We develop personalized, AI-guided cancer vaccine blueprints — designed for each unique case and created solely for educational and research visualization purposes.

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Empowering Medicine with Artificial Intelligence

AI + Python + mRNA Innovation

Python-driven engine analyzes genomic, proteomic, and structural data.
AI identifies the safest, strongest antigen targets for each disease.
Automated mRNA construct design with codon optimization and stability modeling.
In-silico safety screening, immune simulation, and risk prediction.
Expert review ensures scientific accuracy and translational value.

At Alkhaleeli BioAI LLC, Python is the core engine that powers our AI-driven mRNA design platform. Python scripts collect and clean genomic, proteomic, and structural data, then run machine-learning models to identify the best antigen targets for cancer, multidrug-resistant bacteria, brain-eating amoeba, and allergic disease. The system automatically converts these targets into optimized mRNA constructs, simulates immune responses, checks off-target risk, and generates clear reports. Python connects all external sources—scientific databases, structural models, and cloud compute—into one reproducible workflow, while human experts review every design before it is advanced to experimental or clinical partners.

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founder, Alkhaleeli BioAI LLC
AI-Driven Biomedical Researcher | Vaccine Blueprint Designer | Future Physician-Scientist

Rami Alkhaleeli is a biomedical innovator using artificial intelligence to imagine the next generation of personalized immunotherapies. His work focuses on AI-guided mRNA vaccine blueprints, neoantigen discovery, and computational immune engineering, all designed to inspire the scientific community and advance educational exploration of future medicine.

He is the creator of one of the most unique independent research pipelines in the U.S.—transforming DNA, protein structures, and immunological principles into in-silico vaccine designs and AI-generated immune models, archived openly on Zenodo for global access.

With a deep belief that knowledge should elevate humanity, Rami publishes his work freely to support students, researchers, and future clinicians.

🔬 About My Work

Rami’s research centers on one core mission:

“Can AI help the immune system learn faster than disease can spread?”

To answer this, he developed a full computational platform that can:

Analyze DNA and protein sequences
Predict T-cell and B-cell epitopes
Design mRNA vaccine blueprints against cancer and pathogens
Model immune behavior and antigen recognition
Simulate adoptive T-cell training concepts

All designs are conceptual and educational models, demonstrating how AI could support personalized medicine in the future.

His published Zenodo work includes:

AI-guided cancer neoantigen vaccine models
mRNA constructs for antibiotic-resistant pathogens
CRISPR-assisted antigen validation frameworks
Computational models for ex vivo immune reprogramming
and advanced simulations for synthetic drug neutralization pathways

Rami’s long-term goal is to merge AI with clinical immune engineering after medical school—building a pipeline where data teaches immunity, and immunity heals humanity.

How It Works

1. Contact & Project Setup

Email ralkhaleeli@outlook.com with your research goal.
You’ll receive:

A short project form
A quote
An educational-use waiver
Option to request same-day delivery

Setup usually takes minutes, not hours.

2. Send Your Digital Sequence Data

Submit your FASTA-style file via:

Email attachment
Or physical USB/DVD (optional)

Supported datasets include:

Normal vs cancer DNA (same patient; de-identified)
Bacterial, fungal, or viral genomes
Multi-resistant isolates
Reference genomes
Synthetic or experimental sequences

Only include the sequence — no personal data.

🤖 3. AI Analysis & mRNA Blueprint Simulation

Your FASTA file enters a specialized AI pipeline built for educational visualization:

🔍 Feature Extraction

AI identifies mutations, conserved regions, antigenic hotspots, and structural clues.

🧬 Immune Target Prediction

Models simulate:

Epitope prediction
MHC I/II binding likelihood
Structural hints (AlphaFold-style)
Rank scoring of immunogenic sites

📘 mRNA Blueprint Simulation

AI generates a visual, non-functional mRNA design for demonstration:

Codon-optimized sequence mockup
Sample 5' & 3' UTR structure
Theoretical antigen expression
Clean diagrams and annotations

Nothing biological is created — only educational simulations.

⏱ Same-Day Delivery

Standard: ~1 week
Fast Track: Same-Day Results

📦 4. Delivery & Payment

You receive:
✔️ A polished digital PDF report
✔️ Sequence summaries
✔️ Simulated mRNA blueprint diagrams
✔️ Immune prediction maps
✔️ AI-generated insights

Delivered securely through email.

Payment is completed through PayPal only after results are confirmed.

Optional: secure data storage for future model updates.