CONICET scientists are making progress in developing a digital diagnostic device for hepatitis E

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The wearable technology incorporates artificial intelligence tools. The project involves the participation of specialists from Gisens Biotech, a bioelectronics and nanotechnology startup based in La Plata, Argentina, with a branch in the United States.

The device contains a graphene sensor chip and was developed within the framework of the ViroSensar Network, formed to seek strategies for addressing neglected infectious diseases.

Within the framework of the ViroSensAr Network, a platform for developing rapid and portable biosensors for the detection of viral infections established just over two years ago, the development of a digital diagnostic kit for hepatitis E was published in the scientific journal ACS Sensors in December 2025. Hepatitis E is an emerging disease in Argentina, primarily transmitted through the consumption of contaminated water, and is often underdiagnosed. “Since the network’s purpose is to detect neglected diseases of public health importance in our country, the collaborative work of the involved parties led to an interest in hepatitis E,” explained Omar Azzaroni, a CONICET researcher at the Institute of Theoretical and Applied Physicochemical Research (INIFTA, CONICET-UNLP*) and coordinator of ViroSensAr.

In addition to that node, the platform includes two other institutions: the Institute of Physical Chemistry of Materials, Environment and Energy (INQUIMAE, CONICET-UBA) and the Higher Institute of Biological Research (INSIBIO, CONICET-UNT). The project is further enhanced by the participation of a startup company, Gisens Biotech, a recently established and rapidly growing company specializing in bioelectronics and nanotechnology, based in La Plata and with a branch in the United States.

Esteban Piccinini (left) and Omar Azzaroni (right) are representatives of the ViroSensar Network at INIFTA

Previously
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The published findings cannot be understood without mentioning a previous study by the same groups, published in October 2025 in another leading scientific journal, Biosensors and Bioelectronics, which reported the incorporation of nanoantibodies into graphene integrated circuits or chips. These are a type of antibody derived from camelids (camels, dromedaries, llamas, alpacas, guanacos, and vicuñas) that are ten times smaller than the corresponding proteins in other mammals, allowing them to penetrate tissues more effectively and thus serving as a therapeutic tool. In this case, they were developed at INSIBIO and are specific to hepatitis E, as they precisely recognize an antigen called ORF2, the main marker of this virus against which the immune system reacts.

“For the first time, we were able to integrate these nanoantibodies onto the surface of sensor chips that, instead of being made of silicon like those used in modern electronics, for example in computers or smartphones, are made of graphene, a material derived from graphite that is one hundred times harder than steel and a better electrical conductor than copper,” explained Esteban Piccinini, a CONICET researcher at INIFTA and one of the authors of both studies. “This allows for rapid, digital, and portable detection”, he added** The next step, described in the latest publication, “was the incorporation of machine learning into the device to optimize the accuracy of the diagnostic tests,” continued the expert, who has a distinguished career in the field and in 2023 received the prestigious MIT Innovators Under 35 Award, granted by the Massachusetts Institute of Technology’s Technology Magazine to young innovators under 35.

Machine learning (ML) belongs to the field of computer science and is a branch of Artificial Intelligence (AI) that seeks to develop techniques for computers to “learn” to perform tasks autonomously and improve based on experience. In this instance, the company Gisens Biotech was responsible for generating an algorithm to enhance the function of nanoantibodies and made it available to scientific teams, who incorporated it into the device. “The original test went from a sensitivity of 89 percent and a specificity of 69 percent to almost 100 percent in both values once it was complemented with this technique,” Piccinini said, and emphasized that “because it is a digital language, this improvement also has a virtually negligible cost compared to what it would cost to make modifications to the hardware, in this case, a chip.”

Underdiagnosis and animal-to-human transmission
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According to the World Health Organization (WHO), nearly 20 million cases of acute hepatitis E, the most common form of the disease, have been recorded in recent years. Acute hepatitis E usually resolves on its own within two to six weeks, although it can progress to a chronic form or fulminant hepatitis with high mortality. While it exists worldwide, its prevalence is higher in some areas of Africa and Asia, as well as Central America. Argentina is considered a country with low endemicity, but cases have been reported in the central and northern regions over the last decade. The Argentine Society of Infectious Diseases (SADI) estimates that the infection is underdiagnosed and that most cases go undetected. However, the circulation of zoonotic genetic variants of the virus—those transmitted from animals to humans—has been found here. This type of transmission has been reported through the consumption of undercooked pork and also through contact with rodents.

The diagnosis is not standardized and requires highly specific analytical tests that look for precise antibodies against this virus, since the symptoms cannot distinguish it from other types of hepatitis or infections that also cause jaundice, the yellowing of the skin characteristic of liver diseases. At this point, the potential development of the digital test would also bring advantages to the procedure itself in terms of sample collection, moving from requiring venous blood to capillary blood, that is, blood obtained from small capillaries and requiring only a tiny prick in the fingertip, much less invasive than the traditional extraction from the inside of the elbow. “This simplification will allow diagnoses to be made at small testing sites or rural locations, also dispensing with highly specialized personnel, who are not always available outside of large health centers,” Piccinini added.

And… there is more…
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Finally, another improvement on the new device would offer over current tests relates to the results obtained: it not only differentiates between negative and positive results, but also provides a quantitative value within the latter group—valuable information that conventional tests do not offer. Thus, positive cases will also know the exact concentration of antigen in their blood, a crucial factor in the case of infections that, like hepatitis E, can become chronic and last for six months or more. “These patients are treated with medication for extended periods, and knowing their viral load levels is essential to confirm whether the treatment is effective and whether it is necessary to change the drugs,” explained the researcher.

Citation
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The study Machine Learning-Augmented Graphene Transistor Biosensing: Quantitative Platform Validation and Immunotesting of Hepatitis E. was published in ACS Sensors. Authors: Sofía Albesa, Ezequiel Giménez, José M. Piccinini, María G. Vizoso-Pinto, Waldemar A. Marmisollé, Esteban Piccinini & Omar Azzaroni

Sens. 2026 Jan 23;11(1):728-738. doi: 1021/acssensors.5c04006

The study Digital detection of hepatitis E antigen tailored for multiple genotypes using graphene transistors functionalized with nanobodies: End-to-end test development and optimization was published in the Biosensors and Bioelectronics journal, part of the ScienceDirect group. Authors: Ezequiel Giménez, Lorena P. Arce, Esteban Piccinini, Julia Matías Brancher, José M. Piccinini, Waldemar A. Marmisollé, Lorena I. Ibáñez, María G. Vizoso-Pinto & Omar Azzaroni.
The article Científicos del CONICET avanzan con el desarrollo de un dispositivo de diagnóstico digital para la hepatitis E, signed by Mercedes Benialgo was published in CONICET’s news section