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. 2018 Dec 19;20(12):e12448.
doi: 10.2196/12448.

Decision Support Tools for Regenerative Medicine: Systematic Review

Ching Lam  1   2 , Edward Meinert  2   3 , Abrar Alturkistani  3 , Alison R Carter  2 , Jeffrey Karp  4 , Aidong Yang  1 , David Brindley  2 , Zhanfeng Cui  1
Affiliations

Decision Support Tools for Regenerative Medicine: Systematic Review

Ching Lam et al. J Med Internet Res. .

Abstract

Background: Decisional tools have demonstrated their importance in informing manufacturing and commercial decisions in the monoclonal antibody domain. Recent approved therapies in regenerative medicine have shown great clinical benefits to patients.

Objective: The objective of this review was to investigate what decisional tools are available and what issues and gaps have been raised for their use in regenerative medicine.

Methods: We systematically searched MEDLINE to identify articles on decision support tools relevant to tissue engineering, and cell and gene therapy, with the aim of identifying gaps for future decisional tool development. We included published studies in English including a description of decisional tools in regenerative medicines. We extracted data using a predesigned Excel table and assessed the data both quantitatively and qualitatively.

Results: We identified 9 articles addressing key decisions in manufacturing and product development challenges in cell therapies. The decision objectives, parameters, assumptions, and solution methods were analyzed in detail. We found that all decisional tools focused on cell therapies, and 6 of the 9 reviews focused on allogeneic cell therapy products. We identified no available tools on tissue-engineering and gene therapy products. These studies addressed key decisions in manufacturing and product development challenges in cell therapies, such as choice of technology, through modeling.

Conclusions: Our review identified a limited number of decisional tools. While the monoclonal antibodies and biologics decisional tool domain has been well developed and has shown great importance in driving more cost-effective manufacturing processes and better investment decisions, there is a lot to be learned in the regenerative medicine domain. There is ample space for expansion, especially with regard to autologous cell therapies, tissue engineering, and gene therapies. To consider the problem more comprehensively, the full needle-to-needle process should be modeled and evaluated.

Keywords: cell therapy; cell- and tissue-based therapy; decision support techniques; decisional tool; regenerative medicine; systematic review.

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Conflict of interest statement

Conflicts of Interest: Funding support from the CRMI-Oxford Technology Centre is gratefully acknowledged. JK has been a paid consultant in the field of regenerative medicine for companies including Stempeutics, Sanofi, Celltex, LifeVaultBio, Takeda, and Mesoblast. JK is also an inventor on a patent that was licensed to Mesoblast. JK holds equity in Frequency Therapeutics, a company that has licensed intellectual property generated by JK that may benefit financially if it is further validated. The interests of JK were reviewed and are subject to a management plan overseen by his institutions in accordance with its conflict of interest policies. DB is a stockholder in Translation Ventures Ltd (Charlbury, Oxfordshire, UK) and IP Asset Ventures Ltd (Oxford, Oxfordshire, UK), companies that, among other services, provide cell therapy biomanufacturing, and regulatory and financial advice to pharmaceutical clients. DB is also subject to the CFA Institute’s codes, standards, and guidelines, so he must stress that this piece is provided for academic interest only and must not be construed in any way as an investment recommendation. Additionally, at the time of publication, DB and the organizations with which he is affiliated may or may not have agreed or have pending funding commitments from the organizations named here.

Figures

Figure 1
Figure 1
Key data extracted from the eligible literature.
Figure 2
Figure 2
Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA) flowchart of the literature review process.
Figure 3
Figure 3
Coverage of existing decisional tools. conc: concentration; DSP: downstream processing; QC: quality control; USP: upstream processing.
Figure 4
Figure 4
Upstream and downstream operations considered in the reviewed articles. FACS: fluorescence-activated cell sorting; MACS: magnetic-activated cell sorting.
Figure 5
Figure 5
Choice of simulation platforms.
See this image and copyright information in PMC

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