Applied Mathematics for Pharmaceutical Problems Using Robotics as Assistive Tools for Learning: A Comprehensive Review
DOI:
https://doi.org/10.31764/jtam.v5i2.4720Keywords:
Pharmacy Automation, Cybernetics, Self-Regulating, Smart Machine, Machine Learning, Sophisticated Medical DevicesAbstract
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.References
Amandeep Kaur, Dhiman, M., Mansi Tonk, & Ramneet Kaur. (2020). Real World of Artificial Intelligence - A Review. Journal of Technology Management for Growing Economies, 11(2), 41–47. https://doi.org/10.15415/jtmge.2020.112005
Aoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. In Robot-Proof: Higher Education in the Age of Artificial Intelligence. https://doi.org/10.1080/02607476.2018.1500792
Barrett, M., Oborn, E., Orlikowski, W. J., & Yates, J. A. (2012). Reconfiguring boundary relations: Robotic innovations in pharmacy work. Organization Science, 23(5), 1448–1466. https://doi.org/10.1287/orsc.1100.0639
Basu, B., Dharamsi, A., Makwana, S., & Makasana, Y. (2011). Prefilled syringes: An innovation in parenteral packaging. International Journal of Pharmaceutical Investigation, 1(4), 200. https://doi.org/10.4103/2230-973x.93004
Batson, S., Herranz, A., Rohrbach, N., Canobbio, M., Mitchell, S. A., & Bonnabry, P. (2021). Automation of in-hospital pharmacy dispensing: A systematic review. In European Journal of Hospital Pharmacy (Vol. 28, Issue 2, pp. 58–64). https://doi.org/10.1136/ejhpharm-2019-002081
Bhatnagar, N. (2020). Role of Robotic Process Automation in Pharmaceutical Industries. Advances in Intelligent Systems and Computing, 921, 497–504. https://doi.org/10.1007/978-3-030-14118-9_50
Bhavsar, K., Gohel, D., & Panchal, J. (2021). Design and Analysis of Circular and Square Arm for an Articulated Robot (pp. 457–472). https://doi.org/10.1007/978-981-33-4176-0_39
Bogue, R. (2012). Robots in the laboratory: A review of applications. In Industrial Robot (Vol. 39, Issue 2, pp. 113–119). https://doi.org/10.1108/01439911211203382
Brito, T., Queiroz, J., Piardi, L., Fernandes, L. A., Lima, J., & Leitão, P. (2020). A machine learning approach for collaborative robot smart manufacturing inspection for quality control systems. Procedia Manufacturing, 51, 11–18. https://doi.org/10.1016/j.promfg.2020.10.003
Chen, Y., Patel, V. M., Phillips, P. J., Chellappa, R., Poon, T. W. K., Friesen, M. R., Wang, X., Li, X., Leung, V. C. M., Shukla, S., Yadav, R. N., Zorzi, M., Zanella, A., Testolin, A., Grazia, M. D. F. De, Zorzi, M., Guo, L., Jin, B., Yu, R., … Kose, U. (2018). An Optimizing and Differentially Private Clustering Algorithm for Mixed Data in SDN-Based Smart Grid. IEEE Access, 6, 1.
Cole, A. P., Trinh, Q. D., Sood, A., & Menon, M. (2017). The Rise of Robotic Surgery in the New Millennium. In Journal of Urology (Vol. 197, Issue 2, pp. S213–S215). https://doi.org/10.1016/j.juro.2016.11.030
Colquhoun, A. (2010). Could automation improve efficiency and help pharmacies with cost saving? In Pharmaceutical Journal (Vol. 285, Issue 7628, p. 587).
Cresswell, K., Cunningham-Burley, S., & Sheikh, A. (2018). Health care robotics: Qualitative exploration of key challenges and future directions. Journal of Medical Internet Research, 20(7). https://doi.org/10.2196/10410
Dalton, K., & Byrne, S. (2017). Role of the pharmacist in reducing healthcare costs: current insights. Integrated Pharmacy Research and Practice, Volume 6, 37–46. https://doi.org/10.2147/iprp.s108047
Disler, R. T., Gallagher, R. D., Davidson, P. M., Sun, S.-W., Chen, L.-C., Zhou, M., Wu, J.-H., Meng, Z.-J., Han, H.-L., Miao, S.-Y., Zhu, C.-C., Xiong, X.-Z., Reis, M. S., Sampaio, L. M. M., Lacerda, D., De Oliveira, L. V. F., Pereira, G. B. M., Pantoni, C. B. F., Di Thommazo, L., … Mistraletti, G. (2019). Factors impairing the postural balance in COPD patients and its influence upon activities of daily living. European Respiratory Journal, 15(1), 142–148.
