Additive Manufacturing Processes in Biomedical Engineering 2022
DOI: 10.1201/9781003217961-1
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Recent Advancements of Additive Manufacturing for Patient-Specific Drug Delivery

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“…An educated prediction may include the hypothesis that future directions being added to the healthcare map will be exceptionally combinatorial and may well tie in with technologies which have been discussed elsewhere within this chapter, in addition to others. Drastically enhanced computing power and the ability for systems to handle, process and draw conclusions from extraordinarily large data sets have led to the emergence of "big data", which in turn can centralise hugely useful information such as patient data sets, treatment outcomes and a host of other useful clinical, management-centric and professional performance data (Dash et al 2019;Hanna and Hanna 2019) This, combined with technologies such as AI, labs-on-chip-based testing and enhancements in rapid drug and device manufacturing will accelerate the area of personalised medicine (Wu et al 2018;Jhunjhunwala and Kapil 2022;Katakam, Adiki, and Satapathy 2022), potentially allowing us to move away from population-based empirical models for the treatment of disease and, instead, toward something which is maximally targeted. It is not long ago that the suggestion that someone who had fallen ill could be tested at their bedside, and their diagnostic test results instantly generated and fed into a data set which would allow both the selection of a medication that would cater specifically to that patient's needs, and its manufacture within hours or minutes within the care setting, would be touted as something straight from a science-fiction novel.…”
Section: Future Directionsmentioning
confidence: 99%
“…An educated prediction may include the hypothesis that future directions being added to the healthcare map will be exceptionally combinatorial and may well tie in with technologies which have been discussed elsewhere within this chapter, in addition to others. Drastically enhanced computing power and the ability for systems to handle, process and draw conclusions from extraordinarily large data sets have led to the emergence of "big data", which in turn can centralise hugely useful information such as patient data sets, treatment outcomes and a host of other useful clinical, management-centric and professional performance data (Dash et al 2019;Hanna and Hanna 2019) This, combined with technologies such as AI, labs-on-chip-based testing and enhancements in rapid drug and device manufacturing will accelerate the area of personalised medicine (Wu et al 2018;Jhunjhunwala and Kapil 2022;Katakam, Adiki, and Satapathy 2022), potentially allowing us to move away from population-based empirical models for the treatment of disease and, instead, toward something which is maximally targeted. It is not long ago that the suggestion that someone who had fallen ill could be tested at their bedside, and their diagnostic test results instantly generated and fed into a data set which would allow both the selection of a medication that would cater specifically to that patient's needs, and its manufacture within hours or minutes within the care setting, would be touted as something straight from a science-fiction novel.…”
Section: Future Directionsmentioning
confidence: 99%