Computational Model for Targeted Cisplatin Delivery in Lung Tumors
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Solution Overview
Problem
Current treatments for lung cancer using cisplatin via endobronchial ultrasound-guided transbronchial needle injection lack guidance for optimal injection sites and dosing, leading to empirical approaches with increased side effects and reduced efficacy.
Innovation Solution
A computational model is developed to predict advantageous locations and dosing strategies for cisplatin injection within lung tumors based on tissue and blood vessel density, using patient-specific data to optimize drug delivery and minimize systemic side effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cisplatin is administered intravenously, then the drug can reach the tumor, but normal cells throughout the body are exposed to toxicity resulting in heavy side effects
Solution Approach 1:
The patent divides the drug delivery approach into targeted intratumoral injections at multiple discrete sites rather than systemic administration. The tumor is segmented into multiple injection locations where drug is delivered directly, preventing systemic circulation and protecting normal cells from toxicity while maintaining tumor treatment efficacy
Solution Approach 2:
The patent applies drug delivery locally at specific injection sites within the tumor rather than systemically. By concentrating the drug at the tumor location through targeted injections and allowing local diffusion, the treatment achieves high local concentration at the tumor while maintaining low systemic concentration, thereby resolving the contradiction between efficacy and side effects
2Quantity of substance
If cisplatin is directly injected into the tumor, then higher drug concentrations can be achieved within the tumor, but there is little data to guide the choice of injection sites and dose per site
Solution Approach 1:
The patent performs preliminary computational simulations to determine optimal injection sites and dosing strategies before actual treatment. The computational model predicts drug distribution patterns for various injection configurations, allowing selection of optimal sites that achieve uniform tumor coverage while minimizing total dose, thereby simplifying the treatment planning process
Solution Approach 2:
The patent uses computational modeling that simulates drug diffusion and distribution to provide feedback on predicted treatment outcomes. The model allows evaluation of different injection strategies and selection of the optimal approach based on predicted drug concentration distributions, transforming empirical trial-and-error into a guided, optimized process
3Ease of operation
If cisplatin is given as a single bolus to the tumor center, then the injection procedure is simple, but the dose required to kill all cancerous cells is extremely high
Solution Approach 1:
The patent segments the single large bolus injection into multiple smaller injections at different locations within the tumor. This segmentation allows the drug to be distributed more uniformly throughout the tumor volume, achieving complete cell killing with a total dose that is roughly three orders of magnitude lower than a single central bolus injection
Solution Approach 2:
The patent transitions from a single-point (0D) injection at the tumor center to a distributed multi-point (3D) injection strategy throughout the tumor volume. By adding spatial distribution as a new dimension to the injection approach, the treatment achieves uniform drug coverage and dramatically reduces the total dose required while maintaining procedural simplicity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The model significantly reduces the required dose of cisplatin by three orders of magnitude when distributed across multiple sites within the tumor, enhancing treatment efficacy while minimizing systemic exposure.
Implementation Method 1
The model accounts for diffusion of cisplatin within and between the intracellular and extracellular spaces of a tumor
Implementation Method 2
clearance of cisplatin from the tumor via the vasculature
Data Source
AI summary
A method for treatment of a tumor includes obtaining 3D imaging of the tumor; processing the 3D imaging of the tumor to obtain tumor morphology; determining a number of treatment sites, the locations of such sites, and the treatment dosage using a model of intratumoral treatment dynamics between vascular, intracellular, and extracellular space in order for the tumor to receive a therapeutic dosage at every location of the tumor; and treating the tumor at each of the determined treatment sites and with the determined treatment dosage. In some embodiments, the method further includes generating the model to include a plurality of interconnected volumes wherein each volume has one or more adjacent volumes with a shared boundary. One or more simulations of treatment over time may be conducted using the model, each simulation having a set of one or more initial parameters.