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Pîslaru AI, Albișteanu SM, Ilie AC, Ștefaniu R, Mârza A, Moscaliuc Ș, Nicoară M, Turcu AM, Grigoraș G, Alexa ID. Lung Cancer: New Directions in Senior Patients Assessment. Geriatrics (Basel) 2024; 9:101. [PMID: 39195131 DOI: 10.3390/geriatrics9040101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/10/2024] [Accepted: 07/30/2024] [Indexed: 08/29/2024] Open
Abstract
Age is but one significant prognostic factor in lung cancer, influencing survival, treatment response, and outcomes. This narrative review synthesizes findings from searches of 11 leading databases of research studies, systematic reviews, book chapters, and clinical trial reports on lung cancer in senior patients, with a focus on geriatric assessment as well as biomarkers. Key prognostic factors for lung cancer in seniors include biological age, functional capability, physical and psychological comorbidities, frailty, nutrition, status, and biomarkers like DNA methylation age. We identified the most valuable assessments that balance efficacy with quality of life. Optimizing care and improving outcomes with senior lung cancer patients benefits from a tailored therapeutic approach incorporating a complex geriatric assessment. A multidisciplinary collaboration between geriatricians, oncologists, and pulmonologists is crucial.
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Affiliation(s)
- Anca Iuliana Pîslaru
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Sabinne-Marie Albișteanu
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Adina Carmen Ilie
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ramona Ștefaniu
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Aurelia Mârza
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ștefan Moscaliuc
- Department of Oncology, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Mălina Nicoară
- Department of Oncology, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ana-Maria Turcu
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Gabriela Grigoraș
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Ioana Dana Alexa
- Department of Medical Specialties II, Faculty of Medicine, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iasi, Romania
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Markey N, Howitt B, El-Mansouri I, Schwartzenberg C, Kotova O, Meier C. Clinical trials are becoming more complex: a machine learning analysis of data from over 16,000 trials. Sci Rep 2024; 14:3514. [PMID: 38346965 PMCID: PMC10861486 DOI: 10.1038/s41598-024-53211-z] [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: 06/25/2023] [Accepted: 01/29/2024] [Indexed: 02/15/2024] Open
Abstract
The past decade has seen substantial innovation in clinical trials, including new trial formats, endpoints, and others. Also there have been regulatory changes, increasing competitive pressures and other external factors which impact clinical trials. In parallel, trial timelines have increased and success rates remain stubbornly low. This has led many observers to question whether clinical trials have become overly complex and if this complexity is always needed. Here we present a large-scale analysis of protocols and other data from over 16,000 trials. Using a machine learning algorithm, we automatically assessed key features of these trials, such as number of endpoints, number of inclusion-exclusion criteria and others. Using a regression analysis we combined these features into a new metric, the Trial Complexity Score, which correlates with overall clinical trial duration. Looking at this score across different clinical phases and therapeutic areas we see substantial increases over time, suggesting that clinical trials are indeed becoming more complex. We discuss drivers of increasing trial complexity, necessary or helpful ('good') complexity versus unnecessary ('bad') complexity, and we explore mechanisms of how sponsors of clinical trials can reduce trial complexity where appropriate.
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Affiliation(s)
- Nigel Markey
- Boston Consulting Group, 80 Charlotte Street, London, W1T 4DF, UK
| | - Ben Howitt
- Boston Consulting Group, 80 Charlotte Street, London, W1T 4DF, UK
| | - Ilyass El-Mansouri
- Boston Consulting Group, 75 Avenue de la Grande Armée, 75016, Paris, France
| | | | - Olga Kotova
- Boston Consulting Group, 80 Charlotte Street, London, W1T 4DF, UK
| | - Christoph Meier
- Boston Consulting Group, 80 Charlotte Street, London, W1T 4DF, UK.
