Artificial Intelligence Integration in Nanobionic Systems: New Approaches for Toxicology and Medical Applications

Öz

This report addresses the systemic reshaping effects on modern medicine, ranging from the "Bio-Nano-Cyber Convergence" paradigm—which represents the convergence of common knowledge areas such as artificial intelligence (AI), nanotechnology, and biomedical sciences—to cyber-biological security risks posed by neural interfaces based on the "Bio-Nano-Nano Internet of Things" (IoBNT) architecture to cyber-biological security risks posed by neural interfaces. The study carefully examines the systemic reshaping effects on modern medicine, based on the latest data in the literature. The research highlights how deep machine learning approaches have radically improved drug discovery processes and molecular design studies, the transformation caused by systems such as AlphaFold in structural biology, the high-precision monitoring provided by nanobionic sensors in environmental and clinical toxicology, and the impact of "in silico" prediction models (QSAR/Nano-SAR) in identifying "silent toxicity" risks. It also examines how the therapeutic opportunities offered by wireless brain-computer interfaces such as "Neural Dust" can be made compatible with extraordinary ethical and security threats such as "single-pixel attacks," "brain hijacking," and the "nano-abyss" from a "One Health" perspective.

Anahtar Kelimeler

• Bio-Nano-Cyber Convergence; AI-Driven Drug Discovery
• Nanobionic Toxicology; Internet of Bio-Nano Things (IoBNT)
• Cyber Biosecurity
• Neural Dust
• One Health

Nanobiyonik Sistemlerde Yapay Zeka Entegrasyonu: Toksikoloji ve Tıbbi Uygulamalar için Yeni Yaklaşımlar

Öz

Bu rapor, yapay zeka (AI), nanoteknoloji ve biyomedikal bilimler gibi ortak bilgi alanlarının birleşimini ifade eden "Biyo-Nano-Siber Yakınsama" paradigmasını ve bunun ilaç geliştirme endüstrisinden nanobiyonik toksikolojiye, "Biyo-Nano-Nano Nesnelerin İnterneti" (IoBNT) mimarisinden sinirsel arayüzlerin oluşturduğu siber-biyolojik güvenlik risklerine kadar uzanan modern tıp üzerindeki sistem yeniden şekillendirme etkilerini, literatürdeki en son veriler ışığında dikkatle incelemektedir. Araştırma, derin makine öğrenimi yaklaşımlarının ilaç keşif süreçlerini ve moleküler tasarım çalışmalarını nasıl radikal bir şekilde iyileştirdiğini, AlphaFold gibi sistemlerin yapısal biyolojide neden olduğu dönüşümü, çevresel ve klinik toksikolojide nanobiyonik sensörlerin sağladığı yüksek hassasiyetli izlemeyi ve "sessiz toksisite" risklerini belirlemede "in silico" tahmin modellerinin (QSAR/Nano-SAR) etkisini ortaya koymaktadır. Ayrıca, "Neural Dust" gibi kablosuz beyin-bilgisayar arayüzlerinin sunduğu terapötik fırsatların, "tek piksel saldırıları", "beyin kaçırma" ve "nano uçurum" gibi olağanüstü etik ve güvenlik tehditleriyle "Tek Sağlık" perspektifinden nasıl uyumlu hale getirilmesi gerektiğini incelemektedir.

Anahtar Kelimeler

• Biyo-Nano-Siber Yakınsama
• AI Odaklı İlaç Keşfi; Nanobiyonik Toksikoloji
• Biyo-Nano Nesnelerin İnterneti (IoBNT
• Siber Biyogüvenlik; Neural Dust
• Tek Sağlık

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