At OscilloBeam Therapeutics, simulation is a major innovation tool. By integrating advanced computational modeling across the entire R&D process, we ensure that each therapeutic component—nanoparticle, field array, and thermal dose—is optimized prior to any physical deployment. This approach has accelerated development timelines, enhances therapeutic precision, and supports safer translational science.
Magnetic Field & Coil Design Optimization
Our alternating magnetic field (AMF) generators are modeled using FEM solvers such as ANSYS Maxwell and COMSOL Multiphysics®. These simulations enable precise calibration of coil geometry, orientation, and current density to maximize uniformity across the tumor region and minimize energy loss.
Key performance outputs include:
- Specific Absorption Rate (SAR) mapping across 3D tumor volumes
- Field gradient prediction to guide magnetic targeting
- Frequency tuning (typically 100–500 kHz) to align with nanoparticle response thresholds
By optimizing these parameters in silico, we significantly reduce the need for iterative hardware prototyping, cutting time and cost during device engineering.
Photothermal Modeling & Thermal Kinetics
To evaluate the heat transfer and bio-thermal impact of our system, we employ the Pennes’ Bioheat Equation and implement heat diffusion models for both healthy and tumor tissues. These models simulate photothermal heating induced by near-infrared (NIR) irradiation (typically 808–880 nm), using validated absorption coefficients and scattering properties of biological tissues.
Simulated outcomes include:
- Localized temperature elevation of 15–20°C in the tumor site
- Time–temperature response curves under pulsed or continuous laser exposure
- Spatial heat distribution to evaluate thermal gradients across tissue boundaries
These models ensure that therapeutic thresholds are achieved without exceeding safety limits for surrounding structures.
Nanoparticle Behavior & Targeting Efficiency
Our magneto-photothermal nanocarriers are also digitally validated using molecular dynamics (GROMACS, LAMMPS) and particle behavior simulations to assess clustering, aggregation, and passive targeting via the Enhanced Permeability and Retention (EPR) effect. Simulations also incorporate:
- Ligand–receptor interaction models for active targeting
- Surface charge and hydrodynamic radius tuning to prolong circulation
- Responsiveness to AMF activation and NIR absorption efficiency
Through predictive modeling, we can estimate dose distribution, binding efficacy, and kinetic release profiles—long before in vivo validation.
Light–Tissue Interaction Simulations
To ensure effective photothermal activation across variable tumor locations, we utilize Monte Carlo simulations of photon migration through layered tissues. This allows us to define:
- Optical penetration depth of NIR across skin, muscle, and tumor layers
- Effective fluence rates for deep-seated vs superficial tumors
- Laser safety margins under ANSI exposure guidelines
End-to-End Outcomes
By embedding simulation across electromagnetic, thermal, and biological domains, OscilloBeam achieves:
- ~70% reduction in device prototyping cycles
- Earlier detection of off-target risks and thermotoxicity
- Data-driven personalization of treatment plans (based on tumor size, depth, and composition)
- Better alignment with ISO/FDA design control and validation pathways
In short, simulation isn’t just how we accelerate—it’s how we anticipate. It allows us to engineer safer, smarter, and more effective cancer therapies, while de-risking early development and delivering a strong foundation for clinical validation.