O-236 Automating day 0 in the IVF laboratory: clinical validation of a three-stage workflow resulting in first pregnancies

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Abstract Study question Can an automated three-stage IVF workflow, under embryologist supervision, reliably perform sperm preparation, oocyte processing, and ICSI to achieve clinical pregnancies? Summary answer First clinical pregnancies were achieved using a three-stage automated Day 0 IVF workflow, with fertilization and blastocyst rates matching manual controls. What is known already The growing demand for fertility treatments is constrained by a global shortage of skilled embryologists and the inherent variability of manual laboratory procedures. While automation has revolutionised industries like diagnostics and pharmaceutical production by improving standardisation, reducing human error, and increasing throughput, IVF laboratories remain largely manual. Day 0 procedures, including sperm preparation, oocyte handling, and ICSI, rely heavily on embryologist expertise and precision. Despite the known benefits of automation in reducing variability and workload, to the best of our knowledge, no fully integrated system has yet been clinically validated for automating these critical steps while maintaining embryologist oversight. Study design, size, duration This proof-of-concept study reports on three patients allocated to an automated Day 0 IVF workflow, following prior validation of individual automated stations for sperm preparation, oocyte handling, and ICSI. These cases mark the culmination of a 6-month pilot program, progressively validating individual and combined stations across 42 patients. Participants/materials, setting, methods Eligible participants (18-39 years) undergoing IVF/ICSI were enrolled after providing informed consent. Exclusion criteria included uterine pathology, severe male infertility (e.g., azoospermia), or genetic conditions. In this single-centre pilot study, sibling oocytes were randomly assigned to automated or manual processing, adhering to standard IVF protocols. The three-stage automation included: (1) centrifuge-free sperm capacitation, (2) automated COC identification and denudation, and (3) AI-assisted sperm selection with laser-guided piezo-ICSI. Main results and the role of chance A three-stage automated IVF workflow was evaluated in three patients (average age: 29.7 years), all using autologous eggs, with one using donor sperm. The system successfully performed sperm preparation, oocyte processing, and ICSI, leading to pregnancies in all cases. For Patient 1, automation achieved 80% fertilisation (4/5) and 75% blastocyst formation (3/4). One embryo was transferred, resulting in an ongoing pregnancy. The control had 100% fertilisation (6/6) and 67% blastocyst formation (4/6). For Patient 2, automation yielded 43% fertilisation (3/7) and 33% blastocyst formation (1/3). One embryo was transferred, leading to an ongoing pregnancy. The control achieved 60% fertilisation (6/10) and 33% blastocyst formation (2/6). For Patient 3, automation resulted in 100% fertilisation (2/2) and 50% blastocyst formation (1/2). A euploid embryo was transferred, leading to an ongoing pregnancy. Embryo selection was based on Gartner grading with AI assistance (ERICA). In all cases, the top-ranked embryos were from the automated system and prioritised for transfer. The system demonstrated fertilisation and blastocyst rates comparable to manual processes, achieving pregnancies in all cases. However, given the small sample size (three patients), the role of chance cannot be excluded, and further studies are needed to confirm reproducibility. Limitations, reasons for caution This first demonstration of fully automated Day 0 IVF achieved clinical pregnancies in a limited cohort of three patients. The prototype still requires embryologists' supervision and manual sample handling between stations. A larger study on a new system is underway to confirm reproducibility and improved throughput. Wider implications of the findings Achieving pregnancies with a fully automated Day 0 workflow demonstrates the feasibility of standardizing complex IVF procedures while reducing operator dependence and potentially improving cost-effectiveness. Further optimization of this technology could expand access to fertility treatment and enhance laboratory efficiency. Trial registration number Yes

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