ArticleFrontiers in medicine2021
From Single Batch to Mass Production-Automated Platform Design Concept for a Phase II Clinical Trial Tissue Engineered Cartilage Product.
Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- From microtissues to macro solutions - The future of scalable and automated cartilage tissue engineering.Journal of orthopaedic translation · 2026Review
- Towards a bioengineered airway: advances in tracheal tissue engineering and biofabrication.Frontiers in cell and developmental biology · 2026Review
- Current challenges and future directions of ATMPs in regenerative medicine.Regenerative therapy · 2025Review
- Feasibility analysis of automated cleaning in biopharmaceutical production using cleaning-in-place concepts from food production.Frontiers in medical technology · 2025Article
- Autologous and Allogeneic Cytotherapies for Large Knee (Osteo)Chondral Defects: Manufacturing Process Benchmarking and Parallel Functional Qualification.Pharmaceutics · 2023Article
- The Evolving Landscape of Potency Assays.Advances in experimental medicine and biology · 2023Article
- Advances in hPSC expansion towards therapeutic entities: A review.Cell proliferation · 2022Review
- Article
- Scalable Biofabrication: A Perspective on the Current State and Future Potentials of Process Automation in 3D-Bioprinting Applications.Frontiers in bioengineering and biotechnology · 2022Article
Corrections and comments
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Authors and funding
13 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advanced Therapy Medicinal Products (ATMP) provide promising treatment options particularly for unmet clinical needs, such as progressive and chronic diseases where currently no satisfying treatment exists. Especially from the ATMP subclass of Tissue Engineered Products (TEPs), only a few have yet been translated from an academic setting to clinic and beyond. A reason for low numbers of TEPs in current clinical trials and one main key hurdle for TEPs is the cost and labor-intensive manufacturing process. Manual production steps require experienced personnel, are challenging to standardize and to scale up. Automated manufacturing has the potential to overcome these challenges, toward an increasing cost-effectiveness. One major obstacle for automation is the control and risk prevention of cross contaminations, especially when handling parallel production lines of different patient material. These critical steps necessitate validated effective and efficient cleaning procedures in an automated system. In this perspective, possible technologies, concepts and solutions to existing ATMP manufacturing hurdles are discussed on the example of a late clinical phase II trial TEP. In compliance to Good Manufacturing Practice (GMP) guidelines, we propose a dual arm robot based isolator approach. Our novel concept enables complete process automation for adherent cell culture, and the translation of all manual process steps with standard laboratory equipment. Moreover, we discuss novel solutions for automated cleaning, without the need for human intervention. Consequently, our automation concept offers the unique chance to scale up production while becoming more cost-effective, which will ultimately increase TEP availability to a broader number of patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.