|Proceedings of a Workshop—in Brief|
Cutting-Edge Scientific Capabilities for Biological Detection
Proceedings of a Workshop—in Brief
Recent advances in biotechnology and the life sciences have led to new and emerging paradigms for biological detection. For instance, technologies for analyzing brain activity are advancing rapidly and may soon find their way into a multitude of consumer electronics and medical devices. Other technologies are using biological or bio-inspired methods to analyze chemicals present in air, including those of biological origin, allowing the technologies to detect and sense compounds—such as disease biomarkers or industrial pollutants—with unprecedented speed and precision. What capabilities might these technologies unlock? What economic and societal drivers are influencing their development? What ethical, legal, and social issues do they raise? The National Academies of Sciences, Engineering, and Medicine hosted a virtual workshop on Cutting Edge Scientific Capabilities for Biological Detection on January 20, 21, and 28, 2022, to explore emerging technologies for biological detection and critical issues related to their development and use.
The workshop was organized by the National Academies’ Standing Committee on Biotechnology Capabilities and National Security Needs, which facilitates engagement between the national security community and biotechnology stakeholders. The Standing Committee’s work includes the identification of advanced biotechnologies with promising capabilities to meet national security needs and early-stage research that may lead to new or enhanced biotechnologies. Under this charge, the planning committee for the workshop identified two biological detection areas of interest with recent advancements and promising capabilities to highlight in the workshop: technologies for the detection of neural signatures, and technologies related to the digitization of olfaction and the detection and analysis of volatile organic compounds (VOCs).
Presenters and attendees from government, academia, and the biotechnology industry gathered for sessions of live discussions and pre-recorded talks examining cutting-edge research and developments related to these technologies. Sessions explored key advances and their potential applications in the near and long term; the innovation ecosystem that is driving the research, development, and application of these technologies; and critical societal implications of their adoption. Attendees also explored workforce needs, infrastructure, and policy and governance associated with the development and use of biological detection research and technologies.
This Proceedings of a Workshop—in Brief provides the rapporteurs’ high-level overview of the workshop presentations and discussions.
EMERGING TECHNOLOGIES FOR DETECTING NEURAL SIGNATURES
Nita Farahany (Duke University) and Diane DiEuliis (National Defense University) moderated sessions examining technologies designed to detect and analyze human brain activity. Analysis of signals emanating from the brain can be interpreted to infer cognitive and affective states and form the basis for direct interfaces connecting brains with the technologies used. The speakers discussed recent developments in this field along with near- and long-term applications; barriers and constraints; and ethics, security, and privacy issues.
Technologies for Interpreting Brain Activity
Several speakers shared examples of technologies that measure the brain’s electrical activity. Allan Levey (Emory University) offered a brief overview of how electroencephalography (EEG) provides information about brain activity by measuring electrical activity across the brain’s surface. EEG technology has been widely used in research and medical applications for decades, where it has proved especially useful for detecting seizures and states of consciousness. However, EEG typically requires the subject to wear a cap with multiple sensors covering the entire scalp, limiting its use outside of laboratory or medical settings, and only allows access to the top surfaces of the brain, limiting insights into activity in deeper regions of the brain.
Levey and Jonathan Berent (NextSense, Inc.), Dan Furman (Arctop, Inc.), and Maria Ruiz-Blondet (Neurable) presented on recent advances in EEG and related technologies that are poised to overcome some of these limitations and open new opportunities for brain wave analysis in consumer electronics, research, and medicine. The speakers highlighted examples of how brain signals can be obtained from headwear that is more practical than the traditional EEG cap, such as glasses, earwear, or hats (Arctop, Inc.); headphones (Neurable); and earbuds (NextSense, Inc.). Arctop, Inc., for example, is developing a software package, NeuosTM SDK, for a variety of head-mounted devices capable of interpreting the brain’s electrical signals to support brain-based interaction with consumer electronics.1 For instance, Furman described how the technology has been used in demonstrations to authenticate a user’s identity and to allow users to direct a digital interface to flip and sort cards without any physical or voice controls. Neurable’s headphone-based EEG system, Ruiz-Blondet explained, uses electrodes to continuously measure brain activity for insights on the wearer’s attention and focus.2 The system is being developed as an aid to help users stay on task amid distractions, part of the company’s broader goal of developing an everyday brain–computer interface for a variety of use cases.