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3
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Tarighati E, Keivan H, Mahani H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med 2023; 23:1-16. [PMID: 35031885 DOI: 10.1007/s10238-021-00781-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 12/01/2021] [Indexed: 12/12/2022]
Abstract
Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has decreased with the advancement of technology and new diagnostic and therapeutic methods. BCs are histologically divided into in situ and invasive carcinoma, and both of them can be divided into ductal and lobular. The main function after the diagnosis of invasive breast cancer is which patient should use chemotherapy, which patient should receive adjuvant therapy, and which should not. If the decision is for adjuvant therapy, the next challenge is to identify the most appropriate treatment or combination of treatments for a particular patient. Addressing the first challenge can be helped by prognostic biomarkers, while addressing the second challenge can be done by predictive biomarkers. Among the molecular markers related to BC, ER, PR, HER2, and the Mib1/Ki-67 proliferation index are the most significant ones and are tightly confirmed in the standard care of all primary, recurrent, and metastatic BC patients. CEA and CA-15-3 antigens are the most valuable markers of serum tumors in BC patients. Determining the series of these markers helps monitor response to the treatment and early detection of recurrence or metastasis. miRNAs have been demonstrated to be intricate in mammary gland growth, proliferation, and formation of BC known to be incriminated in BC biology. By combining established prognostic factors with valid prognostic/predicted biomarkers, we can start the journey to personalized treatment for every recently diagnosed BC patient.
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Affiliation(s)
- Elaheh Tarighati
- Department of Medical Physics, Iran University of Medical Sciences, Tehran, Iran
| | - Hadi Keivan
- School of Paramedicine, Shahroud University of Medical Sciences, Shahroud, Iran
| | - Hojjat Mahani
- Radiation Applications Research School, Nuclear Science and Technology Research Institute, P.O. Box: 14395-836, Tehran, Iran.
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Lin S, Zhou J, Xiao Y, Neary B, Teng Y, Qiu P. Integrative analysis of TCGA data identifies miRNAs as drug-specific survival biomarkers. Sci Rep 2022; 12:6785. [PMID: 35474090 PMCID: PMC9042876 DOI: 10.1038/s41598-022-10662-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/11/2022] [Indexed: 01/03/2023] Open
Abstract
Biomarkers predictive of drug-specific outcomes are important tools for personalized medicine. In this study, we present an integrative analysis to identify miRNAs that are predictive of drug-specific survival outcome in cancer. Using the clinical data from TCGA, we defined subsets of cancer patients who suffered from the same cancer and received the same drug treatment, which we call cancer-drug groups. We then used the miRNA expression data in TCGA to evaluate each miRNA’s ability to predict the survival outcome of patients in each cancer-drug group. As a result, the identified miRNAs are predictive of survival outcomes in a cancer-specific and drug-specific manner. Notably, most of the drug-specific miRNA survival markers and their target genes showed consistency in terms of correlations in their expression and their correlations with survival. Some of the identified miRNAs were supported by published literature in contexts of various cancers. We explored several additional breast cancer datasets that provided miRNA expression and survival data, and showed that our drug-specific miRNA survival markers for breast cancer were able to effectively stratify the prognosis of patients in those additional datasets. Together, this analysis revealed drug-specific miRNA markers for cancer survival, which can be promising tools toward personalized medicine.
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Affiliation(s)
- Shuting Lin
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, USA
| | - Jie Zhou
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, USA
| | - Yiqiong Xiao
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, USA
| | - Bridget Neary
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, USA
| | - Yong Teng
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, USA
| | - Peng Qiu
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, USA.
