Related Experiment Video
Updated: Aug 15, 2026
07:45
The Use of Mixed Reality in Custom-Made Revision Hip Arthroplasty: A First Case Report
Published on: August 4, 2022
Artificial Intelligence-Guided Precision Orthobiologics in Musculoskeletal Conditions
Sanjeevi Bharadwaj1, Naveen Jeyaraman2,3,4, Subasri Balasubramanian5
1Trauma and Orthopaedic Registrar, Wye Valley, National Health Service Trust, Hereford, United Kingdom.
Journal of Orthopaedic Case Reports
|August 14, 2026
Summary
Artificial intelligence (AI) enhances precision orthobiologics for musculoskeletal conditions like osteoarthritis. While AI shows promise in predicting treatment response and personalizing care, further validation and standardization are crucial for clinical integration.
Area of Science:
- Orthobiology and Regenerative Medicine
- Artificial Intelligence in Healthcare
- Musculoskeletal Disorders Treatment
Background:
- Orthobiologics are increasingly used for osteoarthritis, tendinopathy, and cartilage injuries.
- Clinical outcomes with orthobiologics are inconsistent due to patient variability and product factors.
- Advances in AI offer potential solutions for optimizing orthobiologic treatments.
Purpose of the Study:
- To explore the role of Artificial Intelligence (AI) in advancing precision orthobiologics.
- To review AI applications for improving treatment efficacy and patient stratification in orthopedics.
- To assess the current state and future directions of AI in orthobiologic therapies.
Main Methods:
- Literature search of PubMed, Embase, Cochrane Library, and Scopus (Jan 2019-June 2026).
- Keywords included orthobiologics, AI, machine learning, specific conditions (OA, tendinopathy), and regulatory aspects.
- Narrative synthesis based on principles for assessing narrative review articles.
Main Results:
- AI is key for precision orthobiologics, enabling responder prediction and patient phenotyping.
- Deep learning can quantify imaging biomarkers, and NLP can track outcomes.
- AI facilitates multicenter validation but faces challenges like bias and regulatory uncertainty.
Conclusions:
- AI-assisted orthobiologics represent a translational precision medicine approach.
- Standardization, prospective validation, and regulatory alignment are essential for safe clinical adoption.
- Ongoing outcome monitoring is necessary before routine use of AI in orthobiologics.