A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics
Patients, hospitals, sensors, researchers, providers, phones, and healthcare organisations are producing enormous amounts of data in both the healthcare and drug detection sectors. The real challenge in these sectors is to find, investigate, manage, and collect information from patients in order to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/6/4/161 |
| _version_ | 1797461409623179264 |
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| author | Krithika Latha Bhaskaran Richard Sakyi Osei Evans Kotei Eric Yaw Agbezuge Carlos Ankora Ernest D. Ganaa |
| author_facet | Krithika Latha Bhaskaran Richard Sakyi Osei Evans Kotei Eric Yaw Agbezuge Carlos Ankora Ernest D. Ganaa |
| author_sort | Krithika Latha Bhaskaran |
| collection | DOAJ |
| description | Patients, hospitals, sensors, researchers, providers, phones, and healthcare organisations are producing enormous amounts of data in both the healthcare and drug detection sectors. The real challenge in these sectors is to find, investigate, manage, and collect information from patients in order to make their lives easier and healthier, not only in terms of formulating new therapies and understanding diseases, but also to predict the results at earlier stages and make effective decisions. The volumes of data available in the fields of pharmacology, toxicology, and pharmaceutics are constantly increasing. These increases are driven by advances in technology, which allow for the analysis of ever-larger data sets. Big Data (BD) has the potential to transform drug development and safety testing by providing new insights into the effects of drugs on human health. However, harnessing this potential involves several challenges, including the need for specialised skills and infrastructure. In this survey, we explore how BD approaches are currently being used in the pharmacology, toxicology, and pharmaceutics fields; in particular, we highlight how researchers have applied BD in pharmacology, toxicology, and pharmaceutics to address various challenges and establish solutions. A comparative analysis helps to trace the implementation of big data in the fields of pharmacology, toxicology, and pharmaceutics. Certain relevant limitations and directions for future research are emphasised. The pharmacology, toxicology, and pharmaceutics fields are still at an early stage of BD adoption, and there are many research challenges to be overcome, in order to effectively employ BD to address specific issues. |
| first_indexed | 2024-03-09T17:19:02Z |
| format | Article |
| id | doaj.art-38ff1b51467e40c7a7c9705f99021197 |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-09T17:19:02Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-38ff1b51467e40c7a7c9705f990211972023-11-24T13:18:22ZengMDPI AGBig Data and Cognitive Computing2504-22892022-12-016416110.3390/bdcc6040161A Survey on Big Data in Pharmacology, Toxicology and PharmaceuticsKrithika Latha Bhaskaran0Richard Sakyi Osei1Evans Kotei2Eric Yaw Agbezuge3Carlos Ankora4Ernest D. Ganaa5School of Information Technology and Engineering, Vellore Institute of Technology, Vellore 632014, IndiaInformation and Communication Technology Department, Faculty of Applied Science and Technology, Dr. Hilla Limann Technical University, Wa P.O. Box 553, GhanaComputer Science Department, Faculty of Applied Science, Kumasi Campus, Kumasi Technical University, Kumasi 00233, GhanaComputer Science Department, Faculty of Applied Science, Kumasi Campus, Kumasi Technical University, Kumasi 00233, GhanaDepartment of Computer Science, Faculty of Applied Sciences and Technology, Ho Technical University, Ho P.O. Box HP 217, GhanaInformation and Communication Technology Department, Faculty of Applied Science and Technology, Dr. Hilla Limann Technical University, Wa P.O. Box 553, GhanaPatients, hospitals, sensors, researchers, providers, phones, and healthcare organisations are producing enormous amounts of data in both the healthcare and drug detection sectors. The real challenge in these sectors is to find, investigate, manage, and collect information from patients in order to make their lives easier and healthier, not only in terms of formulating new therapies and understanding diseases, but also to predict the results at earlier stages and make effective decisions. The volumes of data available in the fields of pharmacology, toxicology, and pharmaceutics are constantly increasing. These increases are driven by advances in technology, which allow for the analysis of ever-larger data sets. Big Data (BD) has the potential to transform drug development and safety testing by providing new insights into the effects of drugs on human health. However, harnessing this potential involves several challenges, including the need for specialised skills and infrastructure. In this survey, we explore how BD approaches are currently being used in the pharmacology, toxicology, and pharmaceutics fields; in particular, we highlight how researchers have applied BD in pharmacology, toxicology, and pharmaceutics to address various challenges and establish solutions. A comparative analysis helps to trace the implementation of big data in the fields of pharmacology, toxicology, and pharmaceutics. Certain relevant limitations and directions for future research are emphasised. The pharmacology, toxicology, and pharmaceutics fields are still at an early stage of BD adoption, and there are many research challenges to be overcome, in order to effectively employ BD to address specific issues.https://www.mdpi.com/2504-2289/6/4/161big datadrug developmenthealthcare pharmacologypharmaceuticstoxicology |
| spellingShingle | Krithika Latha Bhaskaran Richard Sakyi Osei Evans Kotei Eric Yaw Agbezuge Carlos Ankora Ernest D. Ganaa A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics Big Data and Cognitive Computing big data drug development healthcare pharmacology pharmaceutics toxicology |
| title | A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics |
| title_full | A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics |
| title_fullStr | A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics |
| title_full_unstemmed | A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics |
| title_short | A Survey on Big Data in Pharmacology, Toxicology and Pharmaceutics |
| title_sort | survey on big data in pharmacology toxicology and pharmaceutics |
| topic | big data drug development healthcare pharmacology pharmaceutics toxicology |
| url | https://www.mdpi.com/2504-2289/6/4/161 |
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