To Transform Medtech, Device Companies Must Embrace Simulation

ARTICLE SUMMARY:

Medtech companies are warming to the use of computational models of virtual patients for device design. There are signs that regulators are starting to embrace it too. By Steve Levine, PhD, Dassault Systèmes.

Computational Modeling and Simulation (CM&S) has begun to revolutionize the fields of medical devices and life sciences.

CM&S is already used across many industries to optimize product designs, elevating design engineering from an empirical “build-and-test” discipline to a “model-and-simulate” paradigm.

The traditional approach to the development of medical devices has been to design, build and physically test, in the laboratory (in vitro) and through animal and human trials (in vivo). Only after these physical tests provided evidence of the safety, reliability, and effectiveness of the device, would the company apply for regulatory approval. Given health outcomes and people’s lives are at stake, this approach was seen as unavoidable.

Enter a new paradigm of medical device evaluation that involves the review of scientific evidence from four models: laboratory data from the bench tests, animal data, data from human trials, and increasingly, data from computational modeling (in silico).

The goal is to have less reliance on animal and human data with the greater influence from computer simulation, including virtual models like specific cells, organs and body systems, virtual physiological patients, and even families. Medical device makers can build models of devices and specific body systems and run comprehensive device performance simulations. They can try out a multitude of scenarios, adjusting variables and conditions, evaluating a large number of possibilities in a relatively short time, finding optimal results and then go to the physical lab.

Evolving Regulatory Landscape 

In its August 2011 report, Advancing Regulatory Science, the US Food and Drug Administration identified an important role CM&S can play in four of its eight strategic priorities to better predict medical products safety, efficacy, and performance:

  • Modernize toxicology

  • Stimulate innovation in clinical evaluations and personalized medicine to improve product development and patient outcomes

  • Ensure FDA readiness to evaluate innovative emerging technologies

  • Harness diverse data through information sciences to improve health outcomes

Overview of CM&S Types in Use and Emerging Technologies

Computational Modeling and Simulation has the potential to be used throughout the product life-cycle, from ideation and discovery to testing and regulatory decisions, to product launch, and post-market monitoring. Because the cost of a change increases significantly later in the development, it is important to use these tools early in the development process to prevent poor designs from moving downstream.

Simulation is already used in the early stages of development of orthopedic and cardiovascular devices to evaluate their reliability and provide rapid insight into design improvements. The experience gained in the upstream design process is now making its way into the hands of clinicians who deploy these products into patients. One example is a clinical simulation of positioning and deployment of various types of valves in the heart or electrodes in the brain, allowing physicians to perform virtual surgeries to be optimally prepared before to the real surgery.

Uses of modeling and simulation include:

  • Anatomy, such as musculoskeletal structures

  • Physiology of organ systems, such as the heart and vasculature

  • 2D and 3D chemical structures

  • The medical device itself, with tailored device parts

  • Radiofrequency waves delivered to and absorbed by human tissue

A number of other models are on the horizon, including:

  • Biocompatibility of materials used in devices

  • Blood damage, hemolysis and thrombosis

  • The healing process of chronic wounds

  • Ultrasound-enhanced drug delivery

  • Biomarkers for allergic risks

  • Virtual clinical trials for regulatory evaluation

Barriers to Adoption

Despite the increasing use of CM&S in a range of medical device applications, wider adoption will grow as technical, scientific, and regulatory challenges are addressed. A key technical limitation is the lack of knowledge about detailed aspects of the human body needed to create accurate models. For example, the electrical conductivity of human body tissues depends on the type of tissue and body temperature, and it varies from person to person with age and disease state. We are seeing great strides in acquiring this data and the models are improving as a result.

According to a 2014 member survey conducted by the Medical Device Innovation Consortium (MDIC), the biggest barrier preventing the industry from more fully embracing CM&S is regulatory uncertainty. The medical device approval process is rigorous, and the FDA sees tremendous potential in this technology. While there is still uncertainty in the industry whether evidence from computer models will be accepted by the regulators, recent statements and activities suggest the future is bright for this approach.

In November 2018, the American Society of Mechanical Engineers (ASME) introduced a new V&V 40 standard for assessing the credibility of computational modeling through verification and validation, with specific application to medical devices, including endovascular and orthopedic devices, heart valves, and stents. “With credible computational modeling, the medical device industry can meet many challenges, streamline processes, reduce costs and scale the development of new technologies for wider use,” said Ryan Crane, PE, Director of Standards and Certification Initiatives for ASME. “Ultimately, these standards and engineering processes can help make a real difference in people’s lives.” 

The FDA participated in the development of the standard. “We believe that standardized computational modeling techniques will aid in the design, testing and regulatory review of medical devices or components that will ultimately lead to a more efficient and lower-cost way of evaluating devices throughout their total product life cycle,” said Tina Morrison, PhD, deputy director of the division of applied mechanics of the FDA and chair of FDA's modeling and simulation working group. 

The Bright Future of CM&S in the Medical Device Industry

The changing FDA landscape, the establishment of the public-private partnerships such as the MDIC and release of the new Computational Modeling standard are the tailwinds that will help the industry adopt CM&S more widely. Additional public-private partnerships include:

  • As part of Singapore’s Smart Nation effort, Dassault Systèmes partnered with the city to develop Virtual Singapore, a virtual representation of the city that allows users (such as city planners, public agencies, civil engineers and students) to visualize in 3D how the city will be develop and evolve in response to population growth, new construction and major events. 

  • Together, Wichita State University (WSU), the National Institute for Aviation Research (NIAR) and Dassault Systèmes opened the 3DEXPERIENCE Center Wichita, which offers expertise in additive manufacturing, 3D printing, reverse engineering and the largest flexible cave for 3D immersive reality.

  • Oak Ridge National Laboratory and Dassault Systèmes are working together to enable 3D design and printing of large structures to support development in additive manufacturing.

  • The World Bank Grouppartners with developing nations to finance healthcare. Countries pool revenue in public and private insurance and into a national health system with automatic coverage.

  • IFPMA represents a partnership between pharmaceutical companies and healthcare associations to provide industry expertise and improve global health.

Today, medical device makers can use computer modeling and simulation to eliminate bad designs before they leave the drawing board. Tomorrow, they will be able to refine and perfect many good designs before they are used on human patients. In the not-too-distant future, ‘digital twins’ consisting of 3D models, simulations of virtual organs, biological systems and patients will augment, and maybe replace a portion of real patients in human clinical trials. 

Dr. Steve Levine is Sr. Director of Life Science and the Founder of the Living Heart Project. Steve is responsible for leading the Virtual Human Modeling strategy for Dassault Systèmes and has more than 30 years of experience helping companies deploy computational modeling methods to address the most challenging scientific topics. Steve holds a Ph.D. in Materials Science and Engineering from Rutgers University and has been elected into the College of Fellows at the American Institute for Medical and Biological Engineering (AIMBE).


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