Levey and Berent described how NextSense, Inc.’s EEG earbuds provide real-time analysis of brain activity in the temporal lobe, the brain’s center for memory, language, and personality. The in-ear sensors can record 50 hours of brain activity and store the data in the earbud or export it to the cloud via Bluetooth. In proof-of-concept demonstrations, Berent discussed that the technology has been shown to be capable of tracking a wearer’s attention (e.g., determining which of two simultaneous audio recordings a person is paying attention to) and feelings toward stimuli (e.g., detecting if a person likes or dislikes a photo). The device also can be used as a platform to influence brain activity. Berent explained how experiments have shown evidence that stimulation delivered via the earbuds can affect sleep patterns and even trigger memories and induce a hybrid state of consciousness that enables the wearer to undertake some conscious activities while sleeping.3
Todd Constable (Yale University) described another approach to gaining insights from the human brain that is based on the synchronous activity of anatomically
1 Haruvi, A., R. Kopito, N. Brande-Eilat, S. Kalev, E. Kay, and D. Furman. 2022. Measuring and modeling the effect of audio on human focus in everyday environments using brain-computer interface technology. Frontiers in Computational Neuroscience 15:760561.
2 Alcaide, R., N. Agarwal, J. Candassamy, S. Cavanagh, M. Lim, B. Meschede-Krasa, J. McIntyre, M. V. Ruiz-Blondet, B. Siebert, D. Stanley, D. Valeriani, and A. Yousefi. 2021. EEG-based focus estimation using Neurable’s Enten headphones and analytics platform. bioRxiv 2021.06.21.448991. https://doi.org/10.1101/2021.06.21.448991.
3 Konkoly, K. R., K. Appel, E. Chabani, A. Mangiaruga, J. Gott, R. Mallett, B. Caughran, S. Witkowski, N. W. Whitmore, C. Y. Mazurek, J. B. Berent, F. D. Weber, B. Türker, S. Leu-Semenescu, J-B. Maranci, G. Pipa, I. Arnulf, D. Oudiette, M. Dresler, and K. A. Paller. 2021. Real-time dialogue between experimenters and dreamers during REM sleep. Current Biology 31(7):1417–1427. https://doi.org/10.1016/j.cub.2021.01.026.
distinct regions of the brain. The approach, known as functional connectivity mapping, uses functional magnetic resonance imaging (fMRI) to decipher brain activity based on small changes in blood flow. Constable’s team developed a method to map a person’s “functional connectome”—akin to a fingerprint of the brain—and used it to produce maps of up to 70,000 connections. These maps can provide insights on a person’s fluid intelligence, working memory, attention, personality traits, and more.4,5
Applications of Brain Interfacing Technologies
Speakers discussed near- and long-term applications envisioned for brain interfacing technologies. One application that has already been well demonstrated is biometrics. Ruiz-Blondet and Furman described how brain signals can be used to discern the unique EEG signatures of individual people to verify a person’s identity, which could be useful for supporting authentication for restricted-access systems. As with any technology, Furman noted that there are tradeoffs between convenience and security. While brain-based biometrics may be less convenient than some other methods because it requires a device to be in contact with the head, this approach could be highly secure at a population level given the vast number of differences that can potentially be discerned between individuals’ “brainprints” as compared to fingerprints.
Another application area with both near- and long-term potential is medical monitoring and intervention. Berent said in-ear EEG could be used for monitoring seizures and guiding drug titration in people with epilepsy given the strong signals that the technology has been shown capable of acquiring. Constable said functional connectome approaches could hold significant potential for diagnosing cognitive or neurologic disorders and monitoring patients’ response to treatment by providing an objective, detailed view of a person’s brain activity and how it changes over time. He also noted that functional brain analysis holds promise as a tool for researching brain development, the effects of preterm birth, and the processes that influence intelligence.
