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Explore original scientific papers, computational research, preprints, technical reports, books, and emerging discoveries from Alkhaleeli BioAI LLC.

Oklahoma City, Oklahoma · Computational Biotechnology

Alkhaleeli BioAI LLCAdvancing Biomedical Innovation

Through Artificial Intelligence, Bioinformatics, and Mathematical Science. An Oklahoma-based computational biotechnology company developing in-silico research frameworks, mRNA vaccine design concepts, diagnostic biosensor models, scientific software, and AI-assisted biomedical solutions.

In-silico research only. No wet-lab testing. No clinical claims. Educational, research, and computational development focus.

Framework Announcement

Rami Five-Checkpoint Framework

A mathematically rigorous, AI-guided computational pipeline for designing personalized mRNA vaccine candidates — built case by case for cancer patients.

Framework Overview

Personalized Cancer mRNA Vaccine Design

The R5CF is an in-silico software framework developed by Rami M. Alkhaleeli at Alkhaleeli BioAI LLC. It processes each patient's unique tumor genomic profile through five sequential mathematical checkpoints to computationally design a tailored mRNA vaccine candidate — from neoantigen identification all the way to manufacturing feasibility scoring.

What R5CF Covers

Case-by-case personalized mRNA vaccine design
Rami Five-Checkpoint Framework (R5CF)
AI-guided neoantigen identification
MHC-I & MHC-II epitope optimization
95%+ global HLA population coverage
Manufacturing feasibility scoring

Computational research only. All outputs are theoretical and require experimental validation. The R5CF is protected under USPTO Provisional Patent Application No. 63/936,055 (Rami M. Alkhaleeli, 2025).

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Advanced Vaccine Design
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About Us

Making Computational Biology More Transparent & Accessible

Alkhaleeli BioAI LLC is a biotechnology and AI research company founded in Oklahoma with a mission to make advanced computational biology more transparent, accessible, and useful for biomedical research, pharmaceutical development, diagnostics, and public-health innovation.

We focus on mathematical and AI-guided frameworks for evaluating biological targets, designing theoretical mRNA vaccine candidates, building diagnostic biosensor concepts, creating scientific software tools, producing research books, and supporting research organizations through computational analysis and technical consulting.

Reproducible computational logic
Transparent scoring systems
Literature-based analysis
Python & bioinformatics pipelines
Explainable AI models
Open scientific frameworks
mRNA Vaccine Design90%
Bioinformatics Analysis95%
AI-Guided Research88%
Diagnostic Modeling82%
Scientific Software85%
USPTO Filings

USPTO Patent Portfolio & Innovation Filings

Biotechnology • AI Diagnostics • mRNA Research • Biosensors • Energy Innovation

Rami M. Alkhaleeli's innovation portfolio includes one granted U.S. patent and multiple USPTO provisional patent applications across biomedical device design, AI-guided mRNA research, rapid immunoassay concepts, AI-designed biosensor platforms, and magneto-mechanical energy-harvesting technology.

Granted Patent

Method and apparatus for improving osseointegration, functional load, and related implant support

US Patent No.11,058,521
GrantedJuly 13, 2021
InventorRami Mohanad Mahdi Alkhaleeli

This granted U.S. patent relates to implant-support technology designed to improve osseointegration, functional loading, and mechanical stability around implant systems. It reflects early innovation work in biomedical device design and functional support engineering.

Provisional Filing

AI-guided personalized mRNA cancer vaccines with CRISPR-based antigen validation

Application No.63/936,055
Receipt DateOctober 30, 2025
InventorRami Mohaned Mahdi Alkhaleeli

This provisional filing describes a research-only AI-guided workflow for identifying cancer-associated targets, prioritizing possible mRNA vaccine candidates, and using CRISPR-based concepts for antigen-validation research. This is an early-stage computational and experimental concept, not a clinical treatment or approved vaccine.

Provisional Filing

Lateral Flow Immunoassay Apparatus for Rapid Detection and Quantification of Allergen-Specific IgE Antibodies

Application No.63/931,575
Receipt DateDecember 5, 2025
InventorRami Mohaned Mahdi Alkhaleeli

This provisional filing focuses on a rapid lateral-flow immunoassay concept for detecting and estimating allergen-specific IgE antibodies. The goal is to support fast, accessible allergy-related screening research using a portable test-format concept.