Dwivedi, J. (2012). Robotic Surgery-A Review on Recent advances in Surgical Robotic Systems. Florida Conference on Recent Advances in Robotics, January 2012, 1–7. http://www.eng.fau.edu/conf/fcrar/papers/FCRAR_2012_2_1_Dwivedi_Mahgoub_FAU.pdf
Estolatan, E., Geuna, A., Guerzoni, M., & Nuccio, M. (2018). Mapping the evolution of the robotics industry: A cross-country comparison. In Innovation Policy White Paper Series. https://munkschool.utoronto.ca/ipl/files/2018/07/robots-final-Jul11.pdf
Gbadegeshin, S. A. (2019). The Effect of Digitalization on the Commercialization Process of High-Technology Companies in the Life Sciences Industry. Technology Innovation Management Review, 9(1), 49–63. https://doi.org/10.22215/timreview/1211
Girasa, R. (2020). Artificial Intelligence as a Disruptive Technology. In Artificial Intelligence as a Disruptive Technology. https://doi.org/10.1007/978-3-030-35975-1
Gomez, M. (2012). Pharmacy automation: Getting help from max and mini. Journal of the American Pharmacists Association, 52(5), 682. http://japha.org/data/Journals/JAPhA/24893/JAPhA_52_5_668.pdf
Grau, A., Bolea, Y., Sanfeliu, A., & Puig-Pey, A. (2017). The Echord Plus Plus Project: Robotics In A Public Economy. Economic And Social Development (Esd): Managerial Issues In Modern Business, 40–49.
Gunkel, D. J. (2018). The other question: can and should robots have rights? Ethics and Information Technology, 20(2), 87–99. https://doi.org/10.1007/s10676-017-9442-4
Haidegger, T. (2019). Autonomy for Surgical Robots: Concepts and Paradigms. IEEE Transactions on Medical Robotics and Bionics, 1(2), 65–76. https://doi.org/10.1109/tmrb.2019.2913282
Isaacs, D. (2020). Artificial intelligence in health care. In Journal of Paediatrics and Child Health (Vol. 56, Issue 10, pp. 1493–1495). https://doi.org/10.1111/jpc.14828
ISO 8373. (2012). Robots and robotic devices. ISO Online Browsing Platform, 30, 38. https://www.iso.org/standard/55890.html
Jain, R., Paterson, S., & Spear, M. (2019). Robotic assisted orthopaedic surgery: Super-specialist niche or the future of practice? Journal of Anatomy, 234(3), 415–416. https://www.embase.com/search/results?subaction=viewrecord&id=L626453347&from=exporthttp://dx.doi.org/10.1111/joa.12923
James, K. L., Barlow, D., Bithell, A., Hiom, S., Lord, S., Pollard, M., Roberts, D., Way, C., & Whittlesea, C. (2013). The impact of automation on workload and dispensing errors in a hospital pharmacy. International Journal of Pharmacy Practice, 21(2), 92–104. https://doi.org/10.1111/j.2042-7174.2012.00238.x
Ji, W., & Wang, L. (2019). Industrial robotic machining: a review. International Journal of Advanced Manufacturing Technology, 103(1-4), 1239–1255. https://doi.org/10.1007/s00170-019-03403-z
Joiner, I. A. (2018). Emerging library technologies: It’s not just for geeks. In Emerging Library Technologies: It’s Not Just for Geeks. https://doi.org/10.1016/C2016-0-05178-1
Junia Santillo Costa, J., Lajovic Carneiro, M., & Antonio Urzedo Machado, T. (2020). Implementation and Validation of Thor 3D Printed Open Source Robotic Arm. IEEE Latin America Transactions, 18(5), 907–913. https://doi.org/10.1109/TLA.2020.9082919
Kabra, M. P., Kabra, D., & Somani, G. (2011). A REVIEW ON ROLE OF ROBOT IN PHARMACEUTICAL INDUSTRY. In International Journal of Institutional Pharmacy and Life Sciences (Vol. 1, Issue 1). www.ijipls.com
Khader, N., Lashier, A., & Yoon, S. W. (2016). Pharmacy robotic dispensing and planogram analysis using association rule mining with prescription data. Expert Systems with Applications, 57, 296–310. https://doi.org/10.1016/j.eswa.2016.02.045
Kulkarni, A. A., Dhanush, P., Chetan, B. S., Thamme Gowda, C. S., & Shrivastava, P. K. (2020). Applications of Automation and Robotics in Agriculture Industries; A Review. IOP Conference Series: Materials Science and Engineering, 748(1). https://doi.org/10.1088/1757-899X/748/1/012002
Landers, R. N. (2019). The cambridge handbook of technology and employee behavior. In The Cambridge Handbook of Technology and Employee Behavior. https://doi.org/10.1017/9781108649636
Lee Ventola, C. (2014). Medical applications for 3D printing: Current and projected uses. P and T, 39(10), 704–711.
