System-Level Modeling Approach to Improve Mechanical Ventilation

Towards a system level modeling approach to improve mechanical ventilation

This pandemic COVID-19 outbreak has called for all possible acceleration in medical innovation to improve immunity and to stay prepared to treat the adversity on health grounds. Besides the in vivo and in vitro approaches, the in-silico ways would complement this mission. Such advanced adoption of computational modeling offers many advantages starting with patient safety going on to personalized treatments, bringing down the invasive routes of drug administration to make it more painless. The focused work on Novel Drug Delivery Systems (NDDS), a 505 (b) (2), or a Paragraph 4 filing would benefit by better optimization when the right set of simulations are devised to pave the way on.

Ethical concerns on animal testing have also been spinning off lately to grab more attention into the in-silico adoption. Digitalization and simulation put up to the right use, there’s more data generated and that would come from more candidates analyzed by a larger sample on the Design of Experiments (DOE).

The outputs derived from simulations can be better quality inputs for the PBPK/PD models to work with. So, the modeling studies actually can be ranging from a 3D component level to a system level. System-level simulations or the Reduced Order Models (ROM) derived from a detailed 3D model simulation can present quicker ways of analyzing even biological units to for necessary responses or stimuli in a virtual environment.

Even the fields as niche as tissue culture, genetics can benefit very much from computational modeling with a focus to virtually study the sensitivity of the cells to the imposed bio-environment. What if scenarios on the impeller speed, fill level and the positioning of the scaffold, etc.., can be virtually studied to find the right answers before going to be physical. Forensic science as well seeks to use simulations to discover the root cause of the victim’s damage, such as explaining the angle of attack of a bullet based on the sort of wound it plunged in the body.

As mentioned, while 3D simulations are always there to cater to the finest details needed, developing system-level models is also equally important to be quick at attending to treatments for patients requiring personalized therapies. As of today, even surgeons with a very limited mathematical background can leverage computational modeling successfully to plan and execute critical, life-sustaining surgeries proving to be a bliss to the enrolled patients.

In the case of a life-sustaining mechanical ventilator, the focus is to use patient-specific operational conditions for the pressure applied based on the flow rate of the ventilation. This is to avoid any Ventilator Induced Lung Injury (VILI) which can be either acute possibility or unless for Severe Acute Respiratory Syndrome (SARS) such as COVID-19. The below-shown representation is a system-level network built with Ansys Twin builder by mechanical & electrical elements to represent the reaction of an artificial lung connected to an input waveform from a mechanical ventilator.

Figure 1: Simulation Model in ANSYS Twin Builder

The model input is a pressure wave supplied to the lung (cylinder with piston) through the trachea (pipe). A flow sensor is used as an en-route to measure the flow rate. Mechanical spring and damping are used to represent resistance and compliance. We can see the conversion from cmH2o to Pascal & Liter’s to m3 in the above expressions to match the medical unit system for the mechanical Spring and damping coefficients.

The below representation is the simulation result as the lung volume and flow rate as a reaction to the fed pressure waveform

Figure 2: Lung Pressure, Volume and flow rate

In addition to the system modeling, a 3D simulation is performed using the Ansys CFD tools on a lung airway model. A real-time breathing cycle is used as an input to such simulation.

Figure 3: The applied breathing cycle and the velocity in the lung air way as a 3D Simulation output

An initial pursuit has been set up to conceive a simulator which can offer an easily accessible platform to test and monitor a pressure signal and other parameters during artificial ventilation. Besides the deployment for regular medical care, this simulator is intended for academic learning and training as well. The outlook is about simulating a 3D Computational Fluid Dynamics (CFD) model and building a Reduced Order Model (ROM) of the breathing cycle in Ansys Fluent. Such ROM shall then be integrated with Twin Builder to develop a holistic response system.

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Ultraviolet Germicidal Irradiation for Disinfecting N95 Masks

Need of UV Disinfection

A sudden rise in the demand for N95 masks as PPE (Personal Protective Equipment), has been widely recognized among the general public during this COVID-19 pandemic. This unexpected demand has resulted in a limited supply of equipment. The need of the hour suggests disinfecting and reusing disposable N95 Filtering Facepiece Respirators (FFRs).

In this context, Ultraviolet Germicidal Irradiation (UVGI) is considered an effective adjunct. Though it is not a stand-alone technology, this could be a method for respiratory disinfection as it has corroborated effectiveness in inactivating an extensive group of pathogens including coronavirus.

