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20 articles for “Machine Learning in Pharmaceuticals”
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Flora-Vision: A Quality Assurance System For The Pharmaceutical Industry
Abstract: In contemporary pharmaceutical production, the persistent challenges of manual labor, human error, and contamination risks pose significant obstacles to efficiency and product quality. Particularly in sectors such as Ayurvedic products, cosmetics, and medicines, the need for innovation is pressing. Revolution in production process can be addressed by introducing innovative solutions and thereby challenges could be overcome. Through the utilization of advanced technology, the proposed system streamlines sample management and quality …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 3, 2024 · pp. 53–60 Read article
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AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article
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Future Prospects of AI in Pharmaceutical Industry and its Limitation
Abstract: The pharmaceutical industry is facing significant challenges, including prolonged drug development timelines, high costs, and low success rates in clinical trials. Traditional methods often result in inefficiencies, with new drug development taking over a decade and billions of dollars, yet most candidates fail in clinical trials due to issues like inefficacy or safety concerns. Artificial Intelligence (AI) has become a groundbreaking technology with the potential to tackle these issues effectively. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 6–13 Read article
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Accelerating Drug Discovery with AI: Transforming the Pharmaceutical Pipeline
Abstract: The revolutionary potential of artificial intelligence (AI) is examined in this essay the pharmaceutical industry, highlighting its application across the drug development lifecycle. Artificial Intelligence, specifically via deep learning models and machine learning (ML) such as GANs, RNNs, and transformers, enhances drug discovery, formulation, toxicity prediction, and clinical trials. It streamlines processes like identification of targets, virtual screening, modelling of structure-activity relationships, and medication repurposing. AI is also employed in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 77–84 Read article
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QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Using Artificial Intelligence for The Design of Polymeric Drug Delivery Systems
Abstract: AI is cost effective and time efficient process. Artificial intelligence is a method which uses high speed calculation, the improvement regarding algorithm along with collection about biological and chemical features in pharmaceutical exploration and development .Present day because continuous progress towards machine learning (ML),Artificial intelligence an effective statistics analysing technology might have been broadly utilized in drug design .In pharmaceutical exploration and research employ of AI in target identification, compound …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1018–1027 Read article
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The Impact of Artificial Intelligence on the Sales and Marketing of Pharmaceutical Products
Abstract: The rapid development of computing and technology has permeated all branches of science, with artificial intelligence (AI) emerging as a pivotal field in computer science. AI has significantly influenced disciplines ranging from basic engineering to pharmaceuticals. In healthcare and medicinal chemistry, AI applications have become indispensable. Traditional drug discovery approaches are gradually being overtaken by computer-aided drug design. In recent years, artificial intelligence (AI) and machine learning (ML) have become …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 · pp. 10–18 Read article
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Pharmacovigilance and drug safety current trends and challenges
Abstract: Pharmacovigilance and drug safety are critical areas of focus in healthcare, aimed at monitoring the safety and efficacy of pharmaceutical products throughout their lifecycle. This review explores current trends, emerging technologies, and challenges in pharmacovigilance, emphasizing their impact on public health and regulatory practices. With the increasing complexity of global pharmaceutical markets, pharmacovigilance systems are evolving to integrate real-time data analytics, artificial intelligence (AI), and machine learning (ML) to detect …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 19–27 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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Polymer Nanocomposites As Emerging Platforms in Pharmaceutical Nanotechnology
Abstract: Nanotechnology allows the handling of materials in the 1–100 nm range, where distinct physicochemical phenomena, including quantum effects and higher surface-to-volume ratio, enable disruptive uses in pharmaceuticals and biomedicine. Significant challenges in solubility, stability and targeted biodistribution of therapeutics can be overcome by incorporating nanostructured polymers and polymer-based composites into drug delivery systems. PLGA nanoparticle and other nanocarriers, such as PLGA micelles, dendrimers, and hydrogels, have revealed promising effects on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 268–278 Read article
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Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
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AI Powered Invention in Pharmaceuticals Boosting Innovation
Abstract: Artificial intelligence has the potential to transform the drug discovery process, making the process more efficient, accurate and faster. But the success of artificial intelligence depends on the availability of good data, resolution of ethical issues, and awareness of the limitations of artificial intelligencebased methods. The present article examined the benefits, challenges, and shortcomings of skills in the workplace and suggested strategies and practical actions to overcome current challenges. Data …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 102–107 Read article
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Advances in Stimuli-Responsive Smart Drug Delivery Systems: A Systematic Review
Abstract: Imagine a world where medicines work smarter, not harder. Stimuli-responsive drug delivery systems (SRDDS) are transforming healthcare by releasing therapeutic agents in response to specific triggers. These triggers can be internal, like changes in pH or temperature, or external, like light or magnetic fields. By leveraging these triggers, SRDDS can optimize treatment and minimize side effects. The potential applications of SRDDS are vast, from cancer treatment to gene delivery and …
Published in Trends in Drug Delivery · Vol. 13, Issue 2, 2026 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Pharma Tech: Leveraging Software for Drug Development & Clinical Research
Abstract: The pharmaceutical sector is progressively adopting software solutions to enhance the drug development process and optimize clinical research results. Drug development is a time-consuming, expensive, and intricate process that traditionally requires extensive laboratory research, preclinical testing, and several stages of clinical trials. Software tools are revolutionizing these stages by improving efficiency, minimizing errors, and speeding up timelines. During preclinical testing, predictive software tools are used to model toxicological effects and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 11–19 Read article
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Advanced Water Purification Techniques for Sustainable Clean Water Management: A Comprehensive Review
Abstract: The growing global demand for safe drinking water, coupled with increasing pollution from industrialization, urbanization, and agricultural activities, has intensified the need for efficient and sustainable water purification technologies. Conventional water treatment processes often fail to remove emerging contaminants such as pharmaceuticals, microplastics, endocrine-disrupting compounds, and heavy metals. Advanced water purification technologies—including membrane filtration, advanced oxidation processes (AOPs), nanotechnology-based adsorbents, photocatalysis, electrochemical treatment, and bio-inspired purification systems—have emerged as promising …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 47–52 Read article