AI-Native Research

SpA Research
AI Laboratory

A patient-led computational research laboratory dedicated to advancing the understanding and treatment of Spondyloarthritis through artificial intelligence.

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SpA
AI
Data
Genes
HLA-B27
Microbiome
Biomarkers
About

AI-Native Science,
Patient-Led Mission

SpA Research AI Laboratory is an independent computational research institute founded on the belief that artificial intelligence can fundamentally transform how we understand complex inflammatory diseases like Spondyloarthritis.

As a patient-led initiative, we combine lived experience with rigorous computational methods — using AI agents for literature synthesis, machine learning for biomarker discovery, and open science principles to make our findings accessible to all.

Our approach is fully AI-native: every stage of the research pipeline — from hypothesis generation through data analysis to manuscript preparation — is augmented by artificial intelligence, allowing a small team to operate at the scale of a much larger institution.

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Computational Biology

Multi-omics integration, biomarker discovery, and pathway analysis using publicly available datasets.

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AI-Augmented Research

AI agents for literature synthesis, hypothesis generation, and accelerated scientific workflows.

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Open Science

All computational pipelines and datasets published openly. Science belongs to everyone.

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Patient-Led

Founded by a patient-researcher. Questions are driven by what matters to those living with SpA.

Research

Active Projects

Our research focuses on the molecular and computational dimensions of Spondyloarthritis, with an emphasis on actionable, clinically relevant findings.

● Active

Diagnostic Biomarker Panel for Early SpA

Multi-omics integration of publicly available gene expression and GWAS datasets to identify a robust, replicable diagnostic signature for early Spondyloarthritis.

Transcriptomics GWAS Machine Learning
○ Planning

Microbiome–SpA Axis: Computational Analysis

Systematic review and meta-analysis of gut microbiome alterations in SpA patients, followed by mechanistic pathway modeling using available metagenomic datasets.

Microbiome Metagenomics Pathway Analysis
○ Planning

Drug Repurposing in SpA

AI-assisted screening of existing approved compounds against SpA molecular targets, prioritising candidates with strong mechanistic rationale and favourable safety profiles.

Drug Repurposing Network Pharmacology AI Screening

We are actively seeking collaborators. If you are a rheumatologist, computational biologist, or SpA patient interested in contributing, please get in touch.

Methodology

How We Work

Our AI-native research pipeline allows rigorous, reproducible science with a lean team.

01

Hypothesis Generation

AI-assisted literature synthesis across thousands of papers to identify gaps and generate testable hypotheses.

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02

Data Integration

Curation and integration of public multi-omics datasets (GEO, UK Biobank, GWAS Catalog, microbiome databases).

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03

Computational Modelling

Machine learning, network analysis, and statistical modelling to test hypotheses and identify patterns.

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04

Publication & Open Release

AI-assisted manuscript preparation, peer review submission, and open-source release of all pipelines.

Team

Who We Are

Pawel Kuklik

Pawel Kuklik, PhD

Founder & Principal Investigator

Cardiac electrophysiology researcher and app developer with expertise in data analysis and computational modelling. SpA patient and advocate. Driving the AI-native research vision of the laboratory.

Website ORCID
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Open Position

Rheumatologist Co-Investigator

We are looking for a rheumatology clinician to provide clinical expertise and co-investigate research questions. Remote collaboration welcome.

Get in Touch
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Open Position

Computational Biology Collaborator

Seeking collaborators with experience in bioinformatics, multi-omics analysis, or machine learning applied to biological data.

Get in Touch
Contact

Get In Touch

Whether you are a researcher, clinician, patient, or simply curious — we welcome collaboration and conversation.

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We are particularly interested in hearing from:

  • Rheumatologists interested in research collaboration
  • Computational biologists & bioinformaticians
  • SpA patients interested in citizen science
  • Researchers working on related inflammatory diseases