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Barakat A, Munro G, Heegaard AM. Finding new analgesics: Computational pharmacology faces drug discovery challenges. Biochem Pharmacol 2024; 222:116091. [PMID: 38412924 DOI: 10.1016/j.bcp.2024.116091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 01/10/2024] [Accepted: 02/23/2024] [Indexed: 02/29/2024]
Abstract
Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.
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Affiliation(s)
- Ahmed Barakat
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Pharmacology and Toxicology, Faculty of Pharmacy, Assiut University, Assiut, Egypt.
| | | | - Anne-Marie Heegaard
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Russo MA, Santarelli DM, Austin PJ, Graham BA. Progressing into a new paradigm: how we must leave the past behind if we want a change in pain research outcomes. Pain Med 2024; 25:5-7. [PMID: 37669143 DOI: 10.1093/pm/pnad115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/15/2023] [Accepted: 08/24/2023] [Indexed: 09/07/2023]
Affiliation(s)
- Marc A Russo
- Hunter Pain Specialists, Broadmeadow, NSW 2292, Australia
- Genesis Research Services, Broadmeadow, NSW 2292, Australia
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| | | | - Paul J Austin
- School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Brain and Mind Centre, Camperdown, NSW 2050, Australia
| | - Brett A Graham
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
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Soliman N, Denk F. Practical approaches to improving translatability and reproducibility in preclinical pain research. Brain Behav Immun 2024; 115:38-42. [PMID: 37793487 DOI: 10.1016/j.bbi.2023.09.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/21/2023] [Accepted: 09/30/2023] [Indexed: 10/06/2023] Open
Abstract
Pain research continues to face the challenge of poor translatability of pre-clinical studies. In this short primer, we are summarizing the possible causes, with an emphasis on practical and constructive solutions. In particular, we stress the importance of increased heterogeneity in animal studies; formal or informal pre-registration to combat publication bias; and increased statistical training in order to help pre-clinical scientists appreciate the usefulness of available experimental design and reporting guidelines.
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Affiliation(s)
- Nadia Soliman
- Pain Research, Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Franziska Denk
- Wolfson Centre for Age-related Diseases, King's College London, Guy's Campus, London, SE1 1UL, United Kingdom.
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Zhang XY, Diaz-delCastillo M, Kong L, Daniels N, MacIntosh-Smith W, Abdallah A, Domanski D, Sofrenovic D, Yeung TP(S, Valiente D, Vollert J, Sena E, Rice AS, Soliman N. A systematic review and meta-analysis of thigmotactic behaviour in the open field test in rodent models associated with persistent pain. PLoS One 2023; 18:e0290382. [PMID: 37682863 PMCID: PMC10490990 DOI: 10.1371/journal.pone.0290382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 08/07/2023] [Indexed: 09/10/2023] Open
Abstract
Thigmotaxis is an innate predator avoidance behaviour of rodents. To gain insight into how injury and disease models, and analgesic drug treatments affect thigmotaxis, we performed a systematic review and meta-analysis of studies that assessed thigmotaxis in the open field test. Systematic searches were conducted of 3 databases in October 2020, March and August 2022. Study design characteristics and experimental data were extracted and analysed using a random-effects meta-analysis. We also assessed the correlation between thigmotaxis and stimulus-evoked limb withdrawal. This review included the meta-analysis of 165 studies We report thigmotaxis was increased in injury and disease models associated with persistent pain and this increase was attenuated by analgesic drug treatments in both rat and mouse experiments. Its usefulness, however, may be limited in certain injury and disease models because our analysis suggested that thigmotaxis may be associated with the locomotor function. We also conducted subgroup analyses and meta-regression, but our findings on sources of heterogeneity are inconclusive because analyses were limited by insufficient available data. It was difficult to assess internal validity because reporting of methodological quality measures was poor, therefore, the studies have an unclear risk of bias. The correlation between time in the centre (type of a thigmotactic metric) and types of stimulus-evoked limb withdrawal was inconsistent. Therefore, stimulus-evoked and ethologically relevant behavioural paradigms should be viewed as two separate entities as they are conceptually and methodologically different from each other.
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Affiliation(s)
- Xue Ying Zhang
- Pain Research, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | | | - Lingsi Kong
- Department of Women and Children’s Health, Faculty of Life Science and Medicine, King’s College London, London, United Kingdom
| | - Natasha Daniels
- Bart’s Health NHS Trust Whipps Cross Hospital, London, United Kingdom
| | - William MacIntosh-Smith
- School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Aya Abdallah
- School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Dominik Domanski
- School of Medicine, Medical Science and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - Denis Sofrenovic
- Faculty of Medicine, Imperial College London, London, United Kingdom
| | | | - Diego Valiente
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jan Vollert
- Pain Research, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Emily Sena
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew S. Rice
- Pain Research, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Nadia Soliman
- Pain Research, Department of Surgery and Cancer, Imperial College London, United Kingdom
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