Building consistent ML pipelines in regulated clinical environments requires strict data governance, consistency, and assessment. Integrate version control, self-opted testing, and audit trails. Ensure observance with healthcare regulations (e.g., HIPAA, GDPR), maintain interpretability, monitor model execution continuously, and document sequences to support transparency, safety, and regulatory review.