Employing Artificial Intelligence Methods in Drug Development: A New Era in Medicine Article Swipe
Omega John Unogwu
,
Mabel Ike
,
Opkanachi Omatule Joktan
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.58496/mjaih/2023/010
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.58496/mjaih/2023/010
Artificial intelligence (AI) plays a vital role in the development of pharmaceuticals. The whole drug development process, from target identification and lead optimization to clinical trials and post-marketing monitoring, has the potential to be revolutionized by AI. Data analysis is a crucial area where AI thrives. To find trends, correlations, and prospective targets for therapeutic intervention, AI systems can analyse enormous volumes of data, including electronic health records, molecular databases, academic literature, and clinical trial data. This saves time and resources by enabling researchers to decide which compounds or pathways to investigate. Lead optimization is another area where AI is essential since algorithms can screen and forecast the efficacy of new drug candidates. To improve efficacy, safety, and pharmacokinetics, the most promising leads are prioritized, and their attributes are optimized. By examining past data to pinpoint patient groupings that are most likely to respond to a certain medication, AI can also improve clinical trial design and patient selection. This advances success rates aids in the development of personalized medication and can support post-marketing surveillance by continuously scanning real-world data for adverse events or unexpected drug-drug interactions after a medicine has been licensed. This permits the quicker detection of potential safety issues and contributes to maintaining the continuous safety of licensed medications. However, some obstacles must be overcome to completely utilize AI in medication development. These include the requirement for high-quality data, assuring AI model transparency and interpretability, taking into account ethical issues, and regulatory frameworks for using AI in drug development.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.58496/mjaih/2023/010
- https://journals.mesopotamian.press/index.php/MJAIH/article/download/129/131
- OA Status
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All OpenAlex metadata
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https://openalex.org/W4388980802Canonical identifier for this work in OpenAlex
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https://doi.org/10.58496/mjaih/2023/010Digital Object Identifier
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Employing Artificial Intelligence Methods in Drug Development: A New Era in MedicineWork title
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articleOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
- Publication date
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2023-10-20Full publication date if available
- Authors
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Omega John Unogwu, Mabel Ike, Opkanachi Omatule JoktanList of authors in order
- Landing page
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https://doi.org/10.58496/mjaih/2023/010Publisher landing page
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https://journals.mesopotamian.press/index.php/MJAIH/article/download/129/131Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://journals.mesopotamian.press/index.php/MJAIH/article/download/129/131Direct OA link when available
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Interpretability, Drug development, Risk analysis (engineering), Identification (biology), Clinical trial, Computer science, Transparency (behavior), Pharmacovigilance, Data science, Artificial intelligence, Drug, Medicine, Pharmacology, Computer security, Botany, Pathology, BiologyTop concepts (fields/topics) attached by OpenAlex
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15Total citation count in OpenAlex
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2025: 10, 2024: 3, 2023: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 8, 30, 107, 119, 164, 194, 205, 226 |
| abstract_inverted_index.(AI) | 2 |
| abstract_inverted_index.Data | 37 |
| abstract_inverted_index.Lead | 92 |
| abstract_inverted_index.This | 76, 158, 192 |
| abstract_inverted_index.aids | 162 |
| abstract_inverted_index.also | 150 |
| abstract_inverted_index.area | 42, 96 |
| abstract_inverted_index.been | 190 |
| abstract_inverted_index.data | 133, 178 |
| abstract_inverted_index.drug | 14, 111, 249 |
| abstract_inverted_index.find | 47 |
| abstract_inverted_index.from | 17 |
| abstract_inverted_index.into | 238 |
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| abstract_inverted_index.most | 120, 140 |
| abstract_inverted_index.must | 214 |
| abstract_inverted_index.past | 132 |
| abstract_inverted_index.role | 6 |
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| abstract_inverted_index.that | 138 |
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| abstract_inverted_index.after | 186 |
| abstract_inverted_index.data, | 63, 230 |
| abstract_inverted_index.data. | 75 |
| abstract_inverted_index.leads | 122 |
| abstract_inverted_index.model | 233 |
| abstract_inverted_index.plays | 3 |
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| abstract_inverted_index.saves | 77 |
| abstract_inverted_index.since | 101 |
