Jose Antonio Esquivel Gaytan
MD, MSc, PhD—thesis submitted (2025)
Physician-scientist | Translational cardiometabolism | AI workflows (prototyping-level) | MDR/GDPR aware
Professional Profile
Physician-scientist (MD, MSc, PhD—thesis submitted Oct 2025) focused on cardiometabolic translational research and responsible, usable AI in healthcare. I prototype workflow-level AI tools with engineers and help clinical teams evaluate safety, utility, and ethics (MDR/GDPR aware). Clear communicator between clinicians, data scientists, and product teams.
QGuard-Med (v2.4): Finalist at Break The Gap 2025. AI-driven patient prioritization with MVP in FastAPI + Next.js.
HTS/OPLAH Discovery: Built high-throughput assay strategy (Z', S/B); identified AMP as OPLAH enhancer (EHJ abstract, 2023).
AI Literacy & Guardrails: Design responsible AI workflows; MDR/GDPR awareness integrated into early design phases.
Open to: clinic co-founding, adjunct teaching, and AI literacy workshops (Netherlands/Spain/EU).
Professional Experience
PhD Researcher — Experimental Cardiology
University Medical Center Groningen (UMCG), Netherlands
Built high-throughput assay strategy (Z', S/B robustness metrics) to explore OPLAH modulation; identified AMP as enhancer (conference abstract, EHJ 2023).
Led cross-functional collaborations with clinicians and data scientists; LLM-assisted documentation to accelerate figures, supplementary info, and code notes for peer-reviewed and open-access outputs.
Clinical Research Investigator & AI PM
PECTUS Respiratory Health (PANGAEA) · Girona/Barcelona, Spain
Bridged clinical and development across three healthcare-AI projects; framed product requirements and safety guardrails.
Prototyped LLM workflows: prompt libraries, model selection (ChatGPT/Claude/Gemini, Mistral/DeepSeek via API), integration testing for responsible AI (bias, explainability, privacy-by-design, MDR awareness).
Co-developer — QGuard-Med (v2.4)
Groningen / Barcelona
Finalist at Break The Gap 2025 (AI for Health & Sport Summit).
Clinical ↔ dev bridge: framed use case, validated requirements, tested MVP with simulated scenarios on historical data. Tech: FastAPI backend, Next.js frontend, LLM orchestration for patient prioritization (time, trend, severity, biomarkers).
Selected Projects
QGuard-Med (v2.4)
AI patient prioritization
Role: Co-developer (clinical ↔ dev bridge). Outcome: MVP with FastAPI + Next.js; simulated scenarios on historical data; pilot planning underway.
MiPrEP
Adherence companion (concept/MVP)
Role: Clinical product framing, privacy model, feature spec. Outcome: Low-fidelity prototype tested with users; validated core assumptions on engagement and trust.
ProtoBot AI
Dual-knowledge approach (concept)
Role: Problem framing, safety guardrails, validation plan. Outcome: Concept validated with clinical stakeholders; pathway to pilot study defined.
Core Competencies
Leadership
Project Management
Team Leadership
Clinical-Tech Translation
Scientific Writing
Translational & Clinical
Translational Medicine
Biomarker Analysis
Assay/HTS Literacy
AI & Data
Prompt Engineering
Model/Tool Selection
LLM-assisted Prototyping
Programming (prototyping-level)
Python (FastAPI basics)
MVP, read/modify, pair with senior engineer
JS/TS (Next.js/React basics)
Frontend prototypes, feature branches
Docker · Git · LLM toolchain
Daily use, workflow integration
Education
PhD in Biomedical/Medical Sciences
University of Groningen (UMCG)
Experimental Cardiology with focus on biomarker discovery, high-throughput screening strategies, and nanoparticle concepts for heart failure research.
MSc Nanotechnology & Regenerative Medicine (Distinction)
University College London (UCL)
Honors: Awarded with Distinction. Project: Photochemical Internalisation for Pancreatic Cancer Treatment.
MD (Physician)
Universidad Nacional Autonoma de Mexico (UNAM)
Medical degree with clinical training in internal medicine and translational research foundations.
Publications
404-error 'Disease not found': Unleashing the translational potential of omics approaches beyond traditional disease classification
European Journal of Heart Failure
Integrates omics to challenge classical HF classification and reveal novel mechanisms. Co-authored with cross-functional research team.
A high-throughput screening strategy identifies adenosine 5-monophosphate as a novel enhancer of the cardio-protective enzyme 5-oxoprolinase (OPLAH)
European Heart Journal, 44(Suppl_2), ehad655.3130
Novel biomarker discovery via HTS. Presented at ESC Congress. Demonstrates OPLAH modulation pathway with potential cardioprotective implications.
Languages
Spanish
Native Proficiency
English
C1 Proficiency
Dutch
B1–B2 (actively studying)
French & Catalan
A2 / A1 Proficiency
Certifications & Credentials
Good Clinical Practice
Article 9 — Animal Experiments License
ML-1 Laboratory Certificate
Elements of AI
Personal Interests
CrossFit
Fitness and strength training
Artificial Intelligence
LLMs, AI workflows, and innovation
Travel
Exploring cultures and perspectives
Animal Welfare
Responsible and ethical practices
Professional Interests & Development
AI Literacy in Healthcare
Designing and piloting workshops on safe LLM use, bias mitigation, validation, and MDR/GDPR awareness for clinical teams. Formats: 2–4h modules tailored to care environments.
Outpatient Clinic (Cardiometabolic Prevention)
Interested in preventive cardio practice integrating lifestyle counseling, biomarker stratification, and AI-assisted risk assessment with explainable, ethical tools.
Academic Teaching
Translational methods, biomarker-to-bedside design, clinical AI case studies, and ethics in healthcare innovation.