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How computational modeling and simulation could benefit care delivery

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It currently takes more than $100 million and eight years to bring a new high-risk medical device to market. These numbers are growing every year, but what if those numbers could be cut in half? What if medical devices could be designed and safely tested in the virtual world before ever being used on a real person?

Researchers, pharmaceutical manufacturers, scientists, doctors and other industry leaders are turning to virtual worlds and computational modeling and simulation (CM&S) software to answer this exact question.

The Food and Drug Administration (FDA) has even dedicated research to uncovering the possibilities that simulation brings to the healthcare industry by partnering with Dassault Systèmes for the Living Heart Project. In July 2017, FDA Commissioner Scott Gottlieb, MD, publicly outlined the FDA’s plan to help consumers capitalize on advances in science, stating, “Modeling and simulation plays a critical role in organizing diverse data sets and exploring alternate study designs. This enables safe and effective new therapeutics to advance more efficiently through the different stages of clinical trials.” In fact, the FDA believes as much as 50 percent of future evidence will come from CM&S.

Simulation software has long been used to model and design airplanes and automobiles, but now it’s starting to be used to also develop highly accurate personalized human organs, medical devices and biologics. Today, simulation technologies can detect how these models will respond under stress or in any lifelike situation. When finally brought to market, the device will result in the highest levels of quality and safety for both patients and providers.

Medical device accuracy
As health innovation continues, the world of engineering will transform to focus on human experience-based design. Through medical and scientific progress, catalyzed by digitalization, engineering’s ability to address previously unmet medical needs is being accelerated.

When building a new medical device, a prototype will go through a variety of iterations. CM&S can significantly speed up this process and reduce costs by enabling manufacturers to quickly discard dysfunctional designs while optimizing the performance of the functional ones, before ever having to build a physical prototype.

The FDA’s Center for Devices and Radiological Health (CDRH) is responsible for ensuring the safety, effectiveness, performance and quality of medical devices and radiation-emitting products used to treat, prevent and diagnose disease. In 2016, the CDRH released new Regulatory Science Priorities to include the development of computational modeling technologies to support regulatory decision making.

Over the past few years, the FDA has seen a dramatic increase in the use of CM&S in:

  • Computer models of patients used to support approval of new medical devices
  • Population modeling methods to understand differences or similarities between a wide range of data sets that will improve medical device designs for more people
  • Virtual clinical trials to create computational approaches to design virtual patients or simulate a clinical study itself

CM&S is becoming a more efficient and effective method for evaluating medical devices and potentially even supporting regulatory submissions. There is a greater opportunity to bring devices to market more quickly and cost effectively while ensuring the device will perform reliably; because of this shifting competitive landscape, it is imperative for life sciences companies to embrace and incorporate CM&S into their product development lifecycle.

The Insigneo Institute for in silico Medicine at the University of Sheffield, UK, is transforming how engineering is being used in medicine. By implementing simulation technologies into their clinical research, their work has demonstrated that it’s not only possible to model the human spine, but we can begin to use simulation to predict the ideal procedures to return function to normal. The extent of how simulation is being applied to science continues to evolve and it’s an incredibly exciting time to see this taking place not only at the professional level, but within academia as well.

Pharmaceutical acceleration
As researchers work toward finding new medicines for disease prevention, the global shift to precision medicine continues to be facilitated by advances in translational sciences, genomics and biotechnology-based medicines. Simulation technologies are enabling researchers to accelerate this progress by enabling them to be more predictive and adaptive.

As digitization across the pharmaceutical industry grows, ensuring a digital thread exists between once siloed departments is key to success in bringing new therapeutics to market sooner and more reliably. By providing traceability of source data, these platforms will give pharma manufacturers more visibility into resources to identify, monitor and operationalize critical production processes. This will enable data-driven decision making in a validated environment.

As they currently stand, Phase III clinical trials typically see half of drug candidates fail. To get to this point, a large pool of patient tests are needed for reliability. However, if mechanical models could be used instead, there could be reductions in costs and time-to-market, and medicine could become vastly more accessible worldwide.

Researchers at Stanford University working with UberCloud recently used the Living Heart as a platform for a model that would enable pharmaceutical companies to test drugs for the risk of inducing cardiac arrhythmias, the leading negative side effect preventing FDA approval.

Using virtual human modeling to engineer safer and more effective devices and medicine is just the tip of the iceberg. Custom medical services for individuals will become the future. Medical devices and pharma will become more personalized, patients will become better educated on their options, which will influence relationships with doctors and ultimately treatment options.

In time, the industry will no longer be bottlenecked by trial-and-error testing but instead be fueled by a transformation in engineering. The patient experience will remain at the forefront as simulation will allow us to not only model for standard medical procedures but also predict a better future for us.

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