Furman and Ruiz-Blondet discussed how brain wave analysis could support more intuitive, frictionless interaction with technology in the next decade. For example, Ruiz-Blondet said devices could interpret brain signals to discern when a person is focused on their task and when would be an optimal time for a notification or signal, providing a more seamless and less intrusive interaction that adapts to the user’s state of mind. Furman added that having feedback from the user’s brain can help make technology more empathetic and personable, enabling the technology to understand and respond appropriately to the user’s mental and physiological state.
Finally, speakers explored how brain analysis technology could be used as a basis for personalized education and learning. Constable said functional connectome approaches are already being pursued by international businesses as a potential tool for assessing and predicting cognitive skills in children and informing remedial interventions, though he said it will still be a while before the technique will be able to reliably predict cognitive performance. Furman, Ruiz-Blondet, Levey, and Berent described how wearable devices could be used to track focus and even assess how information is being encoded in the brain while a person is learning, enabling systems to provide feedback to individualize the educational experience and help the learner stay on task.
Ethics, Security, and Privacy Issues
Farahany noted that the information collected by brain scanning technology is sensitive by nature. In addition to concerns about protecting information that can reveal a person’s identity and health status, brain signal analysis raises special concerns related to mental privacy. By accessing cognitive and affective states, these technologies tap into what people consider the most sensitive and essential parts of their identity and what it means to be human, Farahany noted, raising significant ethical, security, and privacy issues.
4 Finn, E. S., X. Shen, D. Scheinost, M. D. Rosenberg, J. Huang, M. M. Chun, X. Papademetris, and R. T. Constable. 2015. Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity. Nature Neuroscience 18:1664–1671.
5 Shen, X., E. S. Finn, D. Scheinost, M. D. Rosenberg, M. M. Chun, X. Papademetris, and R. T. Constable. 2017. Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nature Protocols 12(3):506–518.
How brain signal data are collected, handled, and used has important implications for the security of these data and the privacy of the individuals whose data are being accessed. For example, are the data stored and computed on the device, or sent to and stored on the cloud? Is all of the raw data kept, or is it filtered and processed before storage? Is the use of the data limited to what is currently technologically feasible, or could it be used in different ways in the future? Furman said these remain open questions in the field. While his company takes a user privacy-centered approach, different companies may take different approaches. Furman and Berent said their companies are focusing more on edge computing solutions that largely keep the data local to the device, while Ruiz-Blondet said Neurable takes a cloud-based approach. Furman underscored the need for regulation and transparency on the part of companies collecting, analyzing, and storing this type of data.
Several speakers stressed that it is vital to ensure those who use the technology understand and consent to the way their data will be collected, handled, and used. Because obtaining functional connectome data requires an fMRI scan, this approach involves some level of consent on the part of the person whose brain is being assessed, Constable noted, although it is still important to protect individuals’ privacy in terms of how the data are used and shared. Raw functional connectome data can potentially be used to derive a wide range of insights beyond the original purpose for which the data are collected. For example, he said it is possible to derive an image of a person’s facial phenotype from brain data alone, meaning patient privacy could include manipulating or “defacing” the data to remove information about potentially recognizable physical features before sharing. For EEG data, Berent and Ruiz-Blondet noted that it can be valuable to offer the opportunity to “donate” their brain data to science or to help companies improve their algorithms, but that this should be done transparently and with attention to protecting individual privacy. Given that numerous companies are actively working to bring the next generation of cutting-edge brain analysis devices into clinical and consumer use in the near term, Berent said there is an urgent need for solutions to ensure people who contribute brain data can retain ownership and control over how that data are used. “I think that this is [going to be] here before we know it,” Berent said. “It’s coming, and so we have to be really thoughtful and make sure that we have safeguards around the data and that the users are in control of what they do with it.”
Brain analysis technologies have unique capabilities that raise unique issues. Even when they are not being used in the context of health assessment, for example, devices could pick up health-relevant information, Furman noted. What happens if a brain analysis device detects a health problem in a user? Who should be notified, and how? He advocated for prioritizing the rights of users over business models, with careful attention to how companies use the data. “It’s your own data, you should own it, you should have a place you can control it … and get the maximum value out of these really exciting and powerful and fun, invigorating technologies,” said Furman. “We need to be very deliberate and intentional about how we use this, how we potentially regulate it.”
