Patient-Specific Cell Therapy Scheduling From Synthesis And Culture Times
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Solution Overview
Problem
Cancer immunotherapy using base-sequence-modified immune cells is time-consuming, typically taking several days to weeks, necessitating efficient management to expedite treatment for cancer patients, especially severe cases, and requiring specific early treatment schedules for patients, medical institutions, and cell manufacturers.
Innovation Solution
An information management apparatus and computer program that acquire and store time information related to synthesizing and culturing cells, associate this information with patient attributes, and calculate prediction values for treatment schedules based on correlation analysis, enabling efficient management and early treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If base-sequence-modified immune cell therapy is performed, then personalized cancer treatment is achieved, but treatment time becomes excessively long (several days to weeks)
Solution Approach 1:
The system performs preliminary actions by pre-establishing treatment schedules and predicting required timeframes before actual treatment begins. The information management apparatus acquires time information related to synthesizing nucleic acids and culturing cells in advance, allowing stakeholders to plan and coordinate activities beforehand, thereby reducing overall treatment delays.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring and storing time information for various treatment steps, then using this data to generate prediction values for treatment schedules. This feedback loop allows the system to learn from actual treatment durations and improve future time estimates, enabling better coordination and potentially shorter treatment cycles.
2Reliability
If treatment schedules are customized for each patient, then treatment effectiveness is optimized, but scheduling complexity and coordination difficulty increase
Solution Approach 1:
The information management apparatus serves multiple functions within a single system: it stores patient attribute information, acquires time information for various treatment steps, calculates prediction values for schedules, and provides this integrated data to multiple stakeholders including patients, medical institutions, and cell manufacturers. This multi-functionality reduces the need for separate specialized systems.
Solution Approach 2:
The system acts as an intermediary between various stakeholders (patients, doctors, laboratories, manufacturers) by centralizing and standardizing treatment schedule information. It translates complex treatment requirements into standardized prediction values and schedules that can be understood and coordinated by all parties, thereby reducing communication and coordination complexity.
3Measurement precision
If time information for all treatment steps is collected and analyzed, then treatment schedule prediction accuracy is improved, but information management complexity increases
Solution Approach 1:
The system segments the treatment process into distinct time-critical steps (synthesizing nucleic acids, culturing cells, etc.) and collects time information for each step separately. This segmentation allows the information management apparatus to process and analyze time data in manageable units, improving prediction accuracy without overwhelming complexity in information management.
Data Source
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AI summary
An information management device according to the present invention is equipped with at least one processor and causes the at least one processor to function so as to acquire, on the basis of a first cell acquired from a cancer patient, first time information pertaining to the time required to acquire a prescribed amount of at least one specific nucleic acid and second time information pertaining to the time required to culture second cells different from the first cell until a prescribed amount is reached, and so as to associate the first time information and the second time information with attribute information of the cancer patient and store the result as individual patient information.