Applied Mathematics for Pharmaceutical Problems Using Robotics as Assistive Tools for Learning:  A Comprehensive Review

Manu Singhai; Akhilesh Kumar Singhai; Kirti Verma

doi:10.31764/jtam.v5i2.4720

Applied Mathematics for Pharmaceutical Problems Using Robotics as Assistive Tools for Learning: A Comprehensive Review

Manu Singhai, Akhilesh Kumar Singhai, Kirti Verma

Abstract

Smart machine endures getting smarter as they are going to access more about the facts and pieces of evidence that make our work even more authentic than before. The term “robot” was created in 1920 by Czechoslovakian playwright Karel Capek and has been a principal point in science fiction ever since. Pharmacy automation involves machine-driven or mechanical processes of distributing, dispensing and managing medications. Pharmaceutical organizations take advantage of robotics to manoeuvre biological or chemical samples around to integrate novel chemical structure or to test the pharmaceutical value of remaining organic material. Pharmaceutical applications with aid of robotic systems are progressively accepted for enhanced throughput and proficiency to satisfy this growing demand, within a rapidly ageing population that directly requires sophisticated medical devices and newer drugs. According to Robot IQ, mathematics is one of the few main robotics attributes that cannot be learned along the way. A good background in many fields of mathematics and science is needed for robotics at the very least. Several studies have shown that robotics is an effective medium for teaching STEM (Science, Technology, Engineering, and Mathematics) skills to students. Thus, Novel methods are under development in machine learning, symbolic reasoning and signal processing which may be utilized in production and packaging concerned to the pharmaceuticals. The target is to review the Planning, Safety, Reliability, Accuracy, Quality, Flexibility, Redeployment, Efficiency and other vital applications of Robotics in Pharmacy.

Keywords

Pharmacy Automation; Cybernetics; Self-Regulating; Smart Machine; Machine Learning; Sophisticated Medical Devices

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References

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DOI: https://doi.org/10.31764/jtam.v5i2.4720