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Lopez I, Truskey GA. Multi-cellular engineered living systems to assess reproductive toxicology. Reprod Toxicol 2024; 127:108609. [PMID: 38759876 PMCID: PMC11179964 DOI: 10.1016/j.reprotox.2024.108609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/07/2024] [Accepted: 05/09/2024] [Indexed: 05/19/2024]
Abstract
Toxicants and some drugs can negatively impact reproductive health. Many toxicants haven't been tested due to lack of available models. The impact of many drugs taken during pregnancy to address maternal health may adversely affect fetal development with life-long effects and clinical trials do not examine toxicity effects on the maternal-fetal interface, requiring indirect assessment of safety and efficacy. Due to current gaps in reproductive toxicological knowledge and limitations of animal models, multi-cellular engineered living systems may provide solutions for modeling reproductive physiology and pathology for chemical and xenobiotic toxicity studies. Multi-cellular engineered living systems, such as microphysiological systems (MPS) and organoids, model of functional units of tissues. In this review, we highlight the key functions and structures of human reproductive organs and well-known representative toxicants afflicting these systems. We then discuss current approaches and specific studies where scientists have used MPS or organoids to recreate in vivo markers and cellular responses of the female and male reproductive system, as well as pregnancy-associated placenta formation and embryo development. We provide specific examples of organoids and organ-on-chip that have been used for toxicological purposes with varied success. Finally, we address current issues related to usage of MPS, emerging techniques for improving upon these complications, and improvements needed to make MPS more capable in assessing reproductive toxicology. Overall, multi-cellular engineered living systems have considerable promise to serve as a suitable, alternative reproductive biological model compared to animal studies and 2D culture.
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Affiliation(s)
- Isabella Lopez
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, United States
| | - George A Truskey
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, United States.
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Stokar-Regenscheit N, Bell L, Berridge B, Rudmann D, Tagle D, Hargrove-Grimes P, Schaudien D, Hahn K, Kühnlenz J, Ashton RS, Tseng M, Reichelt M, Laing ST, Kiyota T, Chamanza R, Sura R, Tomlinson L. Complex In Vitro Model Characterization for Context of Use in Toxicologic Pathology: Use Cases by Collaborative Teams of Biologists, Bioengineers, and Pathologists. Toxicol Pathol 2024:1926233241253811. [PMID: 38888280 DOI: 10.1177/01926233241253811] [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: 06/20/2024]
Abstract
Complex in vitro models (CIVMs) offer the potential to increase the clinical relevance of preclinical efficacy and toxicity assessments and reduce the reliance on animals in drug development. The European Society of Toxicologic Pathology (ESTP) and Society for Toxicologic Pathology (STP) are collaborating to highlight the role of pathologists in the development and use of CIVM. Pathologists are trained in comparative animal medicine which enhances their understanding of mechanisms of human and animal diseases, thus allowing them to bridge between animal models and humans. This skill set is important for CIVM development, validation, and data interpretation. Ideally, diverse teams of scientists, including engineers, biologists, pathologists, and others, should collaboratively develop and characterize novel CIVM, and collectively assess their precise use cases (context of use). Implementing a morphological CIVM evaluation should be essential in this process. This requires robust histological technique workflows, image analysis techniques, and needs correlation with translational biomarkers. In this review, we demonstrate how such tissue technologies and analytics support the development and use of CIVM for drug efficacy and safety evaluations. We encourage the scientific community to explore similar options for their projects and to engage with health authorities on the use of CIVM in benefit-risk assessment.
