Highlights
Medical device makers have always used test-based design processes to ensure the safety, efficacy, quality, and performance of their products. This methodology follows a sequential path from bench testing to animal studies and final clinical trials. Data collected from these are used as the source of evidence to ensure regulatory compliance.
However, ensuring accurate data collection, defining precise methods to draw correct conclusions, and complying with evolving regulations is a herculean task, given the innovation-driven medtech domain and the pressure of shorter time-to-market. Considering the patients who are hopefully waiting for a panacea, any delay in delivering a device or therapy could be at the cost of a human life. This is where capabilities in Computational Modelling and Simulation (CM&S) are proposing a paradigm shift.
Medical device manufacturers are always under pressure to innovate and launch products as quickly as possible, meeting the ever-increasing safety and regulatory standards. Traditional methods are no longer enough to keep pace with the product development and certification needs.
Computational Modelling and Simulation technologies are now an essential tool for evaluating new concepts, enhancing device capabilities and performance while accelerating product development and reducing time-to-market.
With computational models in product development there is increased efficiency in data-gathering that in turn helps in making better decisions. Simulation stretches the limits of empirical space that will generate data for measurements hitherto too expensive or even impossible and enable early detection of design flaws (fail early). Simulation outputs can be used as artifacts for regulatory compliance, which acts as a catalyst in minimising time from lab to patient. Medical device industry is embracing computational modelling and simulation as a transformative tool that acts as a catalyst for innovation to alleviate pain of patients in need.
CM&S is used in the product development life cycle to accelerate the development, verification and validation of medical devices. With patient safety and wellbeing at stake, the predictive capability of a computational model, also known as model credibility, is of utmost importance.
Uncertainty quantification is an important step of generating and applying mathematical models to estimate uncertainty in the empirical data or simulation results.
Model credibility is ensured through verification, validation, and uncertainty quantification (VVUQ). The mathematical correctness of a computational model can be established by verification, while its fidelity to the empirical data can be ensured by validation.
Though regulatory compliance needs are specific to a country or a geography they all share a common perspective that there are different classifications of medical devices based on the probability of causing patient harm. The higher the risk classification, the higher the degree of evidence that the medical device maker must provide to satisfy the regulatory compliance requirements.
Conventional methods that are followed to create evidence include laboratory testing, animal studies, and clinical studies after which the medical device is approved cleared for investigational use across a relatively small group of patients. CM&S is the fourth source of evidence. It is of great value to medical device manufacturers and regulators due to its power to provide insights into device function which cannot be achieved through any other sources. This is due to the ability of CM&S to noninvasively and non-destructively “see inside” the working environment as well as the device. CM&S also generates huge amount of data compared to traditional methods.
This is an important engineering tool that every medical device manufacturer must use to stay relevant in business.
The In Silico Clinical Trial (ISCT) process follows four steps. The first step in this process is building virtual patients, which are three-dimensional anatomical models developed from CT or MRI imaging.
The sample is chosen to reflect and represent the real-world population taking into consideration age, sex, and disease severity.
For example, a device such as a heart valve may include hundreds of patients. The patient sample will determine how useful and valuable are the results of the trials.
Next step is to introduce the medical device as a geometric model into each of the digital patient twin’s anatomy which was created in the first step after which simulation parameters are defined by including material properties, boundary conditions, and operating parameters. In the third step simulation will be initiated to compute how the medical device interacts with the anatomy under realistic conditions. Depending on the device class and therapeutic needs additional parameter can be analysed. These parameters help identify design flaws early (fail early).. In the final step, the simulation results are documented in the prescribed verification and validation (V&V) report format and prepared for regulatory submissions as per FDA and European Commission requirements.
Computational Modeling and Simulation (CM&S) is making its mark throughout the medical device product lifecycle, thanks to the underlying digital engineering platform. Digital BioTwin, patient-specific simulations, and AI-interventions are increasingly integrated into clinical and regulatory practices for building trust and enabling innovation.
The most disruptive aspect of CM&S is in clinical planning enabled by In Silico Clinical Trials (ISCT), which uses "virtual patients" to evaluate safety and efficacy.
Moving away from the traditional "design -build-and-test" methodology to a digitally enabled predictive approach using physics-based engineering that is coupled with physiological human models and digital bio twins, CM&S dramatically reduce research and development efforts, reduced clinical trial costs in turn speeding up regulatory approval.
FDA accepts computational modeling and simulation evidence provided the model satisfies the requirements of ASME V&V 40 standard. The European Medical Device Regulation (MDR) also accepts modeling and simulation evidence. This is the way forward to a better clinical outcome and enhanced patient safety.