Using simulation to optimize IVF lab resources and meet physiological time constraints

The challenge

Within the intricate ecosystem of an IVF laboratory, embryologists play a vital role in performing delicate tasks which aim to achieve successful fertilization and embryo development. However, with limited staff and workstations, a finite number of cryo spaces, bed spaces for up to six female patients at a time, and just two sperm production rooms available in the unit, the current manual approach to patient flow presents a range of challenges that impede the time efficiency and precision of the process.

Every stage, from egg collection to insemination, is time sensitive and can affect the final outcome, which is clinical pregnancies. At present, embryologists rely on microscopic observations and manual techniques to achieve fertilization, track development and cryopreserve of patients’ eggs and embryos.

Their work is complex and necessitates impeccable hand-eye coordination, extensive training and continued skills development. Furthermore, there is a heightened risk of burnout due to heavy workloads. Additionally, the human eye has limitations, which may hinder the accuracy required for consistent outcomes, especially if staff are under constant elevated pressure.

Strict time constraints permeate the landscape of an IVF laboratory. Procedures are meticulous to fit within the confines of regulatory guidelines. The inherent complexity of IVF procedures and the pressure to minimize time spent on each step create a delicate balancing act for an embryologist’s weekly workload.

For example, if eggs are collected from 10 patients on a Monday, a series of ten groups of micromanipulations and observations must run simultaneously or at very close intervals until the eggs fertilize. However, this process relies on staff availability and the equipment needed to carry out the work. Embryologists' ability to complete numerous tasks within limited timeframes is crucial to the success of an IVF cycle.

Furthermore, the absence of automation compounds the challenges embryologists face. While certain aspects, such as embryo culture, have witnessed automation advancements, a considerable portion of the workflow still relies on manual interventions. The lack of automation elevates the risk of human errors and introduces variability that can impact overall success rates.

The method

Laboratory staff identified that proactive planning and modeling would enable them to identify process timing deviations and test strategies before applying them.

As a result, under the supervision of fertility experts from Guy’s and St Thomas’, Simul8 were able to create a simulation of embryology laboratory processes. Simul8 used its expertise in other healthcare environments to design a simulation that delivered a dynamic understanding of the IVF laboratory.

The simulation needed to replicate every touchpoint in an ACU patient’s journey to deliver accurate results. Simul8 analyzed each stage of the process and developed specific features within the simulation to address the pain points highlighted by the team, including:

• Arrival Planner : The ACU operates on an appointment basis, meaning arrivals are known in advance. Simu8’s simulation uses the arrival planner to generate these patient arrivals to the clinic in a way that reflects how it would play out in real life and ensure enough resources are available to complete the required tasks.


• Routing by Label : The unit offers numerous fertility services; however, each follows a different pathway. Applying labels to patients and samples based on the required treatment ensures each work item follows the correct path and provides an overview of what’s going on in different areas of the clinic by separating the different pathways.


• Queue Start-Up and Capacity : The ACU uses cryogenic dewars - specialist flask containers - to store embryos, eggs and sperm at ultra low temperatures to preserve their properties and viability. To reflect this process within the simulation, Simul8 used ‘Queues’ to represent the dewars and the ‘Start-Up’ option to represent all samples within the dewars. Each dewar has limited space, so the ‘Capacity’ option was applied.


• Resource Moves with Work Item : Female patients entering the unit undergo an egg collection procedure which requires a bed space. The bed is released once an embryologist has spoken to the patient post-procedure. Simul8 applied the ‘Resource moves with work item’ feature to replicate this process within the simulation.

Next steps for Guy’s and St Thomas’ ACU

Utilizing retrospective data extracted from databases and the electronic witnessing system, the team can use the simulation to predict and test strategies such as staff availability and the impact their workload has on time-sensitive procedures. The data gathered from the simulation can be fed back to staff and stakeholders to identify areas for improvement.

Other critical themes the simulation aims to address include:

• How many embryologists are needed to run all tasks on time, and how does this impact rota planning?
• How many tasks aren’t completed on time with current staffing levels?
• Where are the bottlenecks and process traffic issues?
• How many procedures can be completed with the available staff and equipment within the desired timeframe?
• How many deviations from recommended process timings that are crucial to IVF are there?
• Test ‘what if’ scenarios to allow staff to plan proactively.

The benefits of simulation modeling in IVF

Projects such as this deliver multiple benefits to the NHS, staff and patients. Improved efficiency within an IVF laboratory means increased capacity, reduced waiting times and enhanced service quality and clinical outcomes.

Once the project is complete, Simul8 and the Guy’s and St Thomas’ NHS Foundation Trust hope the results will demonstrate why simulation modeling should be made available to fertility clinics nationwide.