Germicidal UV typically engages mercury-based lamps operating at 254nm, the energy at which strongly absorbed by nucleic acids, resulting in damaging RNA and DNA molecules in pathogens preventing their further growth and function.

Moreover, the irradiation level of UVGI inactivating those pathogens does not hamper the fit and filtration characteristics of N95 FFRs. As per the literature, in the range of 0.5-950J/cm2, FFR fit performance is at 90-100% passing rate after 3 cycles depending on model whereas exposures as low as 2-5mJ/cm2 are capable of inactivating coronaviruses on surfaces. Thus, though proven to be an efficient method, UVGI could be used to effectively disinfect disposable respirators for reuse but the maximum number of disinfection cycles will depend on the respirator model and the UVGI dose required to inactivate the pathogen.

Simulating the performance of your UV System:

The design method of UV systems needs some questions to be answered before starting the design:

  • How much irradiance do we need to kill bacteria?
  • How many UV sources do we need?
  • What power should they have?
  • Where should we place them?

Simulation tools like ANSYS SPEOS help designers to efficiently answer these questions.

Besides, the ray-tracing capabilities of the tool also help in calculating accurately radiometric distribution in UVGI Devices with different surface reflectivities and lamp configurations.

ANSYS SPEOS Simulation to calculate Irradiance over the surface of N95 Mask

Apart from Radiometric studies, Structural Integrity of the respirators is one of the major concerns & studies show a noticeable decrease in structural integrity at lower doses. In conclusion, there are so many works of literature which suggests UVGI can be used for respiratory disinfection, though the maximum number of disinfection cycle will be limited by the respirator model and UVGI doses.

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Confronting COVID-19 with Optics & Photonics

At the zenith of such a situation when the whole world is fighting against a pandemic COVID-19, a multidirectional approach for combating requires excessive attention. The quick detection of infected patients stands as a primary challenge due to variability in the symptoms. Though the field of Optics and Photonics provides various conventional molecular analysis instruments such as multiple spectrum cameras, multispectral optical spectrometers, and they still couldn’t achieve a potential detection method for the masses. Moreover, these methods are time-consuming, prone to error, and may lead to respiratory infections.

Recently, a method involving biosensor which uses thermal and optical effect for safe and reliable detection of COVID is to be seen in a picture. The Plasmonic biosensor used for detection combines Plasmonic Photothermal (PPT) and Localized Surface Plasmon Resonance (LSPR) on a tiny gold nanoisland chip kept on a glass substrate. Artificially produced DNA receptors that match specific RNA sequences of the SARS-CoV-2 virus are grafted onto the AuNI chips. Through Nucleic Acid Hybridization, sensitive detection of specific RNA sequences of the SARS virus is done. LSPR creates plasmonic near field by exciting the metallic nanostructure. The change in the refractive index is measured using an optical sensor helping in determining if the sample contains RNA strands of SARS. The LSPR response due to plasmonic sensing determines the concentration of sequences ranging from 1 pM to 1 nM. PPT helps in boosting the ambient temperature to secure the detection of only reliable matching of RNA strand and DNA receptor.

The sensing stability, sensitivity, and reliability of the device can be significantly enhanced by measuring the same at 2 different angles under 2 different wavelengths. The thermo-plasmonic heat is generated on the AuNI chips while being illuminated at their plasmonic resonance frequency for better sensing performance. The localized PPT heat can elevate the hybridization temperature during the process and facilitate the accurate discrimination of two similar gene sequences.
Though this technique is not yet efficient for a high frequented location, yet it embarks a step closer towards the modern techniques of simulations for such complicated processes.

ANSYS Lumerical Suite comes with all the tools which are required to simulate surface plasmon resonance(SPR) and photothermal heating in plasmonic nanostructures. It comes with a Finite difference time domain (FDTD) solver and heat transport solver for thermal simulation.

The picture below (fig 1) shows the simulation done for getting a source incidence angle that excites the SPR. The absorption in the Silver was measured to determine the angle with the strongest coupling.

Fig:1 Electric Field intensity vs Incident Angle
Source: Lumerical Knowledge Base
Simulation is done on plasmonic nano-structures to understand the effect of varying optical intensity on the performance
Source: Lumerical Knowledge Base

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