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Artificial intelligence powers regenerative medicine into predictive realm.

Armin Garmany1,2, Andre Terzic1

  • 1Marriott Heart Disease Research Program, Department of Cardiovascular Medicine, Department of Molecular Pharmacology & Experimental Therapeutics, Department of Clinical Genomics, Mayo Clinic, Rochester, MN, USA.

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|December 11, 2024
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Summary
This summary is machine-generated.

Artificial intelligence (AI) is revolutionizing regenerative medicine by enhancing precision and outcomes. AI integration across discovery, manufacturing, and clinical applications promises more effective and equitable regenerative therapies.

Keywords:
artificial intelligencehealthcaremachine learningmanufacturingregenerationstem cellsystems biologytissue engineering

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Area of Science:

  • Regenerative Medicine
  • Bioinformatics
  • Artificial Intelligence

Background:

  • Regenerative medicine aims to improve tissue repair and regeneration but requires enhanced precision and reliability.
  • Current regenerative medicine approaches often rely on empirical methods, necessitating data-driven advancements.
  • The convergence of big data, informatics, and artificial intelligence (AI) presents a transformative opportunity.

Purpose of the Study:

  • To explore the potential of artificial intelligence in advancing regenerative medicine.
  • To outline AI's role in optimizing biotherapeutic discovery, manufacturing, and clinical applications.
  • To address the challenges and ethical considerations associated with AI in regenerative medicine.

Main Methods:

  • Leveraging big data analytics and artificial intelligence algorithms.
  • Applying AI for interpretation of repair outcome readouts in biotherapeutic development.
  • Utilizing AI for automated quality control and process monitoring in biomanufacturing.
  • Employing AI to guide clinical trial design, patient selection, and outcome assessment.

Main Results:

  • AI can streamline the discovery and development of optimized biotherapeutics.
  • AI enhances quality control and scalability in advanced biomanufacturing through automated monitoring.
  • AI provides critical support for clinical trial design, patient stratification, and treatment delivery strategies.

Conclusions:

  • Artificial intelligence is poised to significantly enhance the precision, efficiency, and effectiveness of regenerative medicine.
  • Responsible AI implementation requires careful consideration of bias, generalizability, and ethical concerns.
  • The goal is to ensure equitable access to advanced regenerative therapies for all patients.