Automated IVF and ICSI With AI-Guided Robotic Needle Control
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Solution Overview
Problem
Traditional in vitro fertilization (IVF) technologies are dependent on human clinical expertise, leading to high costs, geographic limitations, and inconsistencies due to human performance, limiting access and efficiency.
Innovation Solution
An automated IVF system utilizing robotic modules, imaging, and artificial intelligence/machine learning for tasks such as intracytoplasmic sperm injection (ICSI), including zona pellucida detection, sperm positioning, and egg manipulation, reducing human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional manual IVF methods are used, then human expertise and judgment can be applied, but costs are high and access is limited due to geographic and economic constraints
Solution Approach 1:
The patent replaces manual mechanical operations by human embryologists with an automated robotic system that uses computer vision, machine learning, and robotic manipulation to perform IVF procedures including oocyte retrieval, ICSI, and embryo transfer, thereby reducing geographic and economic barriers while maintaining procedural quality
Solution Approach 2:
The system enables self-service automation where the robotic platform independently performs complex IVF procedures without continuous human intervention, using AI-driven decision-making to guide robotic actions throughout the workflow from sample preparation to procedure completion
2Reliability
If human clinical embryologists perform IVF procedures, then expertise and judgment are applied, but inconsistencies occur due to human performance variations
Solution Approach 1:
The system incorporates real-time feedback loops where computer vision systems continuously monitor procedural parameters, machine learning models analyze outcomes, and the robotic system adjusts its actions based on this feedback to maintain consistent, high-quality performance across all procedures
Solution Approach 2:
The system performs preliminary actions including pre-programming of procedural protocols, pre-training of machine learning models on extensive datasets, and pre-calibration of robotic systems to ensure consistent performance before actual IVF procedures begin
3Productivity
If automated robotic systems are implemented, then costs are reduced and access is improved, but system complexity increases
Solution Approach 1:
The robotic system is designed as a universal platform capable of performing multiple IVF procedures including oocyte retrieval, ICSI, embryo culture monitoring, and embryo transfer using the same core robotic architecture, thereby improving productivity without proportionally increasing complexity
Solution Approach 2:
The system merges computer vision, machine learning, robotic manipulation, and fluid handling into an integrated unified platform, combining multiple functions into a single cohesive system that improves overall efficiency while managing complexity through integration
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
Enhances efficiency, reduces costs, and standardizes IVF processes across different settings by minimizing human error and geographic barriers, improving access to IVF services.
Implementation Method 1
The AI/ML system and imaging system may be used to assess a thickness of the zona and determine an ablation action, may generate a laser to ablate a pre-designated section and depth of the zona pellucida
Implementation Method 2
The AI/ML system and imaging system may be used to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor
Implementation Method 3
breaking the egg membrane (oolemma) using a piezoelectric pulse
Data Source
AI summary
A method for automated ICSI includes providing an egg, using AI to position a robotic ICSI needle, moving the robotic ICSI needle forward into the egg, stopping the robotic ICSI needle at the end point of an injection path, breaking the egg membrane (oolemma) using a piezoelectric pulse, and depositing the sperm in the egg. The methods can also include confirming that the sperm is out of the needle, moving the needle out of the egg, and releasing the egg from a holding pipette.