Organs grown in the lab
Small tissue pieces can be grown or printed, but a complete transplantable organ cannot.
Open in the interactive tree →The shortage of donor organs is huge: only about 10 to 20 percent of global transplant need is met, and more than 100,000 people in the US alone are on waiting lists. Organoids grow from stem cells into pea-sized mini-organs, and bioprinters lay cells in patterns. But a real organ needs blood vessels, nerves, immune compatibility and billions of correctly arranged cells.
As of October 2026
Lab-grown tissues in routine patient use are thin or hollow, such as skin, cartilage and corneas. Organoids and printed tissue stay small and immature because cells more than a fraction of a millimeter from a blood vessel starve. Gene-edited pig organs (record pig-kidney function so far 271 days) are the nearer-term route, and fully human lab-grown organs remain preclinical.
What is missing
- Branching blood-vessel networks that connect to the patient's circulation
- Making hundreds of millions to billions of mature, correctly arranged cells
- Organ-specific structure and function (bile ducts, kidney filtering units, nerves)
- Immune-compatible cells, for example from the patient's own iPS cells
- Production at hospital scale, with quality control and approval pathways
Becomes possible once solved
- An end to organ waiting lists
- Replacement of damaged hearts, livers and kidneys with the patient's own cells
- Tissue models that replace animal testing
Open steps
- Blood-vessel networks Medium AI leverageBranching vessel networks at organ density that connect to a patient's circulation; printers manage only a tiny fraction so far.
- Predicting organoid maturity Medium AI leverageTell early which organoids will mature and function, so only good ones are grown on and recipes can be tuned.
- Billions of mature cells Low AI leverageMake hundreds of millions to billions of mature, correctly arranged cells for one organ at hospital scale.
- Organ-specific structure Medium AI leverageReproduce organ-specific features such as bile ducts, kidney filtering units and nerves with the right cell types in the right places.
- Cells the body accepts Low AI leverageCells that the recipient does not reject, from the patient's own iPS cells or edited donor cells, in organ-scale quantities.
Where AI could help
Low AI leverage. Printing vessels at density, making billions of mature cells and getting approval are engineering limits; AI helps design and tuning, not building tissue.
- Generating perfusable vessel networks that deliver blood evenly through a whole organ
- Image-based models that predict which organoids will mature, to select and tune them
- Searching culture and differentiation conditions with active learning
- Matching donors, recipients and engineered pig organs on immune compatibility
Shown so far
- In June 2025 Science published a Stanford algorithm that designs vessel trees for printed organs about 200 times faster than before, a million vessels for a heart in five hours (physics-based, not machine learning). source
Prerequisites
Unlocks
- Organs on demand2040s?