Research Experience

Research Scientist | Molecular Biology | miRNA | EVs | Data Analysis | Translacional Medicine (2020-2025)

Research Scientist | NGS Library Preparation | Bioinformatics (2024-2025)

• Prepared and validated small RNA NGS libraries (98% first-pass success; Bioanalyzer/Qubit QC), ensuring data robustness for translational research.

• Generated transcriptomic datasets from ARPE-19 cells and extracellular vesicles (small RNA & lncRNA) to explore diabetes-driven molecular mechanisms.

• Executed end-to-end RNA-seq analysis using R/DESeq2, ensuring reproducible QC (PCA, heatmaps) and statistically robust FDR-adjusted outputs.

• Translated differential expression results (log₂FC/FDR) into clear, analysis-ready tables (CSV/Excel) to support downstream interpretation and discussion.

• Applied FDR-based prioritization to identify biologically and clinically relevant gene and miRNA candidates for validation.

• Performed KEGG and GO pathway enrichment to elucidate key mechanisms in diabetic retinopathy, including angiogenesis, oxidative stress and inflammatory signaling.

• Integrated transcriptomic findings with in vitro hyperglycemia models to support mechanistic understanding of diabetes-related retinal dysfunction.

• Generated intuitive visual outputs (volcano plots, MA plots, PCA, heatmaps) to facilitate scientific communication with cross-functional stakeholders.

Pharmaceutical Industry | Oriented to Genetic Diagnosis (2024)

• Completed a Pharma Transition Program focused on Genetic Diagnostics and Clinical Reporting, strengthening my understanding of the pharma ecosystem and scientific–clinical communication.

• Completed 100+ hours of specialized pharma industry training with exposure to Medical Affairs workflows.

• Developed a translational mindset, connecting molecular data (genetics/RNA-seq) with clinical relevance and unmet medical needs.

• Maintained up-to-date knowledge of genetics, RNA-seq and precision medicine trends relevant to clinical development.

• Built strong professional relationships with genetics, clinical and healthcare experts.

• Strengthened core MSL skills — scientific communication, clarity, organization and data-driven insight.

In vitro (2020-2022)

In vivo (2023)

Translacional Medicine (2025)

• Organized master and working cell banks with cryopreservation at −150 °C and defined passage limits, reducing phenotypic drift by approximately 30%.

• Established a protocol for choroid extraction and ex vivo culture in Matrigel, maintaining tissue viability for up to 7 days and generating an SOP with defined acceptance criteria.

• Standardized a hyperglycemia model in ARPE-19 cells (120 h) with strict operational controls (culture medium, confluence, timing) and reproducible molecular endpoints (e.g., HIF-1α and VEGFA).

• Identified the reference miRNA using NormFinder, with cross-validation using geNorm and BestKeeper, improving normalization stability in miRNA analyses.

• Implemented preamplification in samples with no detectable signal, with optimized cycle numbers and bias control, enabling reliable detection of low-abundance targets in liquid tissue samples.

• Recovered previously undetectable targets through controlled preamplification, ensuring assay efficiency between 90–110% and R² ≥ 0.99 after re-validation.

• Consolidated a clean, fully traceable dataset (Cq, ΔCt, flags, outliers) suitable for differential expression analysis and clinical correlation studies.

• Coordinated and executed in vivo studies (dose selection, stratified randomization, blinding) under ethical approval and 3Rs compliance, with GxP-aligned reporting.

• Performed intravitreal miRNA injections in BALB/c mice in a diabetic retinopathy model (>95% success, <5% complications) and established sustained hyperglycemia (>250 mg/dL) with weekly monitoring and 0% mortality.

• Implemented sample size calculation, randomization, and blinding, reducing experimental bias and repetition by ~20%.

• Managed experimental timelines with veterinarians and animal facility staff, aligning procedures with OR availability and biosafety requirements over a 2-year period.

• Rapidly isolated mouse retinas (<5 min post-enucleation) following validated SOPs to preserve tissue integrity for downstream analyses.

• Monitored and documented animal welfare using clinical scoring and predefined analgesia criteria, ensuring full 3Rs compliance.

• Coordinated informed consent for 120 patients in compliance with GDPR/LOPDGDD and principal investigator (PI) requirements, achieving an adherence rate of ~85% with zero ethical incidents.

• Designed and explained patient information sheets using clear, non-technical language

• Ensured full pseudonymization (alphanumeric coding ↔ secure linkage table) with restricted access, resulting in “privacy findings: none” during review.

• Standardized minimum sample volume and collection tube type (EDTA/serum) per biomarker across 120 samples.

• Controlled preanalytical variables (hemolysis, timing, sample handling) and increased miRNA signal detection by ~25%.

• Collected and consolidated clinical variables (glucose, HbA1c, lipid profile, concomitant medication, lifestyle factors) from medical records and laboratory data.

• Built relational patient and visit/sample tables (keys: patient_id, visit_date, sample_id) linked to miR-205-5p expression data, ready for statistical analysis and machine learning workflows.

• Generated curated clinical summaries (glucose, HbA1c, TG/HDL, active medications) in analysis-ready tables for statistics and clinical dashboards