Paolo Colombo, marketing manager at software company Ansys, used to be a pilot. He once flew the Lockheed F-104 Starfighter aircraft, which was designed in the early 1950s. The plane was required to be very light, low-cost, and simple and easy to build and maintain.
It was also required to outperform any other aircraft. While the Starfighter was the first aircraft to hold simultaneous official world records for speed, altitude and time-to-climb, developing and testing it was challenging.
At the recent Ansys conference in Paris, Colombo explained that engineers attached the wings to rockets and then fired them to observe how they performed aerodynamically using on-board cameras.
Colombo talked about how far product design and testing has come since then. Today, design and testing are moving away from the physical and into the realm of digital simulation. It’s all because of software from companies such as Ansys that can accurately simulate our world.
Also speaking at the Ansys conference, Ferdinando Cannizzo from Ferrari said that the company’s aim for the near future is to conduct 90% of the testing and development of its vehicles solely using simulation software, before physical validation of the results in real-world tests.
This is largely because of the advances that have come in simulation software as well as in Internet of Things (IoT) technology. By live streaming data from sensors in an oil pump, for example, using IoT software platforms such as PTC’s ThingWorx, engineers can create a “digital twin” of the real system. This allows for realtime monitoring and modelling of potential scenarios for hazard detection and predictive maintenance.
But if a problem arises, say on a pressure valve, you can run that near-realtime data in simulation software and check various scenarios to identify the cause and how best to resolve it. You can then implement a fix remotely and run further simulations to pinpoint why the fault occurred. This data can then feed into refining and optimising the design of future, more robust products.
Dr Adriano Henney, secretary general of the Avicenna Alliance for Predictive Medicine, hopes one day to be able to create “human digital twins” to aid in the testing and development of medical devices and treatments. But he admits that his sector is far from being able to make that a reality.
Henney said: “The difficulty is that the human body is a combination of genetics, environment and development that come together to create individuality and stochastic variability.” It is incredibly difficult to understand the dynamic interaction of the networks in the body, as even if one fails another may be able to step in and take over.
“We are nearer the level that engineers for the Starfighter aircraft were in 1952 firing off rockets. We are still reliant on physical ‘in vitro’ and ‘in vivo’ testing,” he said.
That is not to say that the medical sector isn’t beginning to make strides in using modelling and simulation to help support diagnoses and treatment, before clinical trials are conducted. This is often referred to as “predictive medicine” or “in silico medicine”. Henney said that the medical sector is able to turn massive amounts of data into “actionable information” using computer models. This can involve modelling small parts of the human body, such as the knee, to run simulations on chemical treatments for arthritis. Alternatively, projects such as the collaboration between Ansys and the University of Sheffield are using digital simulations based on coronary angiograms to carry out non-invasive assessments of where to put a stent in a patient’s body. There has already been a small but very successful trial funded by the Wellcome Trust.
The reason for this drive towards in silico medicine is largely down to the challenges of treating an ageing population. By 2030 it is predicted that 25% of the EU’s population will be over 65 years old. And with age come chronic and debilitating diseases that are difficult to understand and treat.
“Treatments only have limited usefulness for conditions like rheumatoid arthritis, as, while they can be managed, we don’t truly understand how they operate,” explained Henney. This is true of a lot of chronic conditions. Antidepressant drugs typically have a 38% success rate in the general population, while asthma drugs are only 40% effective.
Using simulations to test new drugs could help create more effective treatments before live clinical trials take place. It could also speed up costly drug trials, which often do not make it past the early stages, wasting billions of pounds in the process.
Being able to better treat chronic conditions such as diabetes or rheumatoid arthritis, rather than simply managing the symptoms, could also save countries a lot of money. Henney believes that, unless countries are able to adopt in silico medicine, these problems could bankrupt countries.
However, much work needs to be done to create legislation and standards for the use of simulation software in the medical sector. The Avicenna Alliance was formed to act as an advisory body to navigate this area between academia, industry and government.Following on from an EU-funded project defining a roadmap for in silico clinical trials, the not-for-profit organisation now focuses on building confidence in using the technology, through supporting the development of a policy framework, providing case studies using patient-specific modelling and simulation applied in the R&D of new biomedical products, as well as in the evaluation and assessment of clinical and pre-clinical trials. While Europe is lagging behind other countries such as the US in its approach to in silico medicine, in the European parliament it was recently said that the “virtual physiological human will revolutionise the way health knowledge is produced, stored and managed, as well as the way in which healthcare is delivered”.
While the sentiment is there, Henney said that there is a need for greater collaboration between industry, government, academics and clinicians to make progress happen.
There are many hurdles, both technical and regulatory, to overcome on the path to the human digital twin, but the growth of IoT wearable devices could help us get there faster. “Apple watches have ECG machines approved by the US Food and Drug Administration to check for medical issues such as arrhythmia, and Google has developed contact lenses with glucose sensors for diabetics,” said Henney. “With the kinds of sensors that we carry about we are capable of accessing data to better understand our lifestyles.”
This kind of data could be used in much the same way as the sensors on an oil pump can be used to bring realtime information into digital simulations, and ultimately lead to the development of highly individualised medical solutions.