Provisional Filing

Artificial Intelligence Designed Synthetic Binding Protein Colorimetric Biosensor Platform for Rapid Diagnostic Detection and Classification of Gram Negative Bacteria, Gram Positive Bacteria, and Fungal Pathogens

Application No.64/004,904
Receipt DateMarch 13, 2026
InventorRami M. Alkhaleeli

This provisional filing describes an AI-designed biosensor platform using synthetic binding proteins and colorimetric detection concepts to identify and classify bacterial and fungal pathogens. The concept is intended for research and prototype development, not clinical diagnostic use unless validated and cleared by regulators.

Provisional Filing

The Five-Stage Magneto-Mechanical RF Harvester for Battery-Free Phones

Application No.64/017,342
Receipt DateMarch 26, 2026
InventorMr. Rami M. Alkhaleeli

This provisional filing presents an energy-harvesting concept combining magneto-mechanical motion and RF-related energy-capture ideas for battery-free or emergency power applications. It represents early-stage engineering research into alternative micro-power generation.

USPTO Receipts & Patent Records

Important Disclaimer: Some records shown are provisional patent applications and are not issued patents. Provisional applications are early-stage USPTO filings and do not by themselves represent granted patent rights. Medical, scientific, diagnostic, and therapeutic concepts shown here are research-only and are not FDA-cleared, clinically validated, or intended for diagnosis, treatment, cure, or clinical decision-making unless specifically approved through the appropriate regulatory process.

Alkhaleeli BioAI LLC presents this portfolio for informational, educational, and research-innovation purposes. All medical and biotechnology concepts require laboratory validation, safety testing, regulatory review, and appropriate approvals before any clinical or commercial use.

Our Services

Comprehensive Computational Biotechnology Services

From in-silico vaccine design to scientific software development, we provide end-to-end computational research services.

AI-Guided mRNA Vaccine Design

In-silico mRNA vaccine workflows including antigen selection, codon optimization, immunogenicity assessment, and manufacturability scoring.

Computational Biology & Bioinformatics

Sequence analysis, protein evaluation, antigen prioritization, epitope screening, and scientific interpretation using transparent workflows.

Scientific Software Development

Software and digital tools for sequence analysis, vaccine scoring, report generation, diagnostic modeling, and research automation.

Research Consulting Services

Expert consulting for biotech companies, pharmaceutical groups, academic researchers, and government-facing innovation programs.

Diagnostic Biosensor Concepts

Theoretical biosensor frameworks for pathogen detection, including AI-designed binding protein concepts for multiple pathogen classes.

Patents & Intellectual Property

Patentable concepts in computational biotechnology, AI-guided therapeutics, diagnostic platforms, software, and biomedical engineering.

Research Focus

Research Focus Areas

Our research spans multiple domains of computational biotechnology, from vaccine design to diagnostic innovation.

In-Silico mRNA Vaccine Design

Computational vaccine candidate evaluation using antigen selection, sequence optimization, RNA design logic, immunogenicity prediction, and manufacturability scoring.

Personalized Cancer Vaccine Concepts

Computational workflows for evaluating mutation-specific neoantigens and theoretical mRNA vaccine design strategies.

Viral and Bacterial Vaccine Research

In-silico prioritization of viral glycoproteins, bacterial surface proteins, and conserved antigenic targets.

Diagnostic Biosensor Design

AI-guided theoretical binding protein and colorimetric biosensor concepts for pathogen classification and rapid detection.

Pharmaceutical R&D Support

Mathematical and computational tools to support early research evaluation, documentation, and decision-making.

Scientific Software Engineering

Development of reproducible tools, apps, and PDF-generating platforms for biomedical research.

Books and Education

Educational materials explaining computational biology, AI biotechnology, mRNA design, and transparent research frameworks.

Patents and Innovation

Development of intellectual property in biotech, diagnostics, software, and biomedical engineering.

Scoring Framework
Rami Computational Framework (R10CF)
1
Target or antigen selection
2
Sequence quality assessment
3
RNA or protein structure evaluation
4
Immunogenicity or biological relevance prediction
5
Manufacturability and scalability review
6
Safety and specificity considerations
7
Evidence-weighting
8
Final integrated scoring
Methodology

Transparent Computational Frameworks

Alkhaleeli BioAI LLC develops transparent scoring frameworks for computational biotechnology. These frameworks are designed to convert complex biological features into explainable numerical checkpoints that can be reviewed, reproduced, and improved.

Each checkpoint in our framework represents a distinct biological or engineering consideration, scored using literature-derived evidence and computational logic — making every decision auditable and explainable.

"Our goal is to make computational biotechnology more transparent, reproducible, and explainable."

