Enhancing Clinical Translation of Cancer Using Nanoinformatics

Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recen...
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Gespeichert in:

Autor*in:	Madjid Soltani [verfasserIn] Farshad Moradi Kashkooli [verfasserIn] Mohammad Souri [verfasserIn] Samaneh Zare Harofte [verfasserIn] Tina Harati [verfasserIn] Atefeh Khadem [verfasserIn] Mohammad Haeri Pour [verfasserIn] Kaamran Raahemifar [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	drug delivery nanomedicine artificial intelligence machine learning deep learning nanoinformatics

Übergeordnetes Werk:	In: Cancers - MDPI AG, 2010, 13(2021), 10, p 2481
Übergeordnetes Werk:	volume:13 ; year:2021 ; number:10, p 2481

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/cancers13102481

Katalog-ID:	DOAJ057400172

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callnumber-first	R - Medicine
author	Madjid Soltani
spellingShingle	Madjid Soltani misc RC254-282 misc drug delivery misc nanomedicine misc artificial intelligence misc machine learning misc deep learning misc nanoinformatics misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens Enhancing Clinical Translation of Cancer Using Nanoinformatics
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topic_title	RC254-282 Enhancing Clinical Translation of Cancer Using Nanoinformatics drug delivery nanomedicine artificial intelligence machine learning deep learning nanoinformatics
topic	misc RC254-282 misc drug delivery misc nanomedicine misc artificial intelligence misc machine learning misc deep learning misc nanoinformatics misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_unstemmed	misc RC254-282 misc drug delivery misc nanomedicine misc artificial intelligence misc machine learning misc deep learning misc nanoinformatics misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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title	Enhancing Clinical Translation of Cancer Using Nanoinformatics
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title_auth	Enhancing Clinical Translation of Cancer Using Nanoinformatics
abstract	Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, <i<i.e.</i<, nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.
abstractGer	Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, <i<i.e.</i<, nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.
abstract_unstemmed	Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, <i<i.e.</i<, nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients.
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title_short	Enhancing Clinical Translation of Cancer Using Nanoinformatics
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