A comprehensive review of key factors affecting the efficacy of antibody drug conjugate

Biomedicine & Pharmacotherapy, Journal Year: 2023, Volume and Issue: 161, P. 114408 - 114408

Published: Feb. 24, 2023

Antibody Drug Conjugate (ADC) is an emerging technology to overcome the limitations of chemotherapy by selectively targeting cancer cells. ADC binds with antigen, specifically over expressed on surface cells, results decrease in bystander effect and increase therapeutic index. The potency ideal entirely depending several physicochemical factors such as site conjugation, molecular weight, linker length, Steric hinderance, half-life, conjugation method, binding energy so on. Inspite fact that there more than 100 ADCs are clinical trial only 14 approved FDA for use. However, design still challenging much be done. Here this review, we have discussed key components along their significant role or contribution towards efficacy ADC. Moreover, also explained about recent advancement method. Additionally, spotlit mode action ADC, challenges, future perspective regarding profound knowledge properties will help synthesis production different engineered ADCs. Therefore, contributes develop low safety concern high We hope review improve understanding encourage practicing research anticancer development.

Language: Английский

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Tribulations and future opportunities for artificial intelligence in precision medicine

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: April 30, 2024

Abstract Upon a diagnosis, the clinical team faces two main questions: what treatment, and at dose? Clinical trials' results provide basis for guidance support official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate reported response from relevant trials. The decision complexity increases with combination treatments where drugs administered together can interact each other, which is often case. Additionally, individual's treatment varies changes in condition. In practice, drug dose selection depend significantly on medical protocol team's experience. As such, are inherently varied suboptimal. Big data Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit application. AI rapidly evolving dynamic field potential revolutionize various aspects of human life. has become increasingly crucial discovery development. enhances across different disciplines, such medicinal chemistry, molecular cell biology, pharmacology, pathology, practice. addition these, contributes patient population stratification. need healthcare evident it aids enhancing accuracy ensuring quality care necessary effective treatment. pivotal improving success rates increasing significance discovery, development, trials underscored by many scientific publications. Despite numerous advantages AI, advancing Precision Medicine (PM) remote monitoring, unlocking its full requires addressing fundamental concerns. These concerns include quality, lack well-annotated large datasets, privacy safety issues, biases algorithms, legal ethical challenges, obstacles related cost implementation. Nevertheless, integrating medicine will improve diagnostic outcomes, contribute more efficient delivery, reduce costs, facilitate better experiences, making sustainable. This article reviews applications development sustainable, highlights limitations applying AI.

Language: Английский

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Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Feb. 5, 2024

Abstract Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical from diagnostic domains such as clinical imaging, pathology, next-generation sequencing (NGS), which help characterize individual differences patients. However, this information needs to be available suitable promote support scientific research technological development, supporting the effective adoption precision medicine approach practice. Digital biobanks can catalyze process, facilitating sharing curated standardized imaging data, clinical, pathological molecular crucial enable development comprehensive personalized data-driven disease management fostering predictive models. This work aims frame perspective, first by evaluating state standardization then identifying challenges proposing possible solution towards an integrative that guarantee suitability shared through digital biobank. Our analysis art shows presence use reference standards and, generally, repositories for each specific domain. Despite this, integration reproducibility numerical descriptors generated domain, e.g. radiomic, pathomic -omic features, is still open challenge. Based on cases scenarios, model, based JSON format, proposed address problem. Ultimately, how, with promotion efforts, biobank model become enabling technology study diseases technologies at service medicine.

Language: Английский

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Network-based drug repurposing identifies small molecule drugs as immune checkpoint inhibitors for endometrial cancer

Molecular Diversity, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 16, 2024

Language: Английский

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Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening‐based approaches

Journal of Medical Virology, Journal Year: 2023, Volume and Issue: 95(4)

Published: March 22, 2023

Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% all known human cancers. Due to large number patients, efficient treatments are needed. De novo drug discovery time consuming expensive process with high failure rate in clinical stages. To address this problem provide patients suffering from faster, repurposing emerges as an effective alternative which aims find the other indications Food Drug Administration approved drugs. Applied cancers, studies following niche have tried if already existing drugs could be used treat Multiple approaches till date been introduced successful results many successfully repurposed various Here study, a critical review cancer related databases, tools, different machine learning, deep learning virtual screening-based focusing on provided. Additionally, mechanism presented along case study specific each cancer. Finally, limitations challenges possible solutions

Language: Английский

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A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Journal of Biomedical Informatics, Journal Year: 2023, Volume and Issue: 142, P. 104373 - 104373

Published: April 27, 2023

Cancer is the second leading cause of death globally, trailing only heart disease. In United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, success rate drug development remains less than 10%, making disease particularly challenging. This low largely attributed to complex poorly understood nature etiology. Therefore, it critical find alternative approaches understanding biology developing effective treatments. One such approach repurposing, which offers a shorter timeline lower costs while increasing likelihood success. this review, we provide comprehensive analysis computational biology, including systems multi-omics, pathway analysis. Additionally, examine use these methods repurposing in cancer, databases tools that are used research. Finally, present case studies discussing their limitations offering recommendations future research area.