The speakers identified future opportunities, barriers, and research priorities for emerging technologies that analyze brain signals. Constable and Ruiz-Blondet pointed to a need for larger and more diverse data sets to better understand how brain signals work (for EEG devices) and relate individual behavior to functional brain organization (for functional connectome applications). The speakers also said that additional research is needed to understand the full scope of the information that is accessible via the diverse spectrum of brain signals, identify which areas are most useful for applications, and transition to commercial deployment.
Ruiz-Blondet said headphone-based EEG can detect signals from as far back as the visual cortex, which allows those devices to capture information relevant to attention, muscle activation, and other activities that can be useful for voiceless interaction with technology. She explained that while there is still work to be done to determine which signals are most useful for what types of information, having a clear signal is key. She noted that advances in materials would be useful to ensure
sensors maintain optimal connection with the skin. She also mentioned that Neurable is exploring ways to give users feedback to ensure the headphones are placed properly for a good signal and not occluded by hair, for example.
Berent speculated that in-ear EEG would ultimately be able to access about 85% of the brain; his company is focusing on determining which of the accessible areas hold the greatest potential for medical and other applications. Levey added that some research suggests it is possible to use in-ear brain stimulation to block or enhance a memory, but Berent said the noisiness of EEG signals make it unlikely for this to be feasible in the near term. Other potential long-term medical applications for in-ear devices they discussed, which further research and development could enable, include addressing sleep problems; applications that involve stimulating the vagus nerve; and delivery of high-frequency gamma waves to guide neuroimmune interventions for the treatment of certain brain diseases. Berent cautioned, however, that any neuromodulation requires great care to avoid unintended effects.
In the context of EEG-based brain biometrics, participants discussed the potential limitation of whether early-stage results and current findings for authentication and identification applications are scalable when applied across an entire population. Some participants expressed optimism as current results show robust reliability for authentication; however, they noted that additional research for identification applications might be needed as the technology scales. Regarding scaling, Furman said that the components and supply chains to integrate “brain ID” capabilities into consumer electronics are already in place. He suggested that big tech companies will likely play the largest role in determining when these capabilities hit the market, though he speculated that it could be within the next year. “There’s really nothing holding back this brain ID from being rolled out to a commercial product,” he said. Beyond biometrics, Furman posited that the future of the field will rely on greater appreciation for the technological capabilities of brain analysis and a workforce that is equipped to think creatively about potential uses. “I think one of the big gaps in adoption is simply the awareness and understanding of what this technology can do,” he said. Ultimately, Arctop, Inc., predicts that brain analysis capabilities will be integrated into about 1 billion devices in the next 10 years.
EMERGING TECHNOLOGIES FOR DIGITAL OLFACTION AND SENSING OF VOLATILE ORGANIC COMPOUNDS
Chemicals, including VOCs, are constantly being emitted from humans and other organisms; materials and industrial activities; and environmental processes. These chemicals can reveal a great deal of information about the identity and states of organisms or processes present; exposure to chemicals can also impact human and environmental health. Catherine Cabrera (Massachusetts Institute of Technology Lincoln Laboratory) moderated a session on biochemical detection technologies. By identifying minute concentrations of particular chemicals and VOCs in gases, these technologies can be valuable tools to monitor the environment, detect pathogens and other organisms, and gain insight into biological processes. The speakers discussed emerging VOC sensing technologies and their potential advantages over existing tools in terms of sensitivity, cost, and energy requirements; examined the range of applications that might benefit from these technologies; and explored related ethical, security, and privacy issues.
Technologies for Detection of VOCs in Air
Three speakers shared technologies that use biological or bio-inspired components to analyze chemicals present in air. Osh Agabi (Koniku Inc.) discussed his company’s synthetic biology–based detector. The device uses neurons that are modified to express olfactory receptors, which are proteins that bind to specific small molecules in the air. These neurons create a living detector that processes, analyzes, and amplifies chemical signals, ultimately transmitting those signals to a digital interface via fluorescent tags. The detector is housed in a device weighing just 700 grams that communicates results via Bluetooth and Wi-Fi. With its low profile and minimal energy requirements, Agabi said the device is designed to be widely deployed across the globe to allow for real-time monitoring of all VOCs that touch human life.
