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ONCOLOGY, NUCLEAR MEDICINE AND TRANSPLANTOLOGY
Review Article
Apr 01, 2026 2 2

Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development

Kehinde Oluwagbenga Falayi 1,
Ome Valentina Akpughe 2,
Kazeem Enitan Bello 3,
Raphael Adebomi Adewale 4,
Bright Kofi Ladzro 5,
Oluwatoyin Aanu Ayeni 6 *
1 Department of Medicine, Obafemi Awolowo University, Ile-Ife, Nigeria2 Department of Health Informatics, University of Science and Technology, Harrisburg, PA, USA3 Department of Computer Science, University of Hull, Hull, UK4 Department of Computer Science, University of Pittburgh, PA, USA5 Department of Mathematics and Statistics, American University, Washington, DC, USA6 Department of Social Works, University of Ibadan, Ibadan, Nigeria* Corresponding Author
Oncology, Nuclear Medicine and Transplantology, 2(1), 2026, onmt015, https://doi.org/10.63946/onmt/18289
Publication date: Apr 01, 2026
Full Text (PDF)

ABSTRACT

Precision medicine aims to deliver the right treatment to the right patient at the right time, yet its widespread clinical adoption remains limited by challenges in accurate diagnosis, slow drug development processes and the difficulty of translating complex biological data into actionable clinical decisions. Conventional diagnostic and therapeutic approaches often rely on population averages, which can overlook individual genetic, molecular and clinical differences, leading to variable treatment responses and high drug development failure rates. In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have gained increasing attention as clinical support tools capable of analyzing complex and large-scale biomedical data, improving diagnostic accuracy, accelerating drug development and enabling more personalized approaches to patient care. This study presents a systematic literature review conducted in accordance with the PRISMA guidelines, examining recent evidence on how AI and ML act as catalysts for precision medicine, particularly in diagnosis and drug development. Peer-reviewed studies published between 2019 and 2025 were systematically identified from major academic databases and screened using predefined inclusion and exclusion criteria. The selected studies were analyzed to assess clinical applications, AI techniques employed and their implications for personalized healthcare and pharmaceutical innovation. The findings indicate that AI and ML significantly enhance diagnostic accuracy through applications in medical imaging, genomics and electronic health record analysis, supporting earlier and more precise disease detection. In drug development, AI-driven methods improve target identification, lead optimization, toxicity prediction and clinical trial design, contributing to reduced development time and cost. Furthermore, the integration of multi-omics and clinical data through AI enables more personalized treatment strategies, improving therapeutic selection and dosing. This study concludes that AI and ML are powerful catalysts for precision medicine and capable of bridging the gap between complex biomedical data and clinical decision-making. With appropriate validation, explainable models and robust ethical and regulatory frameworks, these technologies have the potential to accelerate drug development and support clinicians in delivering more accurate diagnoses, more effective treatments and safer patient-centered, precision-based healthcare.

KEYWORDS

Artificial intelligence (AI) Machine Learning (ML) Precision Medicine Diagnosis Drug Development

CITATION (Vancouver)

Falayi KO, Akpughe OV, Bello KE, Adewale RA, Ladzro BK, Ayeni OA. Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development. Oncology, Nuclear Medicine and Transplantology. 2026;2(1):onmt015. https://doi.org/10.63946/onmt/18289
APA
Falayi, K. O., Akpughe, O. V., Bello, K. E., Adewale, R. A., Ladzro, B. K., & Ayeni, O. A. (2026). Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development. Oncology, Nuclear Medicine and Transplantology, 2(1), onmt015. https://doi.org/10.63946/onmt/18289
Harvard
Falayi, K. O., Akpughe, O. V., Bello, K. E., Adewale, R. A., Ladzro, B. K., and Ayeni, O. A. (2026). Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development. Oncology, Nuclear Medicine and Transplantology, 2(1), onmt015. https://doi.org/10.63946/onmt/18289
AMA
Falayi KO, Akpughe OV, Bello KE, Adewale RA, Ladzro BK, Ayeni OA. Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development. Oncology, Nuclear Medicine and Transplantology. 2026;2(1), onmt015. https://doi.org/10.63946/onmt/18289
Chicago
Falayi, Kehinde Oluwagbenga, Ome Valentina Akpughe, Kazeem Enitan Bello, Raphael Adebomi Adewale, Bright Kofi Ladzro, and Oluwatoyin Aanu Ayeni. "Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development". Oncology, Nuclear Medicine and Transplantology 2026 2 no. 1 (2026): onmt015. https://doi.org/10.63946/onmt/18289
MLA
Falayi, Kehinde Oluwagbenga et al. "Artificial Intelligence and Machine Learning as Catalysts for Precision Medicine: Implications for Diagnosis and Drug Development". Oncology, Nuclear Medicine and Transplantology, vol. 2, no. 1, 2026, onmt015. https://doi.org/10.63946/onmt/18289

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