Patient preparation
Make clinic-approved information easier to navigate before appointments and procedures, with clear references back to the source.
Before the appointmentResearch-informed AI for clinics
Clearer information. More connected care.
PrepAId develops AI-assisted systems for patient preparation, communication and clinic workflows, informed by scientific research.
Built around clinic knowledge. Designed for human oversight.
Reviewed knowledgeHuman understandingClinical oversight
01 / What we design
Good care needs
good connections.
A clinic’s knowledge is valuable only when people can find it, understand it and know what to do next. We build the systems around that journey.
Patient communication
Help people find answers to routine questions and recognise when a conversation with their care team is needed.
Between visitsClinic workflows
Give questions a clear route to the appropriate person, with the context needed to review and respond.
Behind every interactionDesigned for the workflow.
Adapted to the specialty.
Fertility
Preparation and questions across a complex treatment journey. The focus of our PREP-AID prototype.
Dental clinics
Opportunities to clarify appointment preparation, treatment information and routes back to the dental team.
Specialist care
A starting point for systems shaped by each clinic’s documents, people and responsibilities.
02 / How the connection works
The right information.
A clear route to a person.
We use AI to help patients navigate clinic-approved information and support question routing, with clear references, defined limits and human oversight.
Explore a patient question
Illustrative workflow. These examples explain the approach; they do not provide clinical advice.
Route / Information
“Where can I find my preparation instructions?”
Start with the clinic’s guide.
Find the matching approved document and show a reference the patient can open. Keep the answer within the information available.
Document referenceClinic preparation guide · relevant page
Route / Clear limit
“My question isn’t covered in the guide.”
Make the gap visible.
When approved sources do not support an answer, say so clearly and point the patient to their clinic’s contact route.
Source coverageNo supported answer found
Route / Human review
“I need to discuss a concern with my care team.”
Bring a person into the loop.
Route the question according to the clinic’s escalation process, retaining relevant context for staff review. The clinic defines responsibility and response timing.
Next stepClinic-defined review and response
03 / From principle to project
Development prototypeA project in fertility care
Preparation that stays
connected to the clinic.
An AI-assisted fertility-care prototype exploring how patients can navigate reviewed information before treatment, while keeping questions connected to the people responsible for care.
Explore the development notesThe prototype’s design
01
Clinic-approved documents
The starting point for patient information.
02
AI-assisted answers
Responses include references to source sections and pages.
03
A route back to staff
Questions can enter a human review workflow.
Development notes and evidence status
What is documented
The project handover describes source retrieval, citations, rule-based checks, AI-assisted routing and a staff escalation queue. These are prototype design features.
What still needs evaluation
Software testing alone cannot establish clinical effectiveness. Patient understanding, workflow fit, escalation reliability and real-world outcomes require evaluation in the intended care setting.
PREP-AID project documentation, 2025. Experimental educational support under development; clinical effectiveness has not been established.
04 / Research & responsibility
Trust needs
a method.
Healthcare technology earns trust through clarity, review and evidence from the setting where it will be used. These principles guide what we aim to build.
ResearchDesignEvaluation
Define the intended use
Agree on the task, the people it supports and the limits of automation.
Keep the source visible
Use reviewed information and make the basis of a response open to inspection.
Make oversight practical
Define who reviews a question, how it reaches them and what happens next.
Evaluate in context
Examine understanding, usability, risks and workflow impact with the intended users.
Research informing the approach
WHO / 2024
AI ethics & governance
Defined tasks, stakeholder involvement and explicit attention to risks.
NICE / Evidence standardsEvidence fit for purpose
A framework for planning and evaluating evidence for digital health technologies.
FUTURE-AI / BMJ 2025Trust across the lifecycle
Traceability, usability and robustness alongside fairness and explainability.
External research references. They do not imply endorsement, certification or demonstrated effectiveness of PrepAId systems.
05 / Our team
The people
behind PrepAId.
Our team brings together scientific and software development, reproductive medicine, human factors, and patient experience research.
Gayane Sedrakyan
Founder & Scientific/Technology LeadAI, Educational Technology & Human-Centred Intelligent Systems
Read bioClose bio — Gayane Sedrakyan
Dr. Gayane Sedrakyan is an Assistant Professor at the University of Twente and Scientific Lead of Living Models Lab and PrepAId, specializing in Educational Information Systems, human-centred AI, and intelligent technologies for healthcare and patient education.
Building on nearly two decades of research and software engineering experience, she initiated the HiCARE framework and founded PrepAId and PrepAId-IVF, translating research into safe, personalised patient education and guidance.
She is an Associate Editor of Frontiers in Digital Health (Health Informatics section) and a member of the Technology for Women’s Health group at the University of Twente. Her research explores safe zones for responsible AI adoption in clinical practice.
Gayane Arustamyan
Clinical Lead, Reproductive MedicineClinical expertise, patient safety & clinical validation
Read bioClose bio — Gayane Arustamyan
Gayane Arustamyan is a practicing obstetrician-gynecologist and reproductive medicine specialist with clinical expertise in assisted reproductive technologies (ART), in vitro fertilization (IVF), and fertility treatments. Her work focuses on reproductive healthcare, fertility management, and supporting patients throughout their fertility treatment journey.
Her clinical perspective contributes to the PrepAId research on safe AI-assisted patient education and support, particularly in identifying patient information needs, distinguishing routine educational questions from those requiring clinical judgement, and evaluating safe escalation pathways in fertility care.
Simone Borsci
Human Factors & Safety AdvisorHuman factors, usability & safe technology adoption
Read bioClose bio — Simone Borsci
Dr. Simone Borsci is an Associate Professor of Human Factors and Cognitive Ergonomics at the University of Twente, also affiliated with the UK’s National Institute for Health and Care Research (NIHR). He specializes in human–AI interaction, usability, user experience, and human-centred healthcare technology.
His expertise contributes to PrepAId research through the evaluation of patient–AI interactions, usability, trust, and the safe integration of AI-assisted patient education into clinical workflows, with particular attention to human factors, technology adoption, and patient safety.
Valeria Reséndez
Patient Experience ResearcherPatient-centred research & experience design
Read bioClose bio — Valeria Reséndez
Valeria Reséndez is a postdoctoral researcher at the University of Twente, specializing in human factors and the interaction between users and AI-driven technologies. Her research examines how people perceive, evaluate, and interact with AI systems, with a particular focus on trust, user needs, and technology acceptance.
Ahmed Almuhandes
Junior Product & Software Developer (Intern)Product development, integration & technical validation
Read bioClose bio — Ahmed Almuhandes
Ahmed Almuhandes is a Master’s student in Business Information Technology at the University of Twente, specialising in Enterprise Architecture and IT Management. With a Bachelor’s degree in Software Engineering, his expertise spans software development, digital transformation, and AI-driven information systems.
06 / For clinic leaders
Let’s make the
next step clearer.
A useful starting point is a question patients ask repeatedly, a preparation journey that causes confusion, or a handoff that needs clearer ownership.
Three questions to begin with
- Where do patients need more clarity?
- Which information does your team trust?
- What would a better workflow look like?