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Kokudeva M, Vichev M, Naseva E, Miteva DG, Velikova T. Artificial intelligence as a tool in drug discovery and development. World J Exp Med 2024; 14:96042. [PMID: 39312699 PMCID: PMC11372739 DOI: 10.5493/wjem.v14.i3.96042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 08/06/2024] [Accepted: 08/12/2024] [Indexed: 08/29/2024] Open
Abstract
The rapidly advancing field of artificial intelligence (AI) has garnered substantial attention for its potential application in drug discovery and development. This opinion review critically examined the feasibility and prospects of integrating AI as a transformative tool in the pharmaceutical industry. AI, encompassing machine learning algorithms, deep learning, and data analytics, offers unprecedented opportunities to streamline and enhance various stages of drug development. This opinion review delved into the current landscape of AI-driven approaches, discussing their utilization in target identification, lead optimization, and predictive modeling of pharmacokinetics and toxicity. We aimed to scrutinize the integration of large-scale omics data, electronic health records, and chemical informatics, highlighting the power of AI in uncovering novel therapeutic targets and accelerating drug repurposing strategies. Despite the considerable potential of AI, the review also addressed inherent challenges, including data privacy concerns, interpretability of AI models, and the need for robust validation in real-world clinical settings. Additionally, we explored ethical considerations surrounding AI-driven decision-making in drug development. This opinion review provided a nuanced perspective on the transformative role of AI in drug discovery by discussing the existing literature and emerging trends, presenting critical insights and addressing potential hurdles. In conclusion, this study aimed to stimulate discourse within the scientific community and guide future endeavors to harness the full potential of AI in drug development.
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Affiliation(s)
- Maria Kokudeva
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Medical University of Sofia, Sofia 1000, Bulgaria
| | | | - Emilia Naseva
- Faculty of Public Health, Medical University of Sofia, Sofia 1431, Bulgaria
| | - Dimitrina Georgieva Miteva
- Department of Genetics, Faculty of Biology, Sofia University St. Kliment Ohridski, Sofia 1164, Bulgaria
- Medical Faculty, Sofia University St. Kliment Ohridski, Sofia 1407, Bulgaria
| | - Tsvetelina Velikova
- Medical Faculty, Sofia University St. Kliment Ohridski, Sofia 1407, Bulgaria
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Zamora PO, Altay G, Santamaria U, Dwarshuis N, Donthi H, Moon CI, Bakalar D, Zamora M. Drug Responses in Plexiform Neurofibroma Type I (PNF1) Cell Lines Using High-Throughput Data and Combined Effectiveness and Potency. Cancers (Basel) 2023; 15:5811. [PMID: 38136356 PMCID: PMC10742026 DOI: 10.3390/cancers15245811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/05/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Background: Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by heterozygous germline NF1 gene mutations that predispose patients to developing plexiform neurofibromas, which are benign but often disfiguring tumors of the peripheral nerve sheath induced by loss of heterozygosity at the NF1 locus. These can progress to malignant peripheral nerve sheath tumors (MPNSTs). There are no approved drug treatments for adults with NF1-related inoperable plexiform neurofibromas, and only one drug (selumetinib), which is an FDA-approved targeted therapy for the treatment of symptomatic pediatric plexiform neurofibromas, highlighting the need for additional drug screening and development. In high-throughput screening, the effectiveness of drugs against cell lines is often assessed by measuring in vitro potency (AC50) or the area under the curve (AUC). However, the variability of dose-response curves across drugs and cell lines and the frequency of partial effectiveness suggest that these measures alone fail to provide a full picture of overall efficacy. Methods: Using concentration-response data, we combined response effectiveness (EFF) and potency (AC50) into (a) a score characterizing the effect of a compound on a single cell line, S = log[EFF/AC50], and (b) a relative score, ΔS, characterizing the relative difference between a reference (e.g., non-tumor) and test (tumor) cell line. ΔS was applied to data from high-throughput screening (HTS) of a drug panel tested on NF1-/- tumor cells, using immortalized non-tumor NF1+/- cells as a reference. Results: We identified drugs with sensitivity, targeting expected pathways, such as MAPK-ERK and PI3K-AKT, as well as serotonin-related targets, among others. The ΔS technique used here, in tandem with a supplemental ΔS web tool, simplifies HTS analysis and may provide a springboard for further investigations into drug response in NF1-related cancers. The tool may also prove useful for drug development in a variety of other cancers.