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Network pharmacology: curing causal mechanisms instead of treating symptoms. Trends Pharmacol Sci 2021; 43:136-150. [PMID: 34895945 DOI: 10.1016/j.tips.2021.11.004] [Citation(s) in RCA: 338] [Impact Index Per Article: 112.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 10/05/2021] [Accepted: 11/04/2021] [Indexed: 12/15/2022]
Abstract
For complex diseases, most drugs are highly ineffective, and the success rate of drug discovery is in constant decline. While low quality, reproducibility issues, and translational irrelevance of most basic and preclinical research have contributed to this, the current organ-centricity of medicine and the 'one disease-one target-one drug' dogma obstruct innovation in the most profound manner. Systems and network medicine and their therapeutic arm, network pharmacology, revolutionize how we define, diagnose, treat, and, ideally, cure diseases. Descriptive disease phenotypes are replaced by endotypes defined by causal, multitarget signaling modules that also explain respective comorbidities. Precise and effective therapeutic intervention is achieved by synergistic multicompound network pharmacology and drug repurposing, obviating the need for drug discovery and speeding up clinical translation.
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Comte B, Baumbach J, Benis A, Basílio J, Debeljak N, Flobak Å, Franken C, Harel N, He F, Kuiper M, Méndez Pérez JA, Pujos-Guillot E, Režen T, Rozman D, Schmid JA, Scerri J, Tieri P, Van Steen K, Vasudevan S, Watterson S, Schmidt HH. Network and Systems Medicine: Position Paper of the European Collaboration on Science and Technology Action on Open Multiscale Systems Medicine. NETWORK AND SYSTEMS MEDICINE 2020; 3:67-90. [PMID: 32954378 PMCID: PMC7500076 DOI: 10.1089/nsm.2020.0004] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2020] [Indexed: 12/14/2022] Open
Abstract
Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management.
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Affiliation(s)
- Blandine Comte
- Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Université Clermont Auvergne, INRAE, UNH, Clermont-Ferrand, France
| | - Jan Baumbach
- TUM School of Life Sciences Weihenstephan (WZW), Technical University of Munich (TUM), Freising-Weihenstephan, Germany
| | | | - José Basílio
- Institute of Vascular Biology and Thrombosis Research, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Nataša Debeljak
- Medical Centre for Molecular Biology, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Åsmund Flobak
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- The Cancer Clinic, St. Olav's University Hospital, Trondheim, Norway
| | - Christian Franken
- Digital Health Systems, Einsingen, Germany
- Department of Pharmacology and Personalised Medicine, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht, The Netherlands
| | | | - Feng He
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
- Institute of Medical Microbiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Martin Kuiper
- Department of Biology, Faculty of Natural Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Juan Albino Méndez Pérez
- Department of Computer Science and Systems Engineering, Universidad de La Laguna, Tenerife, Spain
| | - Estelle Pujos-Guillot
- Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Université Clermont Auvergne, INRAE, UNH, Clermont-Ferrand, France
| | - Tadeja Režen
- Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Damjana Rozman
- Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Johannes A. Schmid
- Institute of Vascular Biology and Thrombosis Research, Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Jeanesse Scerri
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, University of Malta, Msida, Malta
| | - Paolo Tieri
- CNR National Research Council, IAC Institute for Applied Computing, Rome, Italy
| | | | - Sona Vasudevan
- Georgetown University Medical Centre, Washington, District of Columbia, USA
| | - Steven Watterson
- Northern Ireland Centre for Stratified Medicine, Ulster University, Londonderry, United Kingdom
| | - Harald H.H.W. Schmidt
- Department of Pharmacology and Personalised Medicine, Faculty of Health, Medicine and Life Science, MeHNS, Maastricht University, The Netherlands
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AroCell TK 210 ELISA for determination of TK1 protein: age-related reference ranges and comparison with other TK1 assays. Biotechniques 2020; 68:334-341. [PMID: 32336110 DOI: 10.2144/btn-2019-0148] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Thymidine kinase 1 (TK1) is an enzyme involved in DNA precursor synthesis that has been used as a biomarker for prognosis and monitoring of different malignancies. In this study, we compared two immunoassays for measuring TK1 protein concentrations: the TK 210 ELISA (AroCell AB) and TK1 ELISA from Abcam. Overall, the TK 210 ELISA showed higher sensitivity than the Abcam TK1 ELISA for differentiating hematological malignancies (sensitivity of 0.77 vs 0.45) as well as for distinguishing sera of patients with solid tumors from those of apparently healthy individuals (0.61 vs 0.20). There was no significant difference in the TK1 protein levels determined with the TK 210 ELISA between different age groups from apparently healthy individuals. These results strongly indicate that the AroCell TK 210 ELISA is accurate and sensitive enough to be a valuable tool in cancer management.
