Innovation without evidence is only an idea. Every IVF 2.0 solution is developed, validated and continuously refined through scientific research, clinical collaboration and peer-reviewed publication. We don't ask you to trust our technology because we built it. We ask you to evaluate the evidence behind it.
22
publications & references
3
papers in the Nature group
6+
independent / third-party reviews
2020→2026
years of peer-reviewed work
Foundational and ongoing work by the IVF 2.0 team and collaborators.
Chavez-Badiola, Flores-Saiffe Farias, Mendizabal-Ruiz, Garcia-Sanchez, Drakeley, Garcia-Sandoval
Scientific Reports (Nature) 10:4394
The team's first algorithm — precursor to ERICA, published in the Nature group. Combines embryo morphometry and patient age across five classifiers to predict the pregnancy-test (β-hCG) result on 221 cases from two independent databases.
Read the paperChavez-Badiola, Flores-Saiffe-Farías, Mendizabal-Ruiz, Drakeley, Cohen
RBMO 41:585-593
The foundational ERICA paper. On 1,231 blastocyst images from three clinics, ERICA ranked a euploid embryo first in 78.9% of cases and among the top two in 94.7% — in under 25 seconds per case.
Read the paperChavez-Badiola, Zhang, Flores-Saiffe-Farías, Mendizabal-Ruiz, Drakeley, Olcha
Fertility & Sterility (ASRM 2020)
Explores the correlation between non-invasive chromosome screening (niPGT-A) and ERICA ranking — a step toward fully non-invasive embryo selection.
Chavez-Badiola, Flores-Saiffe, Mendizabal-Ruiz et al.
Fertility & Sterility (ASRM 2020)
Lays the computer-vision groundwork to automatically detect degraded blastocyst regions — functionality later integrated into ERICA.
Chavez-Badiola, Flores-Saiffe, Mendizabal-Ruiz, Drakeley, Cohen
Human Reproduction 36 (Suppl 1), deab130
Retrospective analysis of 599 transferred blastocysts: lower ERICA grade associated with higher probability of early miscarriage, independent of patient age.
Read the paperChavez-Badiola, Flores-Saiffe Farias, Mendizabal-Ruiz, Valencia, Drakeley, Cohen
Fertility & Sterility (ASRM 2021)
Explores whether the model should retrain dynamically per clinic protocol, reporting strong performance predicting ploidy status and selecting better-outcome embryos.
Read the paperIVF 2.0 team
Human Reproduction (ESHRE 2021)
A human–machine interaction study evaluating whether ERICA as an assistant accelerates the embryologist’s identification of euploid embryos.
Mendizabal-Ruiz, Chavez-Badiola, Aguilar Figueroa, Martinez Nuño, Flores-Saiffe Farías, Valencia-Murillo, Drakeley, Garcia-Sandoval, Cohen
RBMO 45:703-711
The foundational SiD paper. Analyzes 383 individual sperm across 78 ICSI cycles; SiD’s quantitative score (VSL, LIN, HMP) opens the door to real-time assistance in selecting the sperm to inject.
Read the paperFlores Saiffe Farías, Sakkas, Chavez-Badiola, Ocali, Mendizabal, Valencia, Valadez, Hernandez, Drakeley, Cohen
Fertility & Sterility (ASRM 2022)
Across 2,154 individual sperm analyzed by SiD, describes the association between operator-assessed morphology and objectively captured kinetic patterns.
Read the paperFlores-Saiffe Farias, Chavez-Badiola, Mendizabal-Ruiz, Valencia-Murillo, Cohen
Scientific Reports (Nature) 13
The blastocyst region-detection method behind ERICA — published again in the Nature group, reinforcing the technical validation of the commercial product.
Read the paperChavez-Badiola, Flores-Saiffe Farías, Mendizabal-Ruiz, Silvestri, Griffin, Valencia-Murillo, Drakeley, Cohen
RBMO
Using 94 features from a single static image, ERICA predicted first-trimester miscarriage risk with 67.4% accuracy — no biopsy or invasive technique required.
Read the paperMendizabal-Ruiz, Paredes, Álvarez López, Acosta-Gómez, Hernández-Morales, González-Sandoval, Mendez-Zavala, Borrayo, Chavez-Badiola
Archives of Medical Research 55(8):103131
Comprehensive review of the state of the art of AI across the whole reproductive cycle — oocyte, sperm and embryo.
Read the paperPalmer, Paredes, Drakeley, Chavez-Badiola, Woolley, Kaouri, Cohen
RBMO 50(3):104435
International cross-sectional survey of clinical embryologists measuring real-world knowledge, adoption and understanding of AI in IVF labs — key insight into the adoption gap.
Read the paperPalmer, Chavez-Badiola, Valencia-Murillo, Harvey, Mendizabal-Ruiz, Flores-Saiffe Farías, Paredes, Griffin
RBMO 51:104990
With 19 embryologists, both they and ERICA identified aneuploidy significantly better than chance; ERICA selected the correct euploid embryo on the first attempt more often (avg 1.73 vs 1.77 attempts).
Read the paperCohen, Silvestri, Paredes, Martin-Alcala, Chavez-Badiola, Alikani, Palmer
RBMO 50(4):104855
A rare self-critical review calling for stronger clinical validation and shared data frameworks — a commitment to scientific rigor over hype.
Read the paperThird-party reviews and studies that reference our systems.
Dimitriadis, Zaninovic, Chavez-Badiola, Bormann
RBMO
Independent team (Weill Cornell) confirms ERICA showed prediction significantly better (70% overall accuracy) than chance and than participating embryologists in the original study.
Read the paperSalih et al.
Human Reproduction Open
Independent systematic review of 20 studies concluding AI consistently outperformed human clinical teams; cites ERICA at 79% accuracy vs 71% and 63% for the two embryologists in the original study.
Read the paperF&S Reports
F&S Reports
Third-party study of ERICA vs iDAScore: senior embryologists tended to change their original decision "for the worse" less often after ERICA support.
Read the paperBiology (MDPI) 13(6):688
Biology (MDPI)
Third-party review reaffirming ERICA placed a euploid embryo among the top two in 94.7% of cases — used as a benchmark against iDAScore, MAIA and other commercial systems.
Read the paperAnnals of Biomedical Engineering
Annals of Biomedical Engineering
Positions ERICA among leading commercial embryo-scoring systems, noting it needs no time-lapse — only a single static image.
Read the paperJournal of IVF-Worldwide
Journal of IVF-Worldwide
Systematic review (2019–2025) reporting ERICA’s positive predictive value of 0.79 for euploidy, contrasted with iDAScore and DeepEmbryo.
Read the paperOfficial partner references.
Kitazato Corporation
Product page (JP/EN)
ERICA evaluates 100+ morphological embryo features undetectable by microscope alone; official technical sheet citing the RBMO / Human Reproduction papers as support.
Read the paperConnecting every step so research can study the full picture — responsibly, with the human in control.
Research collaborations and data-sharing frameworks are available on request.