How simulation can help fight a pandemic like Covid-19

How simulation can help fight a pandemic like Covid-19. It took us unprepared. We missed how much probable was the threat of a contagious and potentially deadly virus as the #covid19 in a hyper-connected world. And we have neither a treatment ready for it nor a common reaction protocol to fight it in an effective way. We are learning while racing against time, while people are dying, and each country is taking its own approach despite the evidence that we are all interconnected. Singapore, primed by the experience with the 2020 SARS (that is a COVID), reacted quickly and drastically. Many others underestimated the risk until the virus started spreading among their population, becoming a global problem. Governments are now working on getting us through this unprecedented human and economic crisis, looking for all the possible tools and ideas that can at least slow down the virus diffusion.

#simulation can truly be the secret weapon to help fight a pandemic. When you have a fast-spreading, highly contagious disease, you need to take a swift reaction to contain and slow the threat down.

Simulation lets you see the invisible

We cannot see viruses, how they spread in the air, infect other people, contaminate surfaces and the buildings we live in. What is happening, for instance, in a closed environment as a cinema or a mall? Why did we have so many cases on a cruise ship? Are we safe on a bus? In all these places we have forced air ventilation systems, which move viruses with the air. #simulation  can predict and let you see how air particles are moving into a closed area. It’s now possible to assess the level of danger of each of these places, to design and tune the air conditioning system in a way that the infection can be limited.

Also, #simulation can see something before it happens. One of the problems we are facing in these days is how to sanitize rooms, offices, hospitals. According to a preprint published by the National Institutes of Health, Princeton, and the University of California, the COVID virus can survive for days on surfaces. Not only in the surgery room of a hospital but also on the handrails of buses and trains, on the doors and shelves of malls, on the desks of offices and schools. One interesting countermeasure could be to sanitize these areas at night, when they are empty. It can be done automatically through spray devices that must be placed in the right spots to be sure they are effective. It’s also possible to use the forced ventilation/air conditioning systems to multiply their effectiveness in a building. How can we design these spraying systems to be sure they will sanitize every corner of each room? #simulation is, again, the answer. You can put virtual spray systems in a place and then move them around. You can change the amount of chemicals you spray, the number of jets and their position, the pressure and other parameters till you find the optimum to maximize the effect, kill the viruses, using the smallest amount of disinfectant.

We created a video that shows how this could be done, all through a web-based platform that requires nothing else that the design of the room on a 3D cad file. Limited simulation expertise is needed as well, as the models are already there, created by international experts.

Simulation speeds up the development and testing of new drugs and medical devices

Research and development of medical devices and drugs are expensive and time-consuming. The launch of a new drug requires many years, and this is totally unacceptable during an emergency. In silico (simulation-based) trials can drastically cut this time, with additional benefits such as impressive cost savings and less tests on animals and humans. The European Medicines Agency (EMA) and US Food and Drug Administration (FDA) have collated examples of impacts of model-based approaches for drug development, from the optimization of preclinical testing conditions to increased drug or medical device performance. Virtual models minimize the risk of failure of in vivo clinical testing while freeing up resources to accelerate medical innovation. The use of standardized and validated models also helps comply with rules of regulatory agencies. Today, for example, the evaluation of exposure and exposure-response relationships can be done virtually. This helps shape clinical trial designs and dosing/regimen administrations. In this way it is possible to reduce trials sample sizes and to define a drug therapeutic window, expediting the overall drug development process. Many other applications are already available. Pfizer and Merck&Co/MSD have reported annual cost savings of €88M and €438M respectively through the use of Model Informed Drug Discovery and Development (MID3) for decision-making in drug development.

What are the challenges today?

There are three essential pillars to use #simulation. The first one is a proven, robust solver, based on physical equations. There are companies on the market that can provide them. The second one is computer power: this will help you speed up your simulation, run many cases in a short time in order to find the optimum configuration. Suitable workstations are now available for a few thousand dollars, and cloud computing is a sound reality. The third part is the hardest to find: expertise. Simulation tools are not easy to use. Despite improved and friendly interfaces, wizards and automation, they still require expert people. We really believe that products as our platform is closing this gap.

There is a fourth challenge: people’s and companies’ mindset. #simulation has evolved so much in the last few years that is now able to predict the behavior of very complex systems with incredible accuracy, so we are ready for critical applications as #insilico medicine. Maybe this crisis will generate so many needs that the industry will accelerate the adoption of this technology that has already proven its value in many other fields.

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