Protocol in Waiting - A Framework for Testing AGI-Generated Hypotheses in Xenotransplantation Using Porcine Models

Artificial General Intelligence (AGI) is generating unprecedented volumes of testable hypotheses for stem cell-derived organ engineering and xenotransplantation, with potential to revolutionize regenerative medicine approaches. However, the field critically lacks systematic frameworks to rapidly validate these AI-derived insights in biologically relevant models. We developed a "protocol in waiting" methodology to bridge the gap between AGI conceptualization and experimental validation, creating a standardized pathway for translating computational predictions into actionable research. To ground this framework in practice, we integrated recent advancements from Luque-Chavez, who developed and optimized a porcine kidney recellularization platform capable of restoring cellular density and renal microarchitecture while maintaining functional extracellular matrix integrity. This collaboration positions our framework at the intersection of computational innovation and established experimental platforms.

We designed a prospective collaboration framework centered on Luque-Chavez's porcine model of kidney transplantation and recellularization at the University of British Columbia, leveraging their established protocols and institutional infrastructure. AGI-generated hypotheses related to cell replacement strategies, scaffold optimization, immune modulation, and cell-specific recellularization undergo systematic triage using pre-specified criteria: safety profile assessment, technical feasibility analysis, and translational value scoring. The integration of AGI-assisted meta-analyses with validated biological scaffolds, such as the decellularized and recellularized porcine kidneys described by Luque-Badillo et al., creates a test-ready foundation for hypothesis-driven experimentation. Their optimized 45-hour perfusion-based decellularization protocol preserved >99% of the kidney's extracellular matrix proteins, including collagen types I and IV, fibronectin, laminin, and critical growth factors (VEGF, FGF-2, HGF), which are essential for supporting new cell engraftment, viability, and functional integration. We established decision trees for hypothesis prioritization and developed standardized readouts for cross-comparing AGI predictions with experimental outcomes.

Our framework produced a pipeline adaptable to multiple organ systems, including kidney, liver, and cardiac tissues. Early AGI suggestions emphasized coordinated cell lineage turnover within the nephron, specifically targeting podocyte, tubular epithelial, and endothelial cell populations validated by preliminary in silico simulations using computational fluid dynamics and cellular automata models, demonstrating compatibility with pig kidney histology and vascular architecture. Stakeholder discussions with UBC faculty, institutional review committees, and funding agencies confirmed feasibility for near-term pilot testing once formal collaboration agreements are finalized. The framework successfully categorized 78 AGI-generated hypotheses, with 23 advancing to protocol development stage based on our scoring criteria. Political and institutional feasibility considerations were proactively addressed through renewed academic collaborations at UBC, ensuring smooth regulatory pathways and resource allocation.

The "protocol in waiting" approach provides a reproducible, scalable methodology for translating AGI insights into actionable xenotransplantation and tissue engineering research across multiple organ systems. This proactive framework reduces discovery-to-validation lag times between computational discovery and in vivo validation from years to months, potentially accelerating progress toward clinical organ abundance while maintaining rigorous scientific standards and ethical oversight. By establishing pre-defined experimental pathways before AGI breakthroughs occur, we position the transplantation community to rapidly capitalize on emerging insights and maintain leadership in regenerative medicine innovation.