Artificial intelligence approaches that link patient data with chemical-induced kidney injury patterns are revolutionizing nephrotoxicity risk assessment. Substantial progress has been made in the development of integrated approaches that leverage big data, molecular profiles and toxicological understanding to identify at-risk patients, provide insights into molecular mechanisms and advance predictive nephrology.

Mexico faces a high burden of chronic kidney disease, which is worsened by fragmented health care and a lack of universal coverage for kidney replacement therapy. The Mexico City CKD Project has improved access for uninsured patients through policy reforms, workforce expansion and infrastructure development, demonstrating a scalable model to reduce kidney health disparities.

The prohibitive costs of new pharmacological agents, particularly biologicals, have largely limited their use to high-income countries, resulting in widening of health disparities. Urgent action from the pharmaceutical industry, governments and healthcare organizations is needed to improve access to treatment and address these inequities.

The inclusion of individuals with disabilities and patients as partners in biomedical research is critical for driving innovation. Equally important are patient–researchers, who are instrumental in identifying key research problems and driving research towards areas of direct benefit. We call for institutions to actively work towards accommodating patient–researchers.