Biotechnology Engineer | Computational Bioprocesses & In-Silico Molecular Design
Founder & Chief Bioengineer at Elevate Biotech  •  Research Lead at Agromanper
Ambato, Ecuador 🇪🇨

Biotechnology Engineer graduated from Universidad Técnica de Ambato (UTA), specialized in bridging wet-lab bioprocess kinetics, molecular biophysics, and reproducible computational engineering.

Founder of Elevate Biotech, pioneering pre-clinical in-silico screening of bioregulatory peptides and cellular longevity molecules, coupled with industrial bioprocess scale-up pipelines (20 L pilot to 200 L industrial reactors).

• 🔬 In-Silico Peptide Discovery & ADMET: Biophysical property calculation (pI bisection, GRAVY, hydrophobic moment $\mu_H$), alanine scanning mutagenesis, 8 MEROPS protease cleavage profiling, semi-classical PBPK plasma $t_{1/2}$ modeling, and multi-omic API integration (UniProt, AlphaFold DB, ChEMBL).
• ⚙️ Bioprocess Engineering & Gray-Box PINNs: Physics-Informed Neural Networks (PyTorch) embedding coupled non-linear ODEs (dual Monod, Pirt, Luedeking-Piret, oxygen $k_L a$ transfer), non-linear ML ($R^2 > 0.99$), and pilot-to-industrial scale-up (20 L to 200 L).
• 📊 Telemetry & Automated GMP Reporting: Interactive SCADA telemetry dashboards (Streamlit / Plotly) and 300-DPI automated PDF technical dossiers with ReportLab Platypus.
• 🤖 Autonomous Multi-Agent Systems: Declarative CrewAI architectures for peer-reviewed scientific literature synthesis, publication-grade analytical plot generation, and academic networking.

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[ MOLECULAR & AGENTS ]               [ BIOPROCESS & ML ]              [ TELEMETRY & AUDIT ]
• bio-agent-skills                   • bioprocess-visual-twin         • bioreactor-dashboard
• insilico-peptide-toolkit           • bioprocess-digital-twin-pinn   • bioreactor-report-automation
• pep-admet-engine                   • fermentation-ml-predictor      
• biopython-sequence-pipeline        • simulacion-bioprocesos

Repository	Domain & Architecture	Mathematical / Computational Engine	Status
bio-agent-skills	AI Agent Skills CLI Suite for Bioengineering	In-silico peptide biophysics (Guruprasad instability, Boman index, Bjellqvist pKa), Contois/Haldane kinetics, Luedeking-Piret, scale-up & carbon balance
bioprocess-visual-twin	3D WebGL Bioreactor Twin & Batch Analytics Suite v2.1	Three.js WebGL (5 Vessels incl. Static), Multilanguage (EN/ES/DE), 8 Strains, Dedicated Results Dashboard, 4 Synchronized Charts, Stoichiometric Audit Table
insilico-peptide-toolkit	Pre-clinical peptide screening & design	Alanine scanning, $\Delta\Delta G$ heuristics, multi-protic net charge titration, UniProt/AlphaFold/ChEMBL connectors
pep-admet-engine	Proteolytic stability & in-silico ADMET	8 MEROPS proteases, $t_{1/2}$ PBPK clearance, Semaglutide/BPC-157/GHK-Cu benchmarks, Snakemake workflow
biopython-sequence-pipeline	Snakemake Workflow Catalog Pipeline	BioPython thermodynamics, RSCU codon bias, modular .smk rules, Conda isolation, dynamic HTML report
bioprocess-digital-twin-pinn	Physics-Informed Neural Network Digital Twin	Gray-box PyTorch PINN, 20 L aerobic reactor, Monod/Pirt/kLa ODEs, soft-sensor autograd ($R^2 > 0.997$)
fermentation-ml-predictor	Machine Learning for fermentation bioprocesses	Non-linear regression (Gradient Boosting, Random Forest, $R^2 > 0.90$) for $k_L a$, shear stress, Haldane kinetics
bioreactor-dashboard	Interactive SCADA bioreactor analytics	Streamlit + Plotly telemetry for dissolved oxygen, pH dynamics, temperature, and biomass curves
simulacion-bioprocesos	Bioprocess scale-up simulator	20 L pilot to 200 L industrial reactors under constant $P/V$, tip speed $v_{\text{tip}}$, Monod & Luedeking-Piret
bioreactor-report-automation	Automated kinetic auditing & technical dossiers	Automated calculation of $\mu_{\max}$, $t_d$, $Y_{X/S}$, $Y_{P/S}$, CPP auditing, and 300-DPI PDF generation

• Core Languages: Python 3.10+, JavaScript (ES6+), SQL, Bash / Shell, LaTeX / KaTeX.
• Deep Learning & PINNs: PyTorch (higher-order autograd, scientific PINNs, custom collocation loss functionals).
• Interactive Web & Graphics: HTML5 Canvas (60 FPS fluid rendering), Chart.js, Tailwind CSS, Streamlit, Plotly, ReportLab (Platypus).
• Biocomputing & Multi-Omics: BioPython, UniProt API, AlphaFold Database, ChEMBL REST, Ensembl REST, GTEx, Reactome.
• Pipelines & Workflows: Snakemake (Workflow Catalog standard, DSL2 paradigms, Conda env isolation, DAG reporting).
• Data Science & Machine Learning: Scikit-learn, NumPy, SciPy, Pandas, SymPy.
• Data Visualization & Telemetry: Matplotlib, Seaborn, Plotly, Streamlit, ReportLab (Platypus engine).
• Architecture & Agents: CrewAI (>=0.152.0), Pydantic, Hatchling, uv, GitHub Actions (CI/CD), Pytest.
• Standards & Reproducibility: Clean Architecture, PEP 517/621 packaging, offline caching fallback, deterministic unit test fixtures.

I actively welcome collaborations with academic laboratories, research consortia, and biotechnology enterprises across Ibero-America, North America, and Europe:

• CYTED (Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo): Salud y Biomedicina — Diseño in-silico y validación biofísica de péptidos bioactivos.
• NIH / Fogarty International Center: Computational pipelines for cost-effective therapeutic peptide optimization in low- and middle-income regions.
• Chevening Fellowships & UK Universities: Structural bioinformatics partnerships (Oxford, Imperial College, Dundee).

For collaborative inquiries, grant consortia, or wet-lab validation protocols (SPPS, RP-HPLC, CD spectroscopy, SPR affinity), please refer to RESEARCH_COLLABORATION.md or connect directly on LinkedIn.

Let's connect: linkedin.com/in/juanj-alva  •  Email: jjalvarezm77@gmail.com