Keywords
clinical trials
drug discovery
drug development
optimization
patient recruitment
trial design
data analysis
regulatory compliance
How to Cite
Abstract
Clinical trials are a critical component of the drug discovery and development process, yet they are often plagued by inefficiencies and high costs. Artificial intelligence (AI) offers a promising solution to optimize clinical trials, improving efficiency, reducing costs, and accelerating the delivery of new therapies to patients. This paper explores the application of AI algorithms in optimizing the design and execution of clinical trials, highlighting their potential to transform the pharmaceutical industry's approach to drug discovery and development. We discuss key AI-driven approaches, including patient recruitment, trial design, data analysis, and regulatory compliance. Case studies and examples are presented to illustrate the benefits of AI in streamlining clinical trial processes and enhancing the success rates of new therapies.
References
Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
Maruthi, Srihari, et al. "Deconstructing the Semantics of Human-Centric AI: A Linguistic Analysis." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 11-30.
Dodda, Sarath Babu, et al. "Ethical Deliberations in the Nexus of Artificial Intelligence and Moral Philosophy." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 31-43.
Zanke, Pankaj, and Dipti Sontakke. "Leveraging Machine Learning Algorithms for Risk Assessment in Auto Insurance." Journal of Artificial Intelligence Research 1.1 (2021): 21-39.
Biswas, A., and W. Talukdar. “Robustness of Structured Data Extraction from In-Plane Rotated Documents Using Multi-Modal Large Language Models (LLM)”. Journal of Artificial Intelligence Research, vol. 4, no. 1, Mar. 2024, pp. 176-95, https://thesciencebrigade.com/JAIR/article/view/219.
Maruthi, Srihari, et al. "Toward a Hermeneutics of Explainability: Unraveling the Inner Workings of AI Systems." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 27-44.
Biswas, Anjanava, and Wrick Talukdar. "Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation." arXiv preprint arXiv:2405.18346 (2024).
Ponnusamy, Sivakumar. "Evolution of Enterprise Data Warehouse: Past Trends and Future Prospects."
Umar, Muhammad, et al. "Role of Deep Learning in Diagnosis, Treatment, and Prognosis of Oncological Conditions." International Journal 10.5 (2023): 1059-1071.
Yellu, Ramswaroop Reddy, et al. "AI Ethics-Challenges and Considerations: Examining ethical challenges and considerations in the development and deployment of artificial intelligence systems." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 9-16.
Maruthi, Srihari, et al. "Automated Planning and Scheduling in AI: Studying automated planning and scheduling techniques for efficient decision-making in artificial intelligence." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 14-25.
Biswas, Anjanava, and Wrick Talukdar. "FinEmbedDiff: A Cost-Effective Approach of Classifying Financial Documents with Vector Sampling using Multi-modal Embedding Models." arXiv preprint arXiv:2406.01618 (2024).
Singh, Amarjeet, and Alok Aggarwal. "A Comparative Analysis of Veracode Snyk and Checkmarx for Identifying and Mitigating Security Vulnerabilities in Microservice AWS and Azure Platforms." Asian Journal of Multidisciplinary Research & Review 3.2 (2022): 232-244.
Zanke, Pankaj. "Enhancing Claims Processing Efficiency Through Data Analytics in Property & Casualty Insurance." Journal of Science & Technology 2.3 (2021): 69-92.
Talukdar, Wrick, and Anjanava Biswas. "Synergizing Unsupervised and Supervised Learning: A Hybrid Approach for Accurate Natural Language Task Modeling." arXiv preprint arXiv:2406.01096 (2024).
Pulimamidi, R., and G. P. Buddha. "AI-Enabled Health Systems: Transforming Personalized Medicine And Wellness." Tuijin Jishu/Journal of Propulsion Technology 44.3: 4520-4526.
Dodda, Sarath Babu, et al. "Conversational AI-Chatbot Architectures and Evaluation: Analyzing architectures and evaluation methods for conversational AI systems, including chatbots, virtual assistants, and dialogue systems." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 13-20.
Gupta, Pankaj, and Sivakumar Ponnusamy. "Beyond Banking: The Trailblazing Impact of Data Lakes on Financial Landscape." International Journal of Computer Applications 975: 8887.
Maruthi, Srihari, et al. "Language Model Interpretability-Explainable AI Methods: Exploring explainable AI methods for interpreting and explaining the decisions made by language models to enhance transparency and trustworthiness." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 1-9.
Biswas, Anjan. "Media insights engine for advanced media analysis: A case study of a computer vision innovation for pet health diagnosis." International Journal of Applied Health Care Analytics 4.8 (2019): 1-10.
Dodda, Sarath Babu, et al. "Federated Learning for Privacy-Preserving Collaborative AI: Exploring federated learning techniques for training AI models collaboratively while preserving data privacy." Australian Journal of Machine Learning Research & Applications 2.1 (2022): 13-23.
Maruthi, Srihari, et al. "Temporal Reasoning in AI Systems: Studying temporal reasoning techniques and their applications in AI systems for modeling dynamic environments." Journal of AI-Assisted Scientific Discovery 2.2 (2022): 22-28.
Yellu, Ramswaroop Reddy, et al. "Transferable Adversarial Examples in AI: Examining transferable adversarial examples and their implications for the robustness of AI systems." Hong Kong Journal of AI and Medicine 2.2 (2022): 12-20.
Reddy Yellu, R., et al. "Transferable Adversarial Examples in AI: Examining transferable adversarial examples and their implications for the robustness of AI systems. Hong Kong Journal of AI and Medicine, 2 (2), 12-20." (2022).
Pulimamidi, Rahul. "To enhance customer (or patient) experience based on IoT analytical study through technology (IT) transformation for E-healthcare." Measurement: Sensors (2024): 101087.
Ponnusamy, Sivakumar, and Pankaj Gupta. "Connecting the Dots: How Data Lineage Helps in Effective Data Governance."
Senthilkumar, Sudha, et al. "SCB-HC-ECC–based privacy safeguard protocol for secure cloud storage of smart card–based health care system." Frontiers in Public Health 9 (2021): 688399.
Singh, Amarjeet, Vinay Singh, and Alok Aggarwal. "Improving the Application Performance by Auto-Scaling of Microservices in a Containerized Environment in High Volumed Real-Time Transaction System." International Conference on Production and Industrial Engineering. Singapore: Springer Nature Singapore, 2023.