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Wermuth PJ, Piera-Velazquez S, Rosenbloom J, Jimenez SA. Existing and novel biomarkers for precision medicine in systemic sclerosis. Nat Rev Rheumatol 2019; 14:421-432. [PMID: 29789665 DOI: 10.1038/s41584-018-0021-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.
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Affiliation(s)
- Peter J Wermuth
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sonsoles Piera-Velazquez
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joel Rosenbloom
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sergio A Jimenez
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA. .,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA. .,The Scleroderma Center, Thomas Jefferson University, Philadelphia, PA, USA.
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Kovalchick C, Sirkar R, Regele OB, Kourtis LC, Schiller M, Wolpert H, Alden RG, Jones GB, Wright JM. Can composite digital monitoring biomarkers come of age? A framework for utilization. J Clin Transl Sci 2017; 1:373-380. [PMID: 29707260 PMCID: PMC5916505 DOI: 10.1017/cts.2018.4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 01/16/2018] [Accepted: 01/19/2018] [Indexed: 12/20/2022] Open
Abstract
INTRODUCTION The application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision-making dashboard. METHODS A framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite, and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare. RESULTS The de novo framework implies consideration of physiological, behavioral, and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed-loop systems is illustrated. CONCLUSIONS The study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering, and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.
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Affiliation(s)
| | - Rhea Sirkar
- Eli Lilly Innovation Center, Cambridge, MA, USA
| | | | | | | | | | | | - Graham B. Jones
- Clinical & Translational Science Institute, Tufts University Medical Center, Boston, MA, USA
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Beger R, Yu LR, Daniels J, Mattes W. Exploratory biomarkers: Analytical approaches and their implications. CURRENT OPINION IN TOXICOLOGY 2017. [DOI: 10.1016/j.cotox.2017.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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Hosoya M, Czysz K. Translational Prospects and Challenges in Human Induced Pluripotent Stem Cell Research in Drug Discovery. Cells 2016; 5:cells5040046. [PMID: 28009813 PMCID: PMC5187530 DOI: 10.3390/cells5040046] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Revised: 11/27/2016] [Accepted: 12/15/2016] [Indexed: 02/07/2023] Open
Abstract
Despite continuous efforts to improve the process of drug discovery and development, achieving success at the clinical stage remains challenging because of a persistent translational gap between the preclinical and clinical settings. Under these circumstances, the discovery of human induced pluripotent stem (iPS) cells has brought new hope to the drug discovery field because they enable scientists to humanize a variety of pharmacological and toxicological models in vitro. The availability of human iPS cell-derived cells, particularly as an alternative for difficult-to-access tissues and organs, is increasing steadily; however, their use in the field of translational medicine remains challenging. Biomarkers are an essential part of the translational effort to shift new discoveries from bench to bedside as they provide a measurable indicator with which to evaluate pharmacological and toxicological effects in both the preclinical and clinical settings. In general, during the preclinical stage of the drug development process, in vitro models that are established to recapitulate human diseases are validated by using a set of biomarkers; however, their translatability to a clinical setting remains problematic. This review provides an overview of current strategies for human iPS cell-based drug discovery from the perspective of translational research, and discusses the importance of early consideration of clinically relevant biomarkers.
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Affiliation(s)
- Masaki Hosoya
- Integrated Technology Research Laboratories, Research Division, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-8555, Japan.
| | - Katherine Czysz
- Integrated Technology Research Laboratories, Research Division, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-8555, Japan.
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