Dmitry Rinberg (New York University Langone Health) shared his work developing a detector that operates within a living organism, the bio-electronic nose. Nature has optimized animal noses for capturing and processing the chemical composition of air with remarkable sensitivity. “[Olfactory] receptors are already tuned, evolutionarily tuned over millions of years, and there’s almost no odor that cannot be sensed by a biological nose,” Rinberg said. Rather than taking advantage of this capability through behavioral training (e.g., dogs trained to sniff out drugs or explosives), Rinberg posits that engineered hybrid biological–electronic olfactory systems can offer a more comprehensive and transferrable means of environmental sensing. His team has developed an electronic detector that can be implanted in a mouse nose to digitize and decode the process mice naturally use to bind odor molecules and process and amplify those chemical signals.6 This approach offers the capability to detect an enormous number of odors at extremely low concentrations with high stability and efficiency, without the need to train individual animals.
Although the human sense of smell is not as sensitive as that of animals such as dogs or mice, even human olfaction outperforms current chemical detection technologies. Jonathan Beauchamp (Fraunhofer Institute for Process Engineering and Packaging IVV) described his real-time mass spectrometry method that performs comparably to the human sense of smell. The traditional approach to identifying odor-active VOCs in air has been to combine gas chromatography with mass spectrometry. Beauchamp’s team uses real-time mass spectrometry with protonated water for a faster analytical approach. Because the main constituents of air are not ionized in the process but most VOCs are, the method is capable of simultaneously distinguishing a wide variety of compounds in air, with broad linear detection and a dynamic range from parts per trillion concentrations up to parts per million.7 In tests, the system achieved similar performance to human olfaction, though sensitivities for both the odorant analysis system and human olfaction vary from compound to compound. Beauchamp suggested the technology can serve as a complement to human smell and traditional gas chromatography/mass spectrometry to analyze fast processes involving multiple compounds simultaneously.
Technologies for Detection of Disease Biomarkers in Exhaled Breath
While many technologies for detecting VOCs in air can be applied to breath analysis, two speakers focused on emerging technologies designed specifically for detecting disease biomarkers in exhaled breath. Because disease processes have unique, identifiable metabolic signatures, detecting these metabolites in the breath offers a means for non-invasive health monitoring. Cristina Davis (University of California, Davis) focused primarily on technologies for detecting viral infections and Jane Hill (University of British Columbia) discussed detectors for bacterial and fungal infections.
Exhaled breath contains both gases and aerosols. Davis said that respiratory gases are about 99% water, with the other 1% comprising VOCs, non-volatile compounds, proteins, drugs, and other compounds. Hill added that the particles in exhalations can even include whole organisms such as bacteria. These components of exhalations reveal information about health. “We walk around every day exhaling health-relevant information,” said Davis. “Non-invasive monitoring is definitely possible and there are advances in sampling and measurement systems that can exploit these signatures for different end purposes.”
Davis described her work developing small sensors that can be deployed in a variety of ways, from drone-mounted systems for environmental monitoring to indoor and wearable sensors for indoor spaces or personal monitoring. She highlighted how her team and others have used such sensors to measure health markers across multiple kingdoms, including the detection of citrus greening disease in plants,8 markers for assessing dolphin health,9 and methods to detect
6 Shor, E., P. Herrero-Vidal, A. Dewan, I. Uguz, V. F. Curto, G. G. Malliaras, C. Savin, T. Bozza, and D. Rinberg. 2022. Sensitive and robust chemical detection using an olfactory brain-computer interface. Biosensors and Bioelectronics 195:113664.
7 Taylor, A. J., J. D. Beauchamp, and V. S. Langford. 2021. In Dynamic flavor: Capturing aroma using real-time mass spectrometry, edited by J. D. Beauchamp. Pp. 1–16. ACS Symposium Series. Washington, DC: American Chemical Society.
8 Aksenov, A. A., A. Pasamontes, D. J. Peirano, W. Zhao, A. M. Dandekar, O. Fiehn, R. Ehsani, and C. E. Davis. 2014. Detection of Huanlongbing disease using differential mobility spectrometry. Analytical Chemistry 86(5):2481–2488.
