Supramolecular Therapeutics Design via Computational Modeling
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Solution Overview
Problem
Current approaches to cancer treatment, such as immunotherapy and nanomedicines, face challenges in achieving high therapeutic concentrations in tumors without causing systemic toxicity, and existing methods for designing supramolecular therapeutics lack insight into the mechanisms of self-assembly and interactions with excipients, limiting their effectiveness.
Innovation Solution
The Volvox process integrates computational modeling and human thought to design supramolecular therapeutics by combining quantum mechanical energy state- and force field-based models with all-atomistic explicit water molecular dynamic simulations to optimize molecular structures for stable interactions, enabling the creation of stable supramolecular structures like taxane and kinase inhibitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If small molecule therapeutics or biologics are used to achieve high therapeutic concentrations in tumors, then therapeutic efficacy is improved, but systemic toxicity increases
Solution Approach 1:
The therapeutic system is segmented into distinct components: hydrophobic therapeutic agents are segmented from hydrophilic excipients through self-assembly into supramolecular structures. This segmentation allows the therapeutic payload to be concentrated in tumor tissues while the hydrophilic exterior minimizes systemic toxicity by improving circulation stability and reducing off-target effects.
Solution Approach 2:
Hydrophilic excipients act as intermediaries between the hydrophobic therapeutic agents and the aqueous biological environment. These excipients self-assemble to form supramolecular structures that encapsulate the therapeutic agents, enabling safe delivery through circulation and targeted accumulation in tumors via the EPR effect, thereby reducing systemic toxicity.
2Reliability
If nanomedicines or antibody-drug conjugates are used to deliver greater quantities of therapeutic payload to tumors, then therapeutic concentration is improved, but the ability to load enough payload onto the carrier becomes challenging
Solution Approach 1:
The supramolecular structures utilize self-service through spontaneous self-assembly of molecular subunits driven by supramolecular interactions. This self-organizing process automatically optimizes payload loading capacity based on the inherent properties of the therapeutic agents and excipients, eliminating the need for complex external control mechanisms and achieving high payload capacity naturally.
Solution Approach 2:
The system employs parameter changes in the supramolecular interactions between molecular subunits to dynamically adjust and optimize payload loading capacity. By modulating factors such as excipient concentration, molecular structure, and interaction strength, the system achieves optimal payload encapsulation without requiring complex engineering controls.
3Ease of manufacture
If current approaches of engineering supramolecular therapeutics using stochastic design of molecular subunits are used, then supramolecular structures can be formed, but insight into mechanisms of self-assembly and interactions with excipients is limited
Solution Approach 1:
The invention implements feedback mechanisms through computational modeling and simulation that provide real-time insights into self-assembly mechanisms and excipient interactions. By integrating these computational tools with experimental data, the system continuously refines its understanding of supramolecular formation processes, transforming the previously stochastic design into a rational, mechanism-driven approach.
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
This approach allows for the rational design of supramolecular therapeutics that minimize exposure to normal tissues while effectively targeting tumors, potentially increasing therapeutic efficacy and reducing systemic toxicity.
Implementation Method 1
molecular subunits self-assemble through supramolecular 'weak' interactions to form large complex structures
Implementation Method 2
all-atomistic explicit water molecular dynamic simulations of interactions with excipients
Data Source
AI summary
The disclosure provides a process of designing and optimizing supramolecular therapeutics. The disclosure also provides a method for designing and optimizing antibody drug conjugates.