Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives
The integration of artificial intelligence into drug discovery processes represents a major innovation in pharmaceutical research and development. This study investigates the role of AI investments in enhancing research efficiency, addressing implementation challenges, and shaping stakeholder perspe...
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| Format: | Article |
| Language: | English |
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Academic Research and Publishing UG (i. G.)
2025-07-01
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| Series: | Health Economics and Management Review |
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| Online Access: | https://armgpublishing.com/wp-content/uploads/2025/07/HEM_2_2025_1.pdf |
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| author | Iakovos Kritikos Andreas Sarantopoulos Anastasios Roumeliotis Julia Vasiliades Ioannis Matsinas |
| author_facet | Iakovos Kritikos Andreas Sarantopoulos Anastasios Roumeliotis Julia Vasiliades Ioannis Matsinas |
| author_sort | Iakovos Kritikos |
| collection | DOAJ |
| description | The integration of artificial intelligence into drug discovery processes represents a major innovation in pharmaceutical research and development. This study investigates the role of AI investments in enhancing research efficiency, addressing implementation challenges, and shaping stakeholder perspectives. Via a structured explanatory research design, the study applies a quantitative methodology based on survey data collected from researchers, investors, and pharmaceutical executives across the USA and United Kingdom. The questionnaire examined respondents’ experiences with artificial intelligence tools, investment patterns, and perceived research outcomes. Statistical methods such as logistic regression and chi-square tests were employed to analyze correlations between investment strategies and research efficiency. Findings indicate that while artificial intelligence improves productivity – in predictive modeling and data analysis – barriers such as high infrastructure costs, inadequate training, and regulatory uncertainty persist. Notably, 70% of participants plan to increase AI investments within the next five years, and 80% regard artificial intelligence as essential or very important to the future of drug discovery. However, successful implementation appears to correlate with firm size and access to technical resources, suggesting disparities in AI readiness across the industry. Recommendations include expanding artificial intelligence training programs, strengthening infrastructure, and fostering closer collaboration between investors and researchers. Ethical considerations, including data privacy and regulatory compliance, are also emphasized. The pilot study provides foundational insights for a full-scale investigation and offers practical guidance for optimizing artificial intelligence integration in pharmaceutical research and development. |
| format | Article |
| id | doaj-art-b84e9288ffa841e18b933ee1725b6355 |
| institution | Kabale University |
| issn | 2786-4626 2786-4634 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Academic Research and Publishing UG (i. G.) |
| record_format | Article |
| series | Health Economics and Management Review |
| spelling | doaj-art-b84e9288ffa841e18b933ee1725b63552025-08-20T03:51:29ZengAcademic Research and Publishing UG (i. G.)Health Economics and Management Review2786-46262786-46342025-07-016211610.61093/hem.2025.2-01Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher PerspectivesIakovos Kritikos0https://orcid.org/0000-0003-3861-6268Andreas Sarantopoulos1https://orcid.org/0009-0001-1390-6472Anastasios Roumeliotis2https://orcid.org/0000-0002-4493-2374Julia Vasiliades3https://orcid.org/0009-0004-2245-7949Ioannis Matsinas4https://orcid.org/0009-0000-8520-3664MSc, MRes, MEM, DBA(c), Global Business School for Health, University College London (UK)MD, Medical School; European University Cyprus, Nicosia (Cyprus)MD, Mount Auburn Hospital, Cambridge, MA (USA)BS, Northeastern University College of Engineering; MA (USA)HULT International Business School, MA (USA)The integration of artificial intelligence into drug discovery processes represents a major innovation in pharmaceutical research and development. This study investigates the role of AI investments in enhancing research efficiency, addressing implementation challenges, and shaping stakeholder perspectives. Via a structured explanatory research design, the study applies a quantitative methodology based on survey data collected from researchers, investors, and pharmaceutical executives across the USA and United Kingdom. The questionnaire examined respondents’ experiences with artificial intelligence tools, investment patterns, and perceived research outcomes. Statistical methods such as logistic regression and chi-square tests were employed to analyze correlations between investment strategies and research efficiency. Findings indicate that while artificial intelligence improves productivity – in predictive modeling and data analysis – barriers such as high infrastructure costs, inadequate training, and regulatory uncertainty persist. Notably, 70% of participants plan to increase AI investments within the next five years, and 80% regard artificial intelligence as essential or very important to the future of drug discovery. However, successful implementation appears to correlate with firm size and access to technical resources, suggesting disparities in AI readiness across the industry. Recommendations include expanding artificial intelligence training programs, strengthening infrastructure, and fostering closer collaboration between investors and researchers. Ethical considerations, including data privacy and regulatory compliance, are also emphasized. The pilot study provides foundational insights for a full-scale investigation and offers practical guidance for optimizing artificial intelligence integration in pharmaceutical research and development.https://armgpublishing.com/wp-content/uploads/2025/07/HEM_2_2025_1.pdfartificial intelligencedrug discoverytechnology investmentsresearch efficiencylarge pharmaceutical companieshealthcare; health tech |
| spellingShingle | Iakovos Kritikos Andreas Sarantopoulos Anastasios Roumeliotis Julia Vasiliades Ioannis Matsinas Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives Health Economics and Management Review artificial intelligence drug discovery technology investments research efficiency large pharmaceutical companies healthcare; health tech |
| title | Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives |
| title_full | Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives |
| title_fullStr | Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives |
| title_full_unstemmed | Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives |
| title_short | Unlocking the Potential of Artificial Intelligence in Pharma Research and Development: Insights from Investor and Researcher Perspectives |
| title_sort | unlocking the potential of artificial intelligence in pharma research and development insights from investor and researcher perspectives |
| topic | artificial intelligence drug discovery technology investments research efficiency large pharmaceutical companies healthcare; health tech |
| url | https://armgpublishing.com/wp-content/uploads/2025/07/HEM_2_2025_1.pdf |
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