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Affiliation(s)
- Nadine Stokar-Regenscheit
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Luisa Bell
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | | | | | - Danilo Tagle
- National Center for Advancing Translational Sciences/National Institutes of Health, Bethesda, Maryland, USA
| | - Passley Hargrove-Grimes
- National Center for Advancing Translational Sciences/National Institutes of Health, Bethesda, Maryland, USA
| | - Dirk Schaudien
- Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany
| | - Kerstin Hahn
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Julia Kühnlenz
- Bayer SAS, CropScience, Pathology & Mechanistic Toxicology, Sophia Antipolis, France
| | - Randolph S Ashton
- University of Wisconsin-Madison, Madison, Wisconsin, USA
- Neurosetta LLC, Madison, Wisconsin, USA
| | - Min Tseng
- Genentech, South San Francisco, California, USA
| | | | | | | | | | | | - Lindsay Tomlinson
- Pfizer Inc., Drug Safety Research and Development, Cambridge, Massachusetts, USA
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Sunildutt N, Parihar P, Chethikkattuveli Salih AR, Lee SH, Choi KH. Revolutionizing drug development: harnessing the potential of organ-on-chip technology for disease modeling and drug discovery. Front Pharmacol 2023; 14:1139229. [PMID: 37180709 PMCID: PMC10166826 DOI: 10.3389/fphar.2023.1139229] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 04/05/2023] [Indexed: 05/16/2023] Open
Abstract
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) is a microfluidic device cultured with human living cells under specific organ shear stress which can faithfully replicate human organ-body level pathophysiology. This emerging organ-on-chip platform can be a remarkable alternative for animal models with a broad range of purposes in drug testing and precision medicine. Here, we review the parameters employed in using organ on chip platform as a plot mimic diseases, genetic disorders, drug toxicity effects in different organs, biomarker identification, and drug discoveries. Additionally, we address the current challenges of the organ-on-chip platform that should be overcome to be accepted by drug regulatory agencies and pharmaceutical industries. Moreover, we highlight the future direction of the organ-on-chip platform parameters for enhancing and accelerating drug discoveries and personalized medicine.
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Affiliation(s)
- Naina Sunildutt
- Department of Mechatronics Engineering, Jeju National University, Jeju, Republic of Korea
| | - Pratibha Parihar
- Department of Mechatronics Engineering, Jeju National University, Jeju, Republic of Korea
| | | | - Sang Ho Lee
- College of Pharmacy, Jeju National University, Jeju, Republic of Korea
| | - Kyung Hyun Choi
- Department of Mechatronics Engineering, Jeju National University, Jeju, Republic of Korea
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Tsai HF, Podder S, Chen PY. Microsystem Advances through Integration with Artificial Intelligence. MICROMACHINES 2023; 14:826. [PMID: 37421059 DOI: 10.3390/mi14040826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 07/09/2023]
Abstract
Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.
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Affiliation(s)
- Hsieh-Fu Tsai
- Department of Biomedical Engineering, Chang Gung University, Taoyuan City 333, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Keelung City 204, Taiwan
- Center for Biomedical Engineering, Chang Gung University, Taoyuan City 333, Taiwan
| | - Soumyajit Podder
- Department of Biomedical Engineering, Chang Gung University, Taoyuan City 333, Taiwan
| | - Pin-Yuan Chen
- Department of Biomedical Engineering, Chang Gung University, Taoyuan City 333, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, Keelung City 204, Taiwan
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Dai M, Xiao G, Shao M, Zhang YS. The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review. BIOSENSORS 2023; 13:389. [PMID: 36979601 PMCID: PMC10046732 DOI: 10.3390/bios13030389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 02/22/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a class of advanced in vitro models. Deep learning, as an emerging topic in machine learning, has the ability to extract a hidden statistical relationship from the input data. Recently, these two areas have become integrated to achieve synergy for accelerating drug screening. This review provides a brief description of the basic concepts of deep learning used in OoCs and exemplifies the successful use cases for different types of OoCs. These microfluidic chips are of potential to be assembled as highly potent human-on-chips with complex physiological or pathological functions. Finally, we discuss the future supply with perspectives and potential challenges in terms of combining OoCs and deep learning for image processing and automation designs.