— Alkhaleeli BioAI LLC

SciNova Research Press

Featured Scientific Discoveries

SciNova Research Press showcases interdisciplinary research at the intersection of artificial intelligence, microbiology, immunology, vaccine design, computational biology, and drug discovery.

Vaccine and Immunoinformatics ResearchPreprintPreprintRestricted

Alkhaleeli, Rami (2026). In Silico Prioritization of a Hantavirus Glycoprotein-Derived Multi-Epitope mRNA Vaccine Candidate Using the Rami Five-Checkpoint Framework. [Preprint]. Zenodo. DOI: 10.5281/zenodo.20099929.

This preprint presents a purely in-silico computational study evaluating the Hantavirus CGRn8316 glycoprotein as a potential mRNA vaccine antigen. The Rami Five-Checkpoint Framework was applied to compare the full-length glycoprotein with a shorter trimmed multi-epitope construct, scoring antigen selection, sequence optimization, RNA design feasibility, epitope-like immunogenicity, and cost/scalability.

HantavirusmRNA vaccinein silico vaccine designcomputational vaccinology
34 views 8 downloads
Vaccine and Immunoinformatics ResearchPreprintPreprintOpen Access

Alkhaleeli, Rami (2026). mRNA Multi-Epitope Vaccine Design Against Zaire Ebolavirus. [Preprint]. Zenodo. DOI: 10.5281/zenodo.18133430.

This work presents the computational design of a multi-epitope mRNA vaccine candidate against Zaire ebolavirus using an immunoinformatics-driven approach. Conserved regions from the Ebola glycoprotein (GP), nucleoprotein (NP), and matrix protein VP40 were analyzed to identify high-affinity CD8+ and CD4+ T-cell epitopes.

Zaire ebolavirusEbola virusmRNA vaccineMulti-epitope vaccine
132 views 79 downloads
Books and Scientific MonographsBookOpen Access

Alkhaleeli, Rami et al. (2025). AI as Humanity's Second Immune System: A Comprehensive Guide to AI-Driven Vaccine Development and Precision Medicine. [Book]. Zenodo. DOI: 10.5281/zenodo.17577320.

This book presents a unified conceptual and computational framework that envisions Artificial Intelligence (AI) as an extension of humanity's adaptive immune system. Through advanced in-silico modeling, the work demonstrates how machine learning and bioinformatics pipelines can emulate immune recognition, predict antigenic targets, and generate mRNA-based vaccine and tolerance candidates.

AI medicinecomputational immunologymRNA vaccinebioinformatics
421 views 310 downloads
9
Total Publications
5
Research Categories
9
DOI-Registered Works
2
Open-Access Works

Counters are calculated live from verified publication records. No fabricated statistics.

Latest Research

View all
Vaccine and Immunoinformatics ResearchPreprintPreprintRestricted

Alkhaleeli, Rami (2026). In Silico Prioritization of a Hantavirus Glycoprotein-Derived Multi-Epitope mRNA Vaccine Candidate Using the Rami Five-Checkpoint Framework. [Preprint]. Zenodo. DOI: 10.5281/zenodo.20099929.

This preprint presents a purely in-silico computational study evaluating the Hantavirus CGRn8316 glycoprotein as a potential mRNA vaccine antigen. The Rami Five-Checkpoint Framework was applied to compare the full-length glycoprotein with a shorter trimmed multi-epitope construct, scoring antigen selection, sequence optimization, RNA design feasibility, epitope-like immunogenicity, and cost/scalability.

HantavirusmRNA vaccinein silico vaccine designcomputational vaccinology
34 views 8 downloads
Vaccine and Immunoinformatics ResearchPreprintPreprintOpen Access

Alkhaleeli, Rami (2026). mRNA Multi-Epitope Vaccine Design Against Zaire Ebolavirus. [Preprint]. Zenodo. DOI: 10.5281/zenodo.18133430.

This work presents the computational design of a multi-epitope mRNA vaccine candidate against Zaire ebolavirus using an immunoinformatics-driven approach. Conserved regions from the Ebola glycoprotein (GP), nucleoprotein (NP), and matrix protein VP40 were analyzed to identify high-affinity CD8+ and CD4+ T-cell epitopes.

Zaire ebolavirusEbola virusmRNA vaccineMulti-epitope vaccine
132 views 79 downloads
Vaccine and Immunoinformatics ResearchPreprintPreprintRestricted

Alkhaleeli, Rami (2026). Personalized mRNA Vaccines Encoding Patient-Derived HIV-1 Envelope Trimers: An In Silico Proof-of-Concept Study in Multidrug-Resistant HIV Infection. [Preprint]. Zenodo. DOI: 10.5281/zenodo.18112582.