| abstract_inverted_index.their | 126 |
| abstract_inverted_index.trial | 74, 153 |
| abstract_inverted_index.using | 246 |
| abstract_inverted_index.vital | 5 |
| abstract_inverted_index.where | 43, 97 |
| abstract_inverted_index.which | 86 |
| abstract_inverted_index.whole | 13 |
| abstract_inverted_index.decide | 85 |
| abstract_inverted_index.design | 154 |
| abstract_inverted_index.events | 181 |
| abstract_inverted_index.health | 66 |
| abstract_inverted_index.issues | 200 |
| abstract_inverted_index.likely | 141 |
| abstract_inverted_index.safety | 199, 207 |
| abstract_inverted_index.screen | 104 |
| abstract_inverted_index.taking | 237 |
| abstract_inverted_index.target | 18 |
| abstract_inverted_index.trials | 25 |
| abstract_inverted_index.account | 239 |
| abstract_inverted_index.adverse | 180 |
| abstract_inverted_index.analyse | 59 |
| abstract_inverted_index.another | 95 |
| abstract_inverted_index.certain | 146 |
| abstract_inverted_index.crucial | 41 |
| abstract_inverted_index.ethical | 240 |
| abstract_inverted_index.improve | 114, 151 |
| abstract_inverted_index.include | 225 |
| abstract_inverted_index.issues, | 241 |
| abstract_inverted_index.patient | 136, 156 |
| abstract_inverted_index.permits | 193 |
| abstract_inverted_index.quicker | 195 |
| abstract_inverted_index.respond | 143 |
| abstract_inverted_index.safety, | 116 |
| abstract_inverted_index.success | 160 |
| abstract_inverted_index.support | 171 |
| abstract_inverted_index.systems | 57 |
| abstract_inverted_index.targets | 52 |
| abstract_inverted_index.trends, | 48 |
| abstract_inverted_index.utilize | 219 |
| abstract_inverted_index.volumes | 61 |
| abstract_inverted_index.However, | 211 |
| abstract_inverted_index.academic | 70 |
| abstract_inverted_index.advances | 159 |
| abstract_inverted_index.analysis | 38 |
| abstract_inverted_index.assuring | 231 |
| abstract_inverted_index.clinical | 24, 73, 152 |
| abstract_inverted_index.efficacy | 108 |
| abstract_inverted_index.enabling | 82 |
| abstract_inverted_index.enormous | 60 |
| abstract_inverted_index.forecast | 106 |
| abstract_inverted_index.licensed | 209 |
| abstract_inverted_index.medicine | 188 |
| abstract_inverted_index.overcome | 216 |
| abstract_inverted_index.pathways | 89 |
| abstract_inverted_index.pinpoint | 135 |
| abstract_inverted_index.process, | 16 |
| abstract_inverted_index.records, | 67 |
| abstract_inverted_index.scanning | 176 |
| abstract_inverted_index.thrives. | 45 |
| abstract_inverted_index.compounds | 87 |
| abstract_inverted_index.detection | 196 |
| abstract_inverted_index.drug-drug | 184 |
| abstract_inverted_index.efficacy, | 115 |
| abstract_inverted_index.essential | 100 |
| abstract_inverted_index.examining | 131 |
| abstract_inverted_index.groupings | 137 |
| abstract_inverted_index.including | 64 |
| abstract_inverted_index.licensed. | 191 |
| abstract_inverted_index.molecular | 68 |
| abstract_inverted_index.obstacles | 213 |
| abstract_inverted_index.potential | 31, 198 |
| abstract_inverted_index.promising | 121 |
| abstract_inverted_index.resources | 80 |
| abstract_inverted_index.Artificial | 0 |
| abstract_inverted_index.algorithms | 102 |
| abstract_inverted_index.attributes | 127 |
| abstract_inverted_index.completely | 218 |
| abstract_inverted_index.continuous | 206 |
| abstract_inverted_index.databases, | 69 |
| abstract_inverted_index.electronic | 65 |
| abstract_inverted_index.frameworks | 244 |
| abstract_inverted_index.medication | 168, 222 |
| abstract_inverted_index.optimized. | 129 |
| abstract_inverted_index.real-world | 177 |
| abstract_inverted_index.regulatory | 243 |
| abstract_inverted_index.selection. | 157 |
| abstract_inverted_index.unexpected | 183 |
| abstract_inverted_index.candidates. | 112 |
| abstract_inverted_index.contributes | 202 |
| abstract_inverted_index.development | 9, 15, 165 |
| abstract_inverted_index.literature, | 71 |
| abstract_inverted_index.maintaining | 204 |
| abstract_inverted_index.medication, | 147 |
| abstract_inverted_index.monitoring, | 28 |
| abstract_inverted_index.prospective | 51 |
| abstract_inverted_index.requirement | 227 |
| abstract_inverted_index.researchers | 83 |
| abstract_inverted_index.therapeutic | 54 |
| abstract_inverted_index.continuously | 175 |
| abstract_inverted_index.development. | 223, 250 |
| abstract_inverted_index.high-quality | 229 |
| abstract_inverted_index.intelligence | 1 |
| abstract_inverted_index.interactions | 185 |
| abstract_inverted_index.investigate. | 91 |
| abstract_inverted_index.medications. | 210 |
| abstract_inverted_index.optimization | 22, 93 |
| abstract_inverted_index.personalized | 167 |
| abstract_inverted_index.prioritized, | 124 |
| abstract_inverted_index.surveillance | 173 |
| abstract_inverted_index.transparency | 234 |
| abstract_inverted_index.correlations, | 49 |
| abstract_inverted_index.intervention, | 55 |
| abstract_inverted_index.identification | 19 |
| abstract_inverted_index.post-marketing | 27, 172 |
| abstract_inverted_index.revolutionized | 34 |
| abstract_inverted_index.pharmaceuticals. | 11 |
| abstract_inverted_index.interpretability, | 236 |
| abstract_inverted_index.pharmacokinetics, | 118 |
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| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 3 |
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| citation_normalized_percentile.is_in_top_10_percent | True |