9 Pasamontes, A., A. A. Aksenov, M. Schivo, T. Rowles, C. R. Smith, L. H. Schwacke, R. S. Wells, L. Yeates, S. Venn-Watson, and C. E. Davis. 2017. Noninvasive respiratory metabolite analysis associated with clinical
Hill described how she and other researchers are applying similar approaches to assess bacterial and fungal infections in humans. In one example, researchers demonstrated success in detecting tuberculosis via breath analysis,12 an application that could help to overcome key barriers in tuberculosis diagnosis and treatment for children in low-income regions. In another example, researchers successfully detected aspergillosis fungal infections in patients with pneumonia.13 Hill said that the approach holds promise for improving diagnostic capabilities for a wide range of health conditions, including infections and cancers affecting the lungs and conditions affecting other body systems. Breath biomarker analysis has many strengths, including the potential for repeated, non-invasive sampling, and could form the basis for portable diagnostic and monitoring tools for both infectious and non-infectious disease management. However, Hill noted that a lack of standardization, a lack of integration with current clinical workflows, and a lack of shared data on breath signatures have limited progress in this space, raising the potential for unvalidated products and processes that may oversell their capabilities.
Applications of Digital Olfaction and VOC-Sensing Technologies
Technologies for detecting VOCs and other chemicals in air and exhaled breath are poised for practical applications in several areas. As Davis and Hill discussed, VOC sensors have already demonstrated the capability of detecting diseases that are important for agriculture and animal care and for complementing existing methods for diagnosing human diseases affecting large swaths of the population. Because they are non-invasive, often portable, and low cost, these technologies offer important advantages over diagnostic methods that rely on blood or tissue samples or bulky and expensive equipment, especially for use outside of hospital or laboratory settings or in low-resource countries.
As Agabi discussed, emerging detection technologies are also well suited for passive detection of industrial pollutants or environmental contaminants in a variety of settings. He noted that his company is working with other industry partners to advance industrial uses and to explore applications in security and weapons detection. Finally, Agabi, Davis, and other speakers pointed to the opportunity to use biological detection technologies to monitor the presence, movement, and health effects of chemicals in the environment for environmental health insights.
Ethics, Security, and Privacy Issues
The low profile and non-invasive nature of emerging VOC detectors raises the prospect that these sensors could be widely deployed and used without the knowledge or consent of the people whose exhalations and environments are being monitored. Debra Mathews (Johns Hopkins University), an expert in bioethics, and other speakers discussed ethical, security, and privacy issues posed by emerging biological detection technologies.
Mathews pointed to transparency as one key issue. Will people know when data are being collected from their exhalations or environments? A related issue is privacy. Will individuals have a meaningful opportunity to opt in or out of being monitored, or be able to control their data and how it is used? Cabrera noted that VOC analysis can potentially reveal information not only about a person’s health and disease status, which has clear privacy concerns, but also about a person’s activities and interactions with other people. Beauchamp added that there is evidence that VOCs can also offer insights into a person’s emotional state.
A third area to consider, Mathews said, is justice. How are the benefits and harms of data collection and use
disease in cetaceans: A Deepwater Horizon oil spill study. Environmental Science and Technology 51(10):5737–5746.
10 McCartney, M. M., A. L. Linderholm, M. S. Yamaguchi, A. K. Falcon, R. W. Harper, G. R. Thompson, S. E. Ebeler, N. J. Kenyon, C. E. Davis, and M. Schivo. 2021. Predicting influenza and rhinovirus infections in airway cells utilizing volatile emissions. Journal of Infectious Diseases doi: 10.1093/infdis/jiab205.
11 Hu, S., M. M. McCartney, J. Arredondo, S. Sankaran-Walters, E. Borras, R. W. Harper, M. Schivo, C. E. Davis, N. J. Kenyon, and S. Dandekar. 2022. Inactivation of SARS-CoV-2 in clinical exhaled breath condensate samples for metabolomics analysis. Journal of Breath Research 16(1):017102.
