In Assisted Reproduction the greatest challenge is to determine which embryo has the potential to achieve pregnancy.
What we do
The objective of Embryoxite is to offer a personalized diagnosis of each embryo according to its metabolome and the integration of clinical, genetic and embryo growth kinetic data (timelapse) in an artificial intelligence (AI) system.
Embryoxite proposes a new system to diagnose, classify and select embryos that is based on different layers of information obtained from the most important aspects of embryo development.
With all the gathered information, we are developing AI algorithms with the aim of providing an implantation prediction score, which the professional will use to make a decision prior to embryo transfer.
WE DISCOVERED A NEW WAY OF TAKING ADVANTAGE OF THE LARGE VOLUME OF DATA THAT CAN BE OBTAINED BEFORE AND DURING THE PROCESS OF EMBRYO DEVELOPMENT, AND USE ADVANCED ARTIFICIAL INTELLIGENCE TOOLS TO PROCESS IT.
In recent decades, governments and non-profit organizations have made efforts to implement more equitable policies for people with infertility problems, same-sex couples, those who need surrogacy, genetic and/or hereditary chromosomal diseases, little access to social coverage or simply those who wish to postpone their maternity/paternity for a planned family future.
Based on the historical analysis of the sector and the increasing demand; its seems imperative the need for an increment on the reproductive success rates reducing the number of pregnancy failures.
CEO / INDUSTRIAL ENGINEERING
Iván Anduaga Marchetti
COO / EMBRYOLOGIST
CTO / MEDICAL PHYSICS ENGINEER
Paula Sacur Silvestre
CSO / EMBRYOLOGIST
CIO / BIOENGINEER