Interactive RNA Production Simulation for Continuous Process Development
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Biopharmaceutical manufacturing processes are time-consuming, resource-intensive, and expensive due to reliance on batch production methods, necessitating a shift towards continuous manufacturing systems.
Innovation Solution
Development of interactive simulators that utilize historical data and literature to create simulated models for continuous RNA production, allowing for safe, controlled, and iterative exploration of various scenarios, reducing the need for real-world experimentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If batch production methods are used, then product quality can be maintained through manual control, but manufacturing time and costs increase significantly
Solution Approach 1:
The patent creates a digital twin (virtual model) of the continuous manufacturing process that replicates real-world behavior. This virtual copy allows for process development, testing, and optimization without physical experimentation, significantly reducing manufacturing time while maintaining product quality through accurate simulation of batch production characteristics
Solution Approach 2:
The system performs preliminary process development and validation in the virtual environment before actual manufacturing. By conducting all process parameter optimization, risk assessment, and protocol development in the digital twin beforehand, the real manufacturing process can proceed efficiently with pre-validated parameters, reducing overall manufacturing time while ensuring quality
2Reliability
If real-world experimentation is conducted for process development, then accurate process understanding is achieved, but costs and time consumption increase
Solution Approach 1:
The patent creates a digital twin (virtual model) of the continuous manufacturing process that replicates real-world behavior. This virtual copy allows for process development, testing, and optimization without physical experimentation, significantly reducing manufacturing time while maintaining product quality through accurate simulation of batch production characteristics
Solution Approach 2:
The system performs preliminary process development and validation in the virtual environment before actual manufacturing. By conducting all process parameter optimization, risk assessment, and protocol development in the digital twin beforehand, the real manufacturing process can proceed efficiently with pre-validated parameters, reducing overall manufacturing time while ensuring quality
3Productivity
If continuous manufacturing is implemented, then productivity and cost efficiency improve, but process complexity and validation requirements increase
Solution Approach 1:
The system performs preliminary process development and validation in the virtual environment before actual manufacturing. By conducting all process parameter optimization, risk assessment, and protocol development in the digital twin beforehand, the real manufacturing process can proceed efficiently with pre-validated parameters, reducing overall manufacturing time while ensuring quality
Solution Approach 2:
The virtual model incorporates feedback mechanisms that continuously compare simulated outcomes with target specifications. This feedback loop enables automatic identification of process deviations and optimization opportunities, simplifying validation by providing clear evidence of process control and performance
4Manufacturing precision
If extensive experimentation is performed to optimize process parameters, then product yield and quality improve, but resource consumption and costs increase
Solution Approach 1:
The patent creates a digital twin (virtual model) of the continuous manufacturing process that replicates real-world behavior. This virtual copy allows for process development, testing, and optimization without physical experimentation, significantly reducing manufacturing time while maintaining product quality through accurate simulation of batch production characteristics
Solution Approach 2:
The system performs preliminary process development and validation in the virtual environment before actual manufacturing. By conducting all process parameter optimization, risk assessment, and protocol development in the digital twin beforehand, the real manufacturing process can proceed efficiently with pre-validated parameters, reducing overall manufacturing time while ensuring quality
Data Source
AI summary
Logic may interact, via one or more interface models, with a client to obtain client input to determine client data for a sequence for a type of ribonucleic acid (RNA). Logic may analyze, via one or more intuitive models, the client data based on historical batch data and experimental batch data to identify additional client data to achieve one or more target metrics of the client data. And logic may simulate, by one or more process models, continuous RNA production based on the client data and the additional client data to generate one or more experimental outcomes of the continuous RNA production defined by the client data and to output a development plan for the continuous RNA production. And logic may amend the client data and the additional client data after each iteration of simulation and perform additional iterations of the simulation until one or more target metrics are met.