12 Bobak, C. A., L. Kang, L. Workman, L. Bateman, M. S. Khan, M. Prins, L. May, F. A. Franchina, C. Baard, M. P. Nicol, H. J. Zar, and J. E. Hill. 2021. Breath can discriminate tuberculosis from other lower respiratory illness in children. Scientific Reports 11(1):2704.
13 Koo, S., H. R. Thomas, S. D. Daniels, R. C. Lynch, S. M. Fortier, M. M. Shea, P. Rearden, J. C. Comolli, L. R. Baden, and F. M. Marty. 2014. A breath fungal secondary metabolite signature to diagnose invasive aspergillosis. Clinical Infectious Diseases 59(12):1733–1740.
distributed across populations? Finally, she said it is important to attend to questions around data governance and security. Who is collecting the data and what are their responsibilities? Who stores the data and how well protected are the data? How are the data used and shared by researchers and by the people from whom the data were collected? These issues, which pose challenges throughout many areas of technology, will be important to address as the field moves forward, Mathews said. She added that it may also be valuable to examine how areas of convergence with related fields such as genetics and synthetic biology influence these ethical and social considerations.
Some biological detection technologies are passing the point of proof-of-concept and maturing toward commercial and health applications, while others are only beginning to emerge and hint at new opportunities in research and engineering. The speakers discussed the current state of the science; key questions and barriers; and future directions for refining the technologies, facilitating their adoption, and exploring new opportunities.
After several decades of development, Hill said that the success of recent experiments in clinical and biomedical applications has given researchers more perspective on the potential of VOC-sensing technology and a place to focus collaborative efforts spanning medicine, bioinformatics, basic biology, and other fields. “I think the future is really bright and exciting,” she said. “This field is at an inflection point that is exceptionally exciting,” Davis agreed, adding that “there is a lot of actionable potential here.” To move forward, Davis said that there is a need to conduct much larger studies in more diverse populations and to establish a database of validated biomarkers to inform which VOCs are useful to measure, something she said could be accomplished through national initiatives and international consortia. Davis also added that there is the potential to develop chip-based devices and explore more applications in environmental exposure monitoring.
To facilitate broader adoption of biological detection technologies, Agabi and Rinberg noted that scaling is perhaps one of the most difficult challenges to address. Agabi said his company devised methods to fine-tune its detector’s sensitivity but the engineered cells themselves cannot reliably live longer than about 1 year. This presents problems for deploying sensors at scale and maintaining them for continuous operation. Rinberg said that scaling sensors to the vast number of potential odorants or chemicals that exist—something nature has done over many millions of years—poses a significant challenge for engineered devices. In the biomedical sphere, Davis said high-throughput technologies are making headway in allowing for screening of large data sets, while Hill noted that knowledge about a specific disease or health condition can help to narrow the field of VOCs to search for, thus helping to address the scaling issue.
Standardization also poses a significant challenge. For instance, it is important to understand the concentrations of VOCs that are relevant, how to translate sensor data into meaningful information, and the interoperability of data from different systems or technologies, Agabi said. Beauchamp noted that the research community is actively working on addressing these and other standardization issues.
Rinberg speculated that biological detection is “on the brink of a new kind of era … a completely unexplored field,” the applications of which may well go beyond current imaginings. In tapping into nature’s long-established method for transmitting information—the emission and detection of chemicals—he said that humans have much to learn from nature and may gain access to capabilities that they can only begin to envision now.
Throughout the workshop’s presentations and discussions, participants examined a variety of technologies in the field of biological detection, summarized in Table 1. Technologies that detect neural signatures and detect chemical markers in surroundings likely hold great potential for applications aimed at
improving human health, national and personal security, and much more. Some of these technologies are already on the brink of commercial deployment, where they may soon find their way into clinics and consumer electronics. Others are still decades away from practical use but could unlock new ways of understanding bodies and the world. Across all of these use cases and development trajectories, many participants stressed that it will be important to consider how structures, norms, and processes can help to support ethical practices—including those that enhance transparency, privacy, and security—in the development and adoption of biological detection technologies.
