Computational Modeling in Medicine

In the past few decades, information technology has revolutionized the medical industry. The accuracy with which biological systems and interactions can be simulated and data can be gathered have improved exponentially. Computational modeling has provided ever-more sophisticated data for the field of medical research. This article will discuss this subject.

computational modelingImage Credit: ShustrikS/

What is computational modeling?

Computational modeling is used to simulate and study complex systems using computer science, physics, and mathematics. Numerous variables are programmed into the computational model to characterize the system which is being studied. By adjusting these variables alone or in various combinations, the outcome can be observed, providing valuable data for researchers.

This allows scientists can conduct thousands of simulated experiments. Data collected from these simulated experiments can be then used to identify which laboratory experiments are likely to solve a problem. Computational modeling is used in many different scientific disciplines including drug discovery, weather forecasting, flight simulation, and medical care research.

Today, computational models can study biological systems at multiple levels, in what is known as multiscale modeling (MSM). These models include cell to cell interactions, molecular processes, and how tissues and organs are affected.

Applying computational modeling to medical science

Medical science is a constantly evolving discipline. Research in the field requires complex testing and the collection of accurate data to provide scientists with the information and tools necessary to provide new solutions and improve health outcomes. The increase in data sources including wearable sensors and digital medical devices has helped to drive the field. Some areas of research to which computational modeling is applied in medicine include:

  • Tracking infectious diseases – By using computational modeling, scientists and organizations can track infectious diseases in populations, leading to more effective interventions. Predicting the way that outbreaks move through populations and identifying and modifying interventions leads to a more effective response that saves lives during pandemics.
  • Clinical decision support – Computational modeling provides guidance for doctors making decisions on disease treatment and informed and consistent care in hospital settings. This is based on each patient’s unique and detailed characteristics.
  • Predicting the adverse side effects of drugs - Using computational models, scientists can predict the potential for a drug to have adverse side effects. Accurate data provided by modeling can thereby help to develop safe and effective medications.
  • Medical device design and development – Computational modeling has been used in the support of medical device design and development. This has helped to inform the safe design of a range of medical devices in use today.

Medicine, like any other discipline, requires data. Sophisticated data-driven models are now possible thanks to a growing array of data sources including records, internet-connected sensors, and the results of previous trials. When these data points are combined with analysis platforms via computing, analysis of outcomes and risk assessments can be provided to medical providers and patients. This improves decision-making processes.

Specific uses of computational modeling in medicine

Computational modeling is applied in numerous studies these days. Some specific examples of its use are:

Gathering targeted information on viral evolution

Viruses mutate during pandemics. Mutations can be completely harmless, but others make the virus more transmissible or can increase resistance to vaccines and therapeutic drugs. Data on currently sequenced pathogens can be used in computational models to identify evolving variants.

This is absolutely crucial for informing public health responses and ensuring that current vaccines work on the new variants or if they have to be modified.

Using computational modeling to aid the design of new medical technologies

A study published in Nature in March 2020 demonstrated how computational modeling can be used to aid the development of new medical technologies. A team led by Alvaro Mata demonstrated how a computational modeling approach can be used in the fields of tissue engineering and regenerative medicine. Specifically, it was demonstrated that it could help to aid the development of new therapies and materials.

Graphene oxide is a useful material that can be used to print 3D tissue-like vasculature structures. However, the mechanism by which graphene oxide exploits the flexible region of a protein is not completely understood. By using a computational modeling approach, the team aimed to understand this better.

Simulations that were run in computational models were used to understand molecular dynamics and elucidate the mechanisms by which molecules assemble together to form various tissues. Thus, by using these simulations, assemblies at the molecular level could be translated into fabrication platforms that are capable of engineering functional structures.

Using models to create “digital twins”

Personalized medicine is a recently developed field of medical science. Providing therapies tailored to each patient’s needs is the aim of this field, and it is being aided significantly by the development of increasingly accurate computational models and more sophisticated data gathering.

One recent application of computational modeling in this area has been in the creation of “twin hearts”. These are digital models of a heart which can be used alongside medical images of the patient’s real heart. These digital twins can then be used to provide vital information on cardiac properties which are currently unavailable to doctors. This can then be used to develop better interventions and therapies.

Computational modeling used in surgery

CRIMSON is open-source software that has been in use since 2015. It was developed by a University of Michigan team led by Alberto Figueroa. The system uses computerized simulations of the patient’s own blood flow obtained with data gathered from MRI scans and hemodynamic variables.

The data is then used to build a highly accurate model of the patient’s own circulatory system which can be used by surgeons to plan surgeries. CRIMSON has been used already in several complex operations including Fontan procedures, which involve rewiring pulmonary circulation in patients born with only one functioning ventricle.

In conclusion

Computational Modeling is providing researchers with a wealth of data that can be used to inform clinical trials, public health decisions and the development of new technologies. This technology is pushing the boundaries of medical science into the new century.

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Further Reading

Last Updated: May 12, 2021

Reginald Davey

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Reginald Davey

Reg Davey is a freelance copywriter and editor based in Nottingham in the United Kingdom. Writing for AZoNetwork represents the coming together of various interests and fields he has been interested and involved in over the years, including Microbiology, Biomedical Sciences, and Environmental Science.


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