IP Library › Granted Patent US 12,310,625
Granted Patent B2
US 12,310,625 · App. 18/431,259 · Granted May 27, 2025

Autonomous insemination in an intelligent automated in vitro fertilization and intracytoplasmic sperm injection platform

Inventors: Gerardo Mendizabal-Ruiz (Guadalajara, MX); Joshua Abram (Lyme, CT); Roberto Valencia-Murillo (Las Paz, MX); Vladimir C. Ocegueda Hernandez (Zapopan, MX); Nuno Costa-Borges (Barcelona, ES); Estefania Hernandez (Guadalajara, MX); Johann Aguayo (Guadalajara, MX); William Nicholas Garbarini, Jr. (Cranford, NJ); Alejandro Chavez-Badiola (Mexico City, MX); Alan Murray (Greenwich, CT); Jacques Cohen (New York, NY); Adolfo Flores-Saiffe Farias (Zapopan, MX)
Assignee: Conceivable Life Sciences Inc.
A61B17/43A61B17/425A61B34/30C12M21/06C12M23/10C12M23/48C12M23/50C12M33/04C12M41/06C12M41/18C12M41/48C12N5/0604G01N33/5091G01N35/0099G01N35/10G01N35/1011G06T7/20G06T7/70G06V10/82G06V20/693A61B34/32G06T2207/20081G06T2207/30024G06V20/69G06V20/698G06V2201/03
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Quick Facts
Patent No.
US 12,310,625
App. No.
18/431,259
Granted
May 27, 2025
Kind
B2
Abstract

A method for automated ICSI includes receiving at least one droplet containing an egg in a dish placed on a stage. The method includes using an artificial intelligence/machine learning system (AI/ML system) and an imaging system to detect a zona pellucida. The imaging system includes a microscopy system, a camera system, and a lighting system. The method includes holding the egg using a robotic microtool and lowering a robotic pipettor into the droplet. The method includes using the AI/ML system and imaging system to determine an area at which to hold the egg and positioning the robotic microtool to that area. The method includes using the AI/ML system and imaging system to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor. The method includes using the AI/ML system and imaging system to determine a target location where zona ablation should be performed.

Claims (34)

1. A method for automated, artificial-intelligence-based intracytoplasmic sperm injection (ICSI), the method comprising:

receiving a droplet containing an egg in a dish placed on a stage;

using an artificial intelligence/machine learning system (AI/ML system) and an imaging system to detect a zona pellucida, wherein the imaging system includes a microscopy system, a camera system, and a lighting system;

holding the egg using a robotic microtool;

lowering a robotic pipettor into the droplet;

using the AI/ML system and the imaging system to determine an area at which to hold the egg and positioning the robotic microtool to that area;

using the AI/ML system to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor;

using the AI/ML system and the imaging system to determine a target location where zona ablation should be performed;

moving the egg to the target location;

using the AI/ML system and the imaging system to assess a thickness of the zona pellucida and determine an ablation action;

generating a laser to produce the ablation action to ablate the zona pellucida at the target location, wherein a depth of the ablation action is based on the assessed thickness;

using the AI/ML system and the imaging system to define an injection path into the egg; and

injecting a sperm, along the injection path, into the egg.

2. The method of claim 1 wherein the stage is a microscope stage.

3. The method of claim 2 wherein the microscopy system includes an inverted microscope.

4. The method of claim 2 wherein the microscopy system includes a stereomicroscope.

5. The method of claim 2 wherein the microscopy system includes a movable microscope.

6. The method of claim 2 wherein the microscopy system includes an optical coherence tomography device.

7. The method of claim 2 wherein the microscopy system includes an optical coherence microscopy device.

8. The method of claim 2 wherein the microscopy system includes a lens-less microscope.

9. The method of claim 1 wherein the robotic microtool is a second robotic pipettor configured to hold the egg.

10. The method of claim 1 wherein:

the robotic pipettor includes a plurality of pipettes, and

lowering the robotic pipettor into the droplet includes lowering at least one of the plurality of pipettes into the droplet.

11. The method of claim 1 further comprising heating the dish.

12. The method of claim 1 wherein the imaging system produces at least one image having a mixed reality in which simulated imagery and real-life imagery are combined.

13. The method of claim 1 wherein the ablation action is produced at an intensity and radius needed to ablate an adequate portion of the zona pellucida to facilitate an entry of an ICSI needle through the zona pellucida without distorting the egg.

14. The method of claim 1 wherein injecting the sperm includes moving a needle forward into the egg along the injection path.

15. The method of claim 14 wherein moving the needle includes moving the needle at a controlled speed and stopping once the needle reaches an end point of the injection path.

16. The method of claim 14 wherein injecting the sperm includes using the AI/ML system to apply positive pressure in a needle to deposit the sperm in the egg.

17. The method of claim 16 further comprising using the AI/ML system and the imaging system to (i) confirm that the sperm is out of the needle and (ii) move the needle out of the egg.

18. The method of claim 1 further comprising using the AI/ML system and the imaging system to apply positive pressure in the robotic microtool until the egg is released into a droplet.

19. The method of claim 1 further comprising breaking a membrane of the egg using a set of piezoelectric pulses, wherein the AI/ML system is configured to determine a number of pulses in the set of piezoelectric pulses.

20. The method of claim 1 wherein using the AI/ML system and the imaging system to determine the target location is performed based on at least one of conventional microscopy, optical coherence tomography, optical coherence microscopy, or three-dimensional simulation of morphology of the egg.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 3, 2024
From: CHAVEZ-BADIOLA, ALEJANDRO; MURRAY, ALAN; COHEN, JACQUES; ABRAM, JOSHUA; MENDIZABAL-RUIZ, GERARDO; FLORES-SAIFFE FARIAS, ADOLFO; MILLAN, CESAR; VALENCIA-MURILLO, ROBERTO; OCEGUEDA HERNANDEZ, VLADIMIR C.; SILVESTRI, GIUSEPPE; COSTA-BORGES, NUNO; HERNANDEZ, ESTEFANIA; ALVAREZ, ANGEL; GREGORIO ESPINOZA FIGUEROA, JOSÉ; MANUEL RICO BOTERO, VICTOR; MANUEL MEDINA PEREZ, VICTOR; AGUAYO, JOHANN; GARBARINI, WILLIAM NICHOLAS, JR.; MARTÍNEZ, DAVID; PIZANO PARRA, ALEJANDRA; MURILLO, ANAIS LEROY; MAURICIO LÓPEZ GÓMEZ, CARLOS; ZAMARRIPA GONZALEZ, VALENTIN; ACOSTA GOMEZ, FATIMA J.; REYES LLAMAS, MARIO; KUKU, STEPHANIE
To: CONCEIVABLE LIFE SCIENCES INC.
Reel/Frame 068470/0904 →
Continuity (3)
Continuation PCTUS2024013428 · Jan 30, 2024
Provisional Application 63523258 · Jun 26, 2023
Related Publication 20240423673A1 · Dec 26, 2024
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