AI-Guided Robotic Sperm Preparation Without Centrifugation
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Solution Overview
Problem
Traditional in vitro fertilization (IVF) technologies are expensive, limited by human performance inconsistencies, and inaccessible due to geographic and economic constraints, relying heavily on human clinical embryologists and andrologists.
Innovation Solution
An intelligent, automated system with robotic IVF modules and AI/ML processes for spermatozoa preparation, including imaging and robotic pipetting, to perform and analyze IVF/ICSI procedures without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional human-operated IVF procedures are used, then clinical expertise and judgment can be applied, but costs are high and accessibility is limited
Solution Approach 1:
The patent replaces manual mechanical operations (pipetting, sperm selection, oocyte injection) with automated robotic systems equipped with computer vision and AI. The robotic system uses optical fields (microscopy, imaging) to detect and manipulate biological samples, substituting human hands and eyes with automated sensing and actuation mechanisms.
Solution Approach 2:
The system enables self-service through autonomous operation where the robotic platform independently performs sperm preparation, oocyte selection, and ICSI procedures without continuous human intervention. The AI algorithms automatically analyze images, make decisions, and control robotic movements, allowing the system to serve itself in completing the IVF workflow.
2Adaptability or versatility
If human clinical embryologists perform IVF procedures, then complex decision-making can be made, but human performance inconsistencies and errors occur
Solution Approach 1:
The system implements continuous feedback loops where the robotic platform captures real-time images of sperm and oocytes, the AI algorithms analyze these images to assess quality and motility, and the system adjusts its selection and manipulation strategies based on this feedback. This closed-loop control ensures consistent decision-making based on objective criteria rather than variable human judgment.
Solution Approach 2:
The patent transforms subjective clinical assessments into objective quantifiable parameters. The AI system measures sperm motility velocity, oocyte morphology dimensions, and other biological characteristics as numerical parameters, enabling consistent comparison and decision-making based on measurable data rather than subjective human evaluation.
3Adaptability or versatility
If manual sperm preparation methods are used, then flexibility in handling different samples is maintained, but time-consuming and labor-intensive processes occur
Solution Approach 1:
The robotic system performs sperm preparation continuously without interruption. The platform automatically transitions through stages including sample loading, sperm motility assessment, selection of motile sperm, and transfer to oocytes, maintaining continuous useful action throughout the process without the breaks and repositioning required in manual operations.
Solution Approach 2:
The patent segments the sperm preparation process into distinct automated stages: sample reception and liquefaction, motile sperm identification through imaging, sperm selection and isolation, and transfer to oocytes. Each segment is handled by specialized robotic functions, enabling efficient processing while maintaining adaptability to different sample types through programmable protocols.
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
Reduces costs, enhances accessibility, and ensures consistent performance by automating IVF processes, improving efficiency and reducing human error.
Implementation Method 1
The AI/ML system may use the optics system to optically scan a quantity of sperm to produce a first image object and a second image object
Data Source
AI summary
A method of artificial-intelligence-based robotic pipetting for spermatozoa preparation includes positioning a vessel containing a semen sample within a staging mechanism. The method includes using a robotic pipettor to make at least two droplets within a dish on the staging mechanism. The method includes using the robotic pipettor to connect the at least two droplets with a medium channel according to a programmable design commanded by an artificial intelligence/machine learning system (AI/ML system). The method includes using the robotic pipettor to deposit a quantity of sperm from the semen sample into one of the droplets. The method includes using the AI/ML system to optically scan the quantity of sperm to produce first and second image objects using an imaging system that includes a microscopy system, a camera system, and a lighting system. Creation of the image objects is separated by a specified time duration.