Language: Английский

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Revolutionizing drug development: harnessing the potential of organ-on-chip technology for disease modeling and drug discovery

Frontiers in Pharmacology, Journal Year: 2023, Volume and Issue: 14

Published: April 25, 2023

The inefficiency of existing animal models to precisely predict human pharmacological effects is the root reason for drug development failure. Microphysiological system/organ-on-a-chip technology (organ-on-a-chip platform) a microfluidic device cultured with living cells under specific organ shear stress which can faithfully replicate organ-body level pathophysiology. This emerging organ-on-chip platform be remarkable alternative broad range purposes in testing and precision medicine. Here, we review parameters employed using on chip as plot mimic diseases, genetic disorders, toxicity different organs, biomarker identification, discoveries. Additionally, address current challenges that should overcome accepted by regulatory agencies pharmaceutical industries. Moreover, highlight future direction enhancing accelerating discoveries personalized

Language: Английский

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Brain tumor detection with integrating traditional and computational intelligence approaches across diverse imaging modalities - Challenges and future directions

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 175, P. 108412 - 108412

Published: April 16, 2024

Language: Английский

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Single-cell atlas reveals multi-faced responses of losartan on tubular mitochondria in diabetic kidney disease

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: Jan. 21, 2025

Mitochondria are crucial to the function of renal tubular cells, and their dynamic perturbation in many aspects is an important mechanism diabetic kidney disease (DKD). Single-nucleus RNA sequencing (snRNA-seq) technology a high-throughput analysis technique for at level single cell nucleus. Here, our DKD mouse single-cell conveys more comprehensive mitochondrial profile, which helps us further understand therapeutic response this unique organelle family drugs. After high fat diet (HFD), mice were intraperitoneally injected with streptozotocin (STZ) induce DKD, then divided into three subsets: CON (healthy) subset, (vehicle) LST (losartan; 25 mg/kg/day) subset. Divide HK-2 LG (low glucose; 5 mM) HG (high 30 + 1 µ M) subsets. snRNA-seq was performed on tissues subset mice. To reveal effects losartan gene pathway changes mitochondria, Gene Ontology (GO) enrichment GSEA/GSVA scoring analyze specific proximal (PT) mitochondria treatment, including key events homeostasis such as morphology, dynamics, mitophagy, autophagic flux, respiratory chain, apoptosis, ROS generation. Preliminary validation through vitro vivo experiments, observation morphology dynamics using probes Mitotracker Red, evaluation effect electron microscopy, laser confocal immunofluorescence, Western blotting. Detection flux cells by transfecting Ad-mCherry-GFP-LC3B dual fluorescence labeled adenovirus. Various fluorescent energy detector used detect ROS, respiration mitochondrion. Through atlas kidneys, it found that treatment significantly increased percentage PT cells. differentially expressed genes showed autophagy mitochondrion pathway. Further GSEA GSVA revealed mitophagy other events, production, membrane potential, adenosine triphosphate (ATP) synthesis, involved protective thereby improving homeostasis. Consistent results also obtained cellular experiments. In addition, we highlighted subpopulation phenotype data, preliminarily validated co-localization expression Pink1 Gclc specimens patients treated losartan. Our research suggests scRNA-seq can reflect multifaceted landscape after drug these findings may provide new targets therapy level.

Language: Английский

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Drug repurposing in psoriasis, performed by reversal of disease-associated gene expression profiles

Computational and Structural Biotechnology Journal, Journal Year: 2022, Volume and Issue: 20, P. 6097 - 6107

Published: Jan. 1, 2022

Psoriasis is a skin disease which results in scales on the caused by flaky patches. triggered various conditions such as drug reactions, trauma, and infection etc. Globally, there are 125 million people affected psoriasis yet no effective treatment available, it emphasizes need for discovery of efficacious treatments. De-novo development takes 10∼17 years $2∼$3 billion investment with less than 10% success rate to bring from concept market ready product. A possible alternative repurposing, aims at finding other indications already approved drugs. In this study, computational repurposing framework developed applied differential gene expressions targets obtained publicly available database (GEO). This strategy uses expression signatures compares perturbagen CMap. Based connected signature drugs ranked could possibly reverse stop psoriasis. The most negative connectivity scores efficient vice versa. top hit verified using literature survey peer reviewed journal, electronic health records, patents, hospital database. As result, 50/150 37/150 confirmed have anti-psoriasis efficacy two datasets. Top 10 suggested potential repurposable study offers, powerful simple approach rapid identification candidates any interest.

Language: Английский

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