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Affiliation(s)
| | | | | | | | | | - Chang In Moon
- Dan L. Duncan Comprehensive Cancer Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
- Lester and Sue Smith Breast Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Dana Bakalar
- National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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Phenotypic screening identifies hydroxypyridone anti-fungals as novel medicines for the prevention of hypertrophic scars. Eur J Pharmacol 2022; 937:175374. [DOI: 10.1016/j.ejphar.2022.175374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/25/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022]
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Bajusz D, Keserű GM. Maximizing the integration of virtual and experimental screening in hit discovery. Expert Opin Drug Discov 2022; 17:629-640. [PMID: 35671403 DOI: 10.1080/17460441.2022.2085685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Experimental and virtual screening contributes to the discovery of more than 50% of clinical candidates. Considering the similar concept and goals, early-phase drug discovery would benefit from the effective integration of these approaches. AREAS COVERED After reviewing the recent trends in both experimental and virtual screening, the authors discuss different integration strategies from parallel, focused, sequential, and iterative screening. Strategic considerations are demonstrated in a number of real-life case studies. EXPERT OPINION Experimental and virtual screening are complementary approaches that should be integrated in lead discovery settings. Virtual screening can access extremely large synthetically feasible chemical space that can be effectively searched on GPU clusters or cloud architectures. Experimental screening provides reliable datasets by quantitative HTS applications, and DNA-encoded libraries (DEL) have enlarged the chemical space covered by these technologies. These developments, together with the use of artificial intelligence methods, represent new options for their efficient integration. The case studies discussed here demonstrate the benefits of complementary strategies, such as focused and iterative screening.
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Affiliation(s)
- Dávid Bajusz
- Medicinal Chemistry Research Group, Research Centre for Natural Sciences, Budapest, Hungary
| | - György M Keserű
- Medicinal Chemistry Research Group, Research Centre for Natural Sciences, Budapest, Hungary
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López-López E, Fernández-de Gortari E, Medina-Franco JL. Yes SIR! On the structure-inactivity relationships in drug discovery. Drug Discov Today 2022; 27:2353-2362. [PMID: 35561964 DOI: 10.1016/j.drudis.2022.05.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 04/09/2022] [Accepted: 05/05/2022] [Indexed: 12/12/2022]
Abstract
In analogy with structure-activity relationships (SARs), which are at the core of medicinal chemistry, studying structure-inactivity relationships (SIRs) is essential to understanding and predicting biological activity. Current computational methods should predict or distinguish 'activity' and 'inactivity' with the same confidence because both concepts are complementary. However, the lack of inactivity data, in particular in the public domain, limits the development of predictive models and its broad application. In this review, we encourage the scientific community to disclose and analyze high-confidence activity data considering both the labeled 'active' and 'inactive' compounds.
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Affiliation(s)
- Edgar López-López
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; Department of Chemistry and Graduate Program in Pharmacology, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City 07000, Mexico.
| | - Eli Fernández-de Gortari
- Department of Nanosafety, International Iberian Nanotechnology Laboratory, Braga 4715-330, Portugal
| | - José L Medina-Franco
- DIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
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Analysis of quantitative high throughput screening data using a robust method for nonlinear mixed effects models. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS 2020. [DOI: 10.29220/csam.2020.27.6.701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Tran TT, Tran PH. Lead Compounds in the Context of Extracellular Vesicle Research. Pharmaceutics 2020; 12:E716. [PMID: 32751565 PMCID: PMC7463631 DOI: 10.3390/pharmaceutics12080716] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 07/26/2020] [Accepted: 07/28/2020] [Indexed: 02/08/2023] Open
Abstract
Studies of small extracellular vesicles (sEVs), known as exosomes, have been flourishing in the last decade with several achievements, from advancing biochemical knowledge to use in biomedical applications. Physiological changes of sEVs due to the variety of cargos they carry undoubtedly leave an impression that affects the understanding of the mechanism underlying disease and the development of sEV-based shuttles used for treatments and non-invasive diagnostic tools. Indeed, the remarkable properties of sEVs are based on their nature, which helps shield them from recognition by the immune system, protects their payload from biochemical degradation, and contributes to their ability to translocate and convey information between cells and their inherent ability to target disease sites such as tumors that is valid for sEVs derived from cancer cells. However, their transport, biogenesis, and secretion mechanisms are still not thoroughly clear, and many ongoing investigations seek to determine how these processes occur. On the other hand, lead compounds have been playing critical roles in the drug discovery process and have been recently employed in studies of the biogenesis and secretion of sEVs as external agents, affecting sEV release and serving as drug payloads in sEV drug delivery systems. This article gives readers an overview of the roles of lead compounds in these two research areas of sEVs, the rising star in studies of nanoscale medicine.
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Affiliation(s)
- Thao T.D. Tran
- Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam;
- The Faculty of Pharmacy, Duy Tan University, Danang 550000, Vietnam
| | - Phuong H.L. Tran
- Deakin University, School of Medicine, IMPACT, Institute for innovation in Physical and Mental health and Clinical Translation, Geelong, Australia
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