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66 articles for “oncology”
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
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Biopolymer-Based 3D Composite Scaffolds for Bone Tissue Engineering: Photothermal-Responsive Systems with Controlled Pt (IV) Prodrug Release
Abstract: Biopolymer-based composite scaffolds have attracted significant attention as multifunctional platforms at the intersection of polymer science, regenerative medicine, and cancer nanotherapy. In this study, a dual-functional scaffold was developed for simultaneous osteosarcoma treatment and bone regeneration using poly (L-lactic acid) (PLLA) reinforced with bioactive glass (BG) and integrated with a glutathione-responsive platinum (IV) prodrug system (PDA@Pt). To improve interfacial adhesion, photothermal conversion efficiency, and tumor-specific activation, the Pt (IV) prodrug …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 351–361 Read article
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Non-Small Cell Lung Cancer: Types, Pathogenesis, Diagnosis, and Novel Therapeutic Strategies
Abstract: Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer, accounting for over 85% of all cases globally. It remains one of the primary causes of cancer-related death due to its rapid progression, few early symptoms, and late detection. The three main forms of non-small cell lung cancer (NSCLC) are adenocarcinoma, squamous cell carcinoma, and giant cell carcinoma; each has a unique histology, prognosis, and response to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Cancer Chronicles: An Overview of its Origins, Types, Treatment, and Prevention
Abstract: Cancer is a multifaceted illness characterized by abnormal cell growth and dissemination throughout the body. Its onset usually arises from a mix of genetic mutations and environmental factors. There exist more than 100 distinct forms of cancer, each possessing unique attributes, risk elements, and therapeutic alternatives. Cancer is a pervasive health challenge that knows no boundaries of age, race, or background, continuing to rank among the foremost causes of mortality …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 36–42 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article