scholarly journals Decision Support Tools for Regenerative Medicine: Systematic Review (Preprint)

2018 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison R. Carter ◽  
Jeffrey Karp ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Gene Therapy ◽  
Decision Support ◽  
Regenerative Medicine ◽  
Product Development ◽  
Cost Effective ◽  
Decision Support Tools ◽  
Cell Therapies ◽  
Allogeneic Cell Therapy ◽  
Support Tools

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.

scholarly journals Decision Support Tools for Regenerative Medicine: Systematic Review

10.2196/12448 ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. e12448 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison R Carter ◽  
Jeffrey Karp ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Regenerative Medicine ◽  
Decision Support Tools ◽  
Support Tools

A Systematic Review of Decision-Support Tools for Regenerative Medicine

2018 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison Carter ◽  
Jeffery M. Karp ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Regenerative Medicine ◽  
Decision Support Tools ◽  
Support Tools

A Framework for Concurrent Consideration in Advanced Product Development Technology Selection

2011 ◽  
Author(s):  
P. J. Farrugia ◽  
E. Francalanza ◽  
K. Coppini
Keyword(s):  
Decision Support ◽  
Product Development ◽  
Appropriate Technology ◽  
Technology Selection ◽  
Decision Support Tools ◽  
Manufacturing Companies ◽  
Time To Market ◽  
Fused Deposition ◽  
Technical Requirements ◽  
Support Tools

In order to survive in the modern market, manufacturing companies need to invest in Advanced Product Development Technologies (APDTs). The problem many companies face, however, is the huge variety of possible technologies available. Examples of these are Stereo Lithography Apparatus (SLA), Selective Laser Sintering (SLS), Fused Deposition Modelling (FDM), Virtual Prototyping and many others. A literature review revealed that there were many attempts at implementing decision support tools, for the selection of the most appropriate APDT for a particular application. These tools were limited in scope to a small range of technologies. Examples of this are the several attempts in the field of Rapid Prototyping. Furthermore the approaches which exist focus on the technical requirements only of the machine and very rarely take into consideration the needs of the manufacturing organization as a whole. Therefore as a result, there is a lack of decision support tools for selecting APDTs while considering the different Product Development (PD) stages. One area in which these APDTs excel is in the reduction of lead times to develop a product. Therefore the implementation of such technologies can potentially reduce the time-to-market of companies investing in them. The question which remains unanswered is: how does one choose the technology which will deliver the greatest improvement with regards to time-to-market? To address this question, this research developed a framework which allows stakeholders in the organization to select the most appropriate technology to reduce time-to-market for companies following the Integrated Product Development (IPD) model. This framework is based on their requirements and a structured approach. This paper presents the framework developed to this end, which was implemented in an Information and Communication Technology (ICT)-based prototype tool. The novelty of the proposed framework lies in the fact that it combines Multiple Attribute Decision Methods (MADM), more specifically Analytical Hierarchical Process (AHP) and Simple Additive Weighting (SAW) along with the IPD model and continuous improvement practices. The validity of the proposed ICT tool was evaluated qualitatively by stakeholders from different PD perspectives such as sales and marketing, product design and manufacturing. The evaluation results provide a degree of evidence that the proposed framework and ICT tool were effective at meeting the time-to-market shortcomings of current product development practices of companies.

Decision Support Tools For Assessing Petroleum Upstream Investments

2020 ◽  
pp. 323
Author(s):  
Nour Elislam Djedaa ◽  
Abderrezak Moulay Lakhdar
Keyword(s):  
Decision Support ◽  
Decision Support Tools ◽  
Support Tools

Elicitation of expert knowledge to develop decision support tools for use in water demand management planning

2007 ◽  
Vol 7 (5-6) ◽  
pp. 53-60
Author(s):  
D. Inman ◽  
D. Simidchiev ◽  
P. Jeffrey
Keyword(s):  
Decision Support ◽  
Water Demand ◽  
Expert Knowledge ◽  
Demand Management ◽  
Decision Processes ◽  
Conservation Strategy ◽  
Influence Diagrams ◽  
Decision Support Tools ◽  
Water Demand Management ◽  
Support Tools

This paper examines the use of influence diagrams (IDs) in water demand management (WDM) strategy planning with the specific objective of exploring how IDs can be used in developing computer-based decision support tools (DSTs) to complement and support existing WDM decision processes. We report the results of an expert consultation carried out in collaboration with water industry specialists in Sofia, Bulgaria. The elicited information is presented as influence diagrams and the discussion looks at their usefulness in WDM strategy design and the specification of suitable modelling techniques. The paper concludes that IDs themselves are useful in developing model structures for use in evidence-based reasoning models such as Bayesian Networks, and this is in keeping with the objectives set out in the introduction of integrating DSTs into existing decision processes. The paper will be of interest to modellers, decision-makers and scientists involved in designing tools to support resource conservation strategy implementation.

scholarly journals Designing environmentally efficient aquafeeds through the use of multi-criteria decision support tools

2021 ◽  
pp. 100276
Author(s):  
Ronan Cooney ◽  
Alex H.L. Wan ◽  
Fearghal O’Donncha ◽  
Eoghan Clifford
Keyword(s):  
Decision Support ◽  
Decision Support Tools ◽  
Support Tools

Decision support tools for oil spill response (OSR-DSTs): Approaches, challenges, and future research perspectives

2021 ◽  
Vol 167 ◽  
pp. 112313
Author(s):  
Zhaoyang Yang ◽  
Zhi Chen ◽  
Kenneth Lee ◽  
Edward Owens ◽  
Michel C. Boufadel ◽  
...  
Keyword(s):  
Decision Support ◽  
Oil Spill ◽  
Future Research ◽  
Decision Support Tools ◽  
Research Perspectives ◽  
Support Tools ◽  
Oil Spill Response
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