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Biotech & Pharma

Ernst & Young analysts posed a vital question a few years ago that remains unanswered: "How can biotech innovation be sustained during a time of serious resource constraints?" Essentially, the R&D paradigm in the industry has remained unchanged.

With modeFRONTIER, scientists and researchers are able to reduce experimental time, to streamline data assessment and to automate processes, by drawing on well-established engineering optimization and numerical modeling technologies.

Applications of modeFRONTIER
in the biotech & pharma industries

modeFRONTIER applications in biotech & biomedical sectors cover a wide range of topics, including:

  • bone implants
  • enzyme engineering
  • systems biology
  • injury biomechanics
  • measurement devices
  • DNA sequencing
  • tear substitute optimization
  • human tissue modeling
  • dental implants

Few examples:

Advanced simulation techniques based on molecular dynamics and molecular docking are routinely used in the design of complex molecular system. modeFRONTIER can streamline the drug design process optimizing the scoring functions used in molecular docking, optimizing multiple contrasting objectives in QSAR analysis and automating the overall multi-step process.


De novo assembly projects often use mixed sequencing technologies, with the combined objective of maximizing the assembly quality and minimizing the sequencing cost. With its optimization and post-processing capabilities, modeFRONTIER can rationalize the DNA assembly process and obtain high-quality results in the sequencing analysis, while reducing cost and process duration.


Computational systems biology applies efficient algorithms and visualization tools to complex biological systems. modeFRONTIER helps computational biologists to create accurate models of system’s response to external and internal factors, such as modeling of insulin secretion in order to find weaknesses in its signaling pathways.


The properties of an enzyme can be modified by directly manipulating its structure. From a computational perspective, the “in silico mutagenesis” consists in the selective substitution of predetermined positions in the amino acid chain. The scientist can use modeFRONTIER to formalize and automate the computational analysis, and to optimize the choice of the mutant with respect to the enzyme target properties.


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