This study develops and evaluates a computational pipeline for designing fully personalized mRNA vaccines for individuals with multidrug-resistant HIV-1 infection. Patient-specific viral envelope (Env) sequences are reconstructed, optimized, and encoded into individualized mRNA constructs formulated in lipid nanoparticles.

HIV-1multidrug-resistant HIVpersonalized medicinemRNA vaccine
81 views 46 downloads
Drug DiscoveryPreprintPreprintRestricted

Alkhaleeli, Rami (2025). A Two-Phase Peripheral Drug Sequestration Strategy Using Protein Binders and Transient mRNA Expression to Reduce CNS Exposure to Fentanyl. [Preprint]. Zenodo. DOI: 10.5281/zenodo.18041349.

The ongoing opioid crisis continues to result in unacceptable overdose mortality. This work presents a conceptual two-phase peripheral drug sequestration framework designed to reduce central nervous system (CNS) exposure to fentanyl without interfering with opioid receptor signaling, based on engineered fentanyl-binding proteins.

Addiction harm reductionfentanylperipheral drug sequestrationprotein binders
59 views 32 downloads
Computational ResearchScientific PaperRestricted

Alkhaleeli, Rami (2025). Harvesting Ambient Radio Waves for Battery-Free Wireless Sensors Using Mechanical Resonance and Acoustic Amplification. [Scientific Paper]. Zenodo. DOI: 10.5281/zenodo.18012003.

Ambient radio-frequency (RF) energy from broadcast transmitters represents a continuously available but extremely low-density power source. This work presents a conceptual and buildable system for harvesting ambient AM radio waves to power battery-free wireless sensors through a hybrid electromagnetic–mechanical energy conversion chain.

Ambient radio-frequency energy harvestingBattery-free wireless sensorsRF energy harvestingMechanical resonance
44 views 5 downloads
Drug DiscoveryPreprintPreprintRestricted

Alkhaleeli, Rami (2025). A Biofilm-First Wound Microenvironment Control Strategy Using an In-Situ Forming MgO-Embedded Hydrogel. [Preprint]. Zenodo. DOI: 10.5281/zenodo.17934896.

Chronic wounds frequently fail to heal due to persistent biofilm formation. This work presents a novel wound microenvironment control approach based on an in-situ forming hydrogel embedded with magnesium oxide (MgO) nanoparticles, designed to impose sustained physicochemical stress on biofilms while maintaining wound conformity and exudate management.

Chronic woundsBiofilm disruptionWound microenvironmentIn-situ forming hydrogel
85 views 82 downloads
Meet the Researcher

Rami M. Alkhaleeli

Founder of Alkhaleeli BioAI LLC and the researcher behind every SciNova publication. His work spans AI-driven vaccine design, computational immunology, mRNA therapeutics, microbiology, and translational biomedical engineering — developed through transparent, reproducible in-silico methods and verified through Zenodo and DOI registration.

ORCID: 0009-0004-0210-9015

Where Scientific Ideas Become Discoverable Knowledge

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A free educational course introducing the fundamentals of in-silico vaccine design, bioinformatics workflows, and computational biology research methods. Perfect for students and researchers exploring the field.

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Alkhaleeli BioAI LLC
Computational Biotechnology & AI Research

An Oklahoma-based computational biotechnology company advancing biomedical innovation through artificial intelligence, bioinformatics, and mathematical science.

Oklahoma City, Oklahoma, USA

Legal

In-silico research only. No wet-lab, animal, or human testing. Educational and computational focus.

Important Disclaimer

Alkhaleeli BioAI LLC provides computational, educational, and research-oriented services only. All vaccine, therapeutic, protein, biosensor, and biomedical concepts described on this website are in-silico models and theoretical frameworks. They are not medical products, are not intended for clinical use, and have not been validated through wet-lab, animal, or human testing. Nothing on this website should be interpreted as medical advice, clinical guidance, regulatory approval, or a claim of safety or efficacy.

Alkhaleeli BioAI LLC provides educational, research-focused, publishing-support, and digital content tools. Content and AI tools are not medical, legal, financial, regulatory, or clinical advice. All submitted content is subject to review before publication. Alkhaleeli BioAI LLC reserves the right to reject, remove, refund, or suspend any content that violates safety, legality, copyright, originality, or professional standards.

© 2026 Alkhaleeli BioAI LLC. All rights reserved. Research Publishing & Royalty Platform.