Leinbach, P. E. (2014). Personnel administration in an automated environment. In Personnel Administration in an Automated Environment. https://doi.org/10.4324/9781315801506
Liu, H. Y., & Huang, H. (2015). Design and Structural Analysis of Robot Arm for High Performance Packaging Robots. Applied Mechanics and Materials, 741, 669–674. https://doi.org/10.4028/www.scientific.net/amm.741.669
MejÃa, L., & Franco, I. (2019). Force-conductance spectroscopy of a single-molecule reaction. Chemical Science, 10(11), 3249–3256. https://doi.org/10.1039/c8sc04830d
Mokled, E., Chartouni, G., Kassis, C., & Rizk, R. (2019). Parallel Robot Integration and Synchronization in a Waste Sorting System. In Mechanisms and Machine Science (Vol. 58, pp. 171–187). https://doi.org/10.1007/978-3-319-89911-4_13
Mourtzis, D., Papakostas, N., Mavrikios, D., Makris, S., & Alexopoulos, K. (2015). The role of simulation in digital manufacturing: Applications and outlook. International Journal of Computer Integrated Manufacturing, 28(1), 3–24. https://doi.org/10.1080/0951192X.2013.800234
Nie, Z. (2020). Research on sports planning and stability control of humanoid robot table tennis. International Journal of Advanced Robotic Systems, 17(1). https://doi.org/10.1177/1729881420905960
Nikolov, E., Nikolova, N. G., & Georgiev, M. (2020). Description and modelling of robot-manipulator FANUC M-430iA/4FH. IOP Conference Series: Materials Science and Engineering, 878(1). https://doi.org/10.1088/1757-899X/878/1/012006
Patel, A. R., Patel, R. S., Singh, N. M., & Kazi, F. S. (2017). Vitality of Robotics in Healthcare Industry: An Internet of Things (IoT) Perspective (pp. 91–109). https://doi.org/10.1007/978-3-319-49736-5_5
Raju, G., Sarkar, P., Singla, E., Singh, H., & Sharma, R. K. (2016). Comparison of environmental sustainability of pharmaceutical packaging. Perspectives in Science, 8, 683–685. https://doi.org/10.1016/j.pisc.2016.06.058
Rasouli, J. J., Shao, J., Neifert, S., Gibbs, W. N., Habboub, G., Steinmetz, M. P., Benzel, E., & Mroz, T. E. (2020). Artificial Intelligence and Robotics in Spine Surgery. In Global Spine Journal. https://doi.org/10.1177/2192568220915718
Rocha, M. A. M. da. (2017). The automotive sector in emerging economies. Revista Brasileira de Inovação, 16(2), 437–442. https://doi.org/10.20396/rbi.v16i2.8650118
Roshanianfard, A., & Noguchi, N. (2018). Kinematics analysis and simulation of a 5DOF articulated robotic arm applied to heavy products harvesting. Tarim Bilimleri Dergisi, 24(1), 91–104. https://doi.org/10.15832/ankutbd.446396
Shah, R., & Pandey, A. B. (2018). Concept for Automated Sorting Robotic Arm. Procedia Manufacturing, 20, 400–405. https://doi.org/10.1016/j.promfg.2018.02.058
Shukla, A. A., Rameez, S., Wolfe, L. S., & Oien, N. (2018). High-throughput process development for biopharmaceuticals. In Advances in Biochemical Engineering/Biotechnology (Vol. 165, pp. 401–441). https://doi.org/10.1007/10_2017_20
Spinks, J., Jackson, J., Kirkpatrick, C. M., & Wheeler, A. J. (2017). Disruptive innovation in community pharmacy – Impact of automation on the pharmacist workforce. In Research in Social and Administrative Pharmacy (Vol. 13, Issue 2, pp. 394–397). https://doi.org/10.1016/j.sapharm.2016.04.009
Takács, Ã., Kovács, L., Rudas, I. J., Precup, R. E., & Haidegger, T. (2015). Models for force control in telesurgical robot systems. Acta Polytechnica Hungarica, 12(8), 95–114. https://doi.org/10.12700/aph.12.8.2015.8.6
Taulli, T. (2020). The Robotic Process Automation Handbook. In The Robotic Process Automation Handbook. https://doi.org/10.1007/978-1-4842-5729-6
Taylor, R. H., Menciassi, A., Fichtinger, G., Fiorini, P., & Dario, P. (2016). Medical robotics and computer-integrated surgery. In Springer Handbook of Robotics (pp. 1657–1683). https://doi.org/10.1007/978-3-319-32552-1_63
Teja, L. T., Keerthi, P., Datta, D., & Babu, N. M. (2014). Recent trends in the usage of robotics in pharmacy. Indian Journal of Research in Pharmacy and Biotechnology, 2(1), 1038. https://libproxy.wlu.ca/login?url=https://search.proquest.com/docview/1562671375?accountid=15090%0Ahttp://sfx.scholarsportal.info/laurier?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&genre=article&sid=ProQ:ProQ%3Aagricenvironm&atitle=Recen
Terra Univesral Inc. (2012). FS209E and ISO cleanroom Standards. Terra Universal.com, 4. http://www.terrauniversal.com/cleanroos/iso-classification-cleanrro-standards.php
Vaidyanathan, R., Sharma, G., & Trahan, J. (2021). On fast pattern formation by autonomous robots. Information and Computation. https://doi.org/10.1016/j.ic.2021.104699
Weiß, M. (2018). Optimization of Robot Tasks with Cartesian Degrees of Freedom using Virtual Joints. In arXiv.
West, D. M. (2018). The future of work: Robots, AI, and automation. In The Future of Work: Robots, AI, and Automation.
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