September 1, 2017 (Vol. 37, No. 15)

Gail Dutton

Electron Microscopy Specialist Designs Systems for Faster and Better-Informed Decisions in Drug Development and Bioprocessing

Vironova, a company specializing in electron-microscopy imaging, is introducing a new way to look at virus research and drug development. The company is combining purpose-built virus analysis and quantification software with a smaller, more efficient electron microscope and camera. By integrating these elements, the company has developed a digitized desktop instrument designed specifically for decision support for drug development and quality control in the viral vector market segment.

“Drug delivery and gene therapy is our current focus,” Vironova Founder and CEO Mohammed Homman says.

A Solution Born from Need

The idea for the technology evolved from Homman’s frustration with the traditional electron microscopes he had used when he conducted virology research at the Karolinska Institute. “I spent years looking at viruses through transmission electronic microscopes, manually quantifying virus particles, analyzing their morphology.”

Homman hoped that applications of newly developed digital technology would streamline morphological analysis, but he was disappointed. “When the digital era arrived, the giant electron microscope manufacturers didn’t change,” he recalls. “We needed new tools to make the process more accurate and objective.”

At the time, Homman was developing a drug that targeted herpes viruses such as cytomegalovirus. “I needed an accurate, efficient way to determine whether a substance affected the morphology of the particles, [a way to facilitate the assessment of] quantification, purity, integrity, and other factors. Although viruses are smaller than bacteria, you don’t have to go to subatomic levels to see them. All I needed was a system that could see particles at the nanoscale with accuracy,” Homman points out. Using a traditional electron microscope, therefore, was overkill. It was large, expensive, and more capable than the task required.

Designed for Virology

The system Vironova created, the MiniTEM™, represents a more elegant approach, according to Homman. “I patented the solutions and suddenly realized that the system could be commercialized.” Introduced in 2014, the MiniTEM is a table-top, low-voltage transmission electron microscope system that integrates imaging and analysis.

“The system’s magic is in the software and its integration to the microscope,” Homman says. “We integrated the microscope, camera, and analysis software to make real-time data analysis possible, shortening image-analysis workflows from one week to half a day.” That integration makes Vironova unique, notes Homman.

The virus-analysis software (VAS) lets researchers automatically screen samples, instantly assessing particle-size distribution, classifying particles, measuring concentrations, finding debris, and determining particle integrity, as well as checking whether viral vectors contain the expected genetic payloads. “The system measures particles in the nanometer range with high accuracy,” he says.

Automating virus particle analysis saves researchers hours, but the ability to extract information from the images is the software’s greatest benefit, Homman says. “A computer removes subjectivity, while providing greater accuracy and traceability and saving the data.” Consequently, the software meets regulatory requirements for traceability. That increased functionality extends its use from research through to industrial settings.

caption Vironova’s MiniTEM instrument, a transmission electron microscope designed specifically for virology, integrates nanoscale imaging with analysis software so that researchers can automatically screen samples and instantly measure particle sizes, classify particles, measure concentrations, detect and quantify debris, and assess particle integrity.


“Vironova’s solutions help inform and accelerate drug development, quality control, and regulatory approval processes, while addressing the key efficacy, safety, productivity, and commercial challenges facing the biopharma industry,” Homman tells GEN.

Vironova’s internal research comparing the MiniTEM with dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) indicates that MiniTEM provides unambiguous data for particles less than 50 nm. In contrast, NTA detected no particles, and DLS with Zetasizer Nano analysis was unable to differentiate between the adeno-associated vectors and proteasome contamination.

In July, Vironova joined a research collaboration at FoRmulaEx, an industrial research center. Vironova and its FoRmulaEx partners, which included AstraZeneca, Camurus, and research groups headed by Chalmers University, anticipated that Vironova’s analytic software would be used to ease key bottlenecks in the delivery of oligonucleotide drugs.

Homman says scientists can use the MiniTEM to process images and generate data for decision support. Although microscopic images have long been used to generate data, the underlying procedures often require that researchers exercise a fair amount of skill and judgment. Automating and integrating analysis software with the camera and microscope provides data that is more accurate, objective, and reproducible. Such data may constitute stronger evidence for scale-up and commercialization, as well as for regulatory submissions.

AI Is the Future

Going forward, Vironova is developing its patent portfolio around artificial intelligence (AI) and deep learning to further enhance data analysis. “It takes 10 years and $10 billion to bring a drug to market today,” Homman says. “If we can shorten time to market, that’s good for everybody. That’s where AI and deep learning come into play.”

Deep learning is a specialty within machine learning that builds complex neural networks similar to those of the brain. As these brain-like networks gain experience, they refine their computational and analytical capabilities. They learn. Eventually, they may be valuable in identifying particles based upon their morphology or surface patterns.

Researchers already use image analysis and pattern recognition to inform virus diagnostics. But these procedures could become more organized, more informative, if they incorporated AI and deep learning. “Now we have such variables as particle size and distribution, whether they are empty or full, and the lamellarity of liposomes, which all are important elements in determining the efficacy of drugs,” Homman notes. Deep learning can screen particles for particular characteristics among any or all or those elements to identify the optimal candidates for further development.

It’s too early, says Homman, for him to talk publicly about the tools he is planning to launch, but he confirms that in the near-term, all these tools will be focus on virus particles. “We want to help in a broad sense with quality control for any biological pharmaceutical, but with a focus on vaccines and viral vectors for drug delivery or gene therapy.”

Vironova is expanding rapidly. Its chemists and virologists work side by side with mathematicians, software developers, and image analysts for what Homman calls a “unique combining of technology and medicine.”

The company has doubled its staff in the past year and is slated to have a presence in the United States in the near future. “We’re focusing first on the Boston area,” Homman says.

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