Overview of Example Technologies Discussed at the Workshop
|EXAMPLE TECHNOLOGY||POTENTIAL APPLICATIONS||ADVANTAGES||LIMITATIONS||MATURITY AND ECOSYSTEM||ETHICS, SECURITY, AND PRIVACY ISSUES|
|NEURAL SIGNATURE DETECTION|
|EEG technologies for brain analysis and interaction (e.g., Arctop, Inc., Neurable, NextSense, Inc.)||Biometrics; intuitive consumer electronics; personalized learning; identity verification; neurological health monitoring and neuromodulation||Brain is more unique for biometrics; hands-free, voice-free interaction with technology increases convenience; real-time feedback can improve learning retention; potential health benefits||Cannot reach all brain regions; requires physical device touching the head; additional validation of certain applications across a population as the technology scales||Some technologies could be available in consumer electronics within months/years; some medical applications entering U.S. Food and Drug Administration review||Concerns about mental privacy; personally identifiable information; health-relevant information; data security and data sharing; transparency and consent|
|Functional connectome mapping||Cognitive and psychiatric diagnostics and monitoring; personalized learning; brain development research||Deep insights into brain organization and development; insights over the course of the lifetime; ability to monitor changes over time||Requires fMRI scan; offers snapshot in time unless scans are repeated||Need for more research to relate individual behavior to functional brain organization||Concerns about mental privacy; personally identifiable information; health-relevant information; data security and data sharing|
|Synthetic biology–based VOC detector||Industrial and environmental monitoring; security and weapons detection; pathogen detection||Real-time results; small size; low power/maintenance requirements; high sensitivity||Scaling; detector cells cannot reliably survive longer than 1 year||Poised for commercialization in partnership with user communities in industry and security||Concerns about transparency and consent; data governance and sharing|
|Bio-electronic nose||Environmental monitoring||Large range of detectable compounds; high sensitivity; transferrable to other animals without training||Scaling; requires animals||Early phase of research and development||Concerns about transparency and consent; data governance and sharing|
|Real-time mass spectrometry||Environmental monitoring||Large range of detectable compounds; high sensitivity||Sensitivity varies from compound to compound||Early phase of research and development||Concerns about transparency and consent; data governance and sharing|
|Breath analysis technologies||Pathogen detection and diagnostics; environmental health research||Non-invasive; potential to deploy in low-resource countries||Need for further clinical validation; lack of clinical workflow integration; lack of data on which VOCs are useful as biomarkers||Inflection point from proof-of-concept to practical application||Concerns about transparency and consent; data governance and sharing|
NOTE: This table lists examples of technologies shared by workshop participants. This table does not include all ideas mentioned by participants, and should not be interpreted as consensus conclusions or recommendations of the National Academies.
DISCLAIMER: This Proceedings of a Workshop—in Brief was prepared by ANNE JOHNSON with contributions from ANDREW BREMER and NANCY CONNELL as a factual summary of what occurred at the workshop. The statements are those of the individual workshop participants and do not necessarily represent the views of all participants, the workshop planning committee, the Standing Committee on Biotechnology Capabilities and National Security Needs, or the National Academies of Sciences, Engineering, and Medicine.
REVIEWERS: To ensure that this Proceedings of a Workshop—in Brief meets institutional standards for quality and objectivity, it was reviewed by JONATHAN BEAUCHAMP (Fraunhofer Institute for Process Engineering and Packaging IVV), NITA FARAHANY (Duke University), and DAVID WALT (Harvard Medical School). The review comments and draft manuscript remain confidential to protect the integrity of the process.
Workshop planning committee members: CATHERINE CABRERA (Chair), Massachusetts Institute of Technology Lincoln Laboratory; ROCCO CASAGRANDE, Gryphon Scientific; ELLIOT CHAIKOF, Harvard Medical School and Beth Israel Deaconess Medical Center; JONATHAN DORDICK, Rensselaer Polytechnic Institute; Nita Farahany, Duke University; CHARLES GILBERT, The Rockefeller University.
The Standing Committee on Biotechnology Capabilities and National Security Needs, under which this workshop was organized, is supported by the U.S. government.
Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2022. Cutting-Edge Scientific Capabilities for Biological Detection: Proceedings of a Workshop—in Brief. Washington, DC: The National Academies Press. https://doi.org/10.17226/26553.
Division on Earth and Life Studies
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