Neuroelectronics

DOI

10.55092/neuroelectronics20260004 

Method of Research

Systematic review

Subject of Research

Not applicable

Article Title

A review of wireless power and data transfer systems for biomedical implants

Article Publication Date

18-Mar-2026