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Affiliation(s)
- Manna Dai
- College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China
- Computing and Intelligence Department, Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Singapore
| | - Gao Xiao
- College of Environment and Safety Engineering, Fuzhou University, Fuzhou 350108, China
- Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China
| | - Ming Shao
- Department of Computer and Information Science, College of Engineering, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA
| | - Yu Shrike Zhang
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA 02139, USA
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Chitosan and Pectin Hydrogels for Tissue Engineering and In Vitro Modeling. Gels 2023; 9:gels9020132. [PMID: 36826302 PMCID: PMC9957157 DOI: 10.3390/gels9020132] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/26/2023] [Accepted: 01/31/2023] [Indexed: 02/09/2023] Open
Abstract
Hydrogels are fascinating biomaterials that can act as a support for cells, i.e., a scaffold, in which they can organize themselves spatially in a similar way to what occurs in vivo. Hydrogel use is therefore essential for the development of 3D systems and allows to recreate the cellular microenvironment in physiological and pathological conditions. This makes them ideal candidates for biological tissue analogues for application in the field of both tissue engineering and 3D in vitro models, as they have the ability to closely mimic the extracellular matrix (ECM) of a specific organ or tissue. Polysaccharide-based hydrogels, because of their remarkable biocompatibility related to their polymeric constituents, have the ability to interact beneficially with the cellular components. Although the growing interest in the use of polysaccharide-based hydrogels in the biomedical field is evidenced by a conspicuous number of reviews on the topic, none of them have focused on the combined use of two important polysaccharides, chitosan and pectin. Therefore, the present review will discuss the biomedical applications of polysaccharide-based hydrogels containing the two aforementioned natural polymers, chitosan and pectin, in the fields of tissue engineering and 3D in vitro modeling.
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Nahak BK, Mishra A, Preetam S, Tiwari A. Advances in Organ-on-a-Chip Materials and Devices. ACS APPLIED BIO MATERIALS 2022; 5:3576-3607. [PMID: 35839513 DOI: 10.1021/acsabm.2c00041] [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: 11/28/2022]
Abstract
The organ-on-a-chip (OoC) paves a way for biomedical applications ranging from preclinical to clinical translational precision. The current trends in the in vitro modeling is to reduce the complexity of human organ anatomy to the fundamental cellular microanatomy as an alternative of recreating the entire cell milieu that allows systematic analysis of medicinal absorption of compounds, metabolism, and mechanistic investigation. The OoC devices accurately represent human physiology in vitro; however, it is vital to choose the correct chip materials. The potential chip materials include inorganic, elastomeric, thermoplastic, natural, and hybrid materials. Despite the fact that polydimethylsiloxane is the most commonly utilized polymer for OoC and microphysiological systems, substitute materials have been continuously developed for its advanced applications. The evaluation of human physiological status can help to demonstrate using noninvasive OoC materials in real-time procedures. Therefore, this Review examines the materials used for fabricating OoC devices, the application-oriented pros and cons, possessions for device fabrication and biocompatibility, as well as their potential for downstream biochemical surface alteration and commercialization. The convergence of emerging approaches, such as advanced materials, artificial intelligence, machine learning, three-dimensional (3D) bioprinting, and genomics, have the potential to perform OoC technology at next generation. Thus, OoC technologies provide easy and precise methodologies in cost-effective clinical monitoring and treatment using standardized protocols, at even personalized levels. Because of the inherent utilization of the integrated materials, employing the OoC with biomedical approaches will be a promising methodology in the healthcare industry.
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Affiliation(s)
- Bishal Kumar Nahak
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Anshuman Mishra
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Subham Preetam
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
| | - Ashutosh Tiwari
- Institute of Advanced Materials, IAAM, Gammalkilsvägen 18, Ulrika 59053, Sweden
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Sorrentino S, Polini A, Arima V, Romano A, Quattrini A, Gigli G, Mozetic P, Moroni L. Neurovascular signals in amyotrophic lateral sclerosis. Curr Opin Biotechnol 2021; 74:75-83. [PMID: 34800850 DOI: 10.1016/j.copbio.2021.10.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/24/2021] [Accepted: 10/22/2021] [Indexed: 12/21/2022]
Abstract
The neurovascular system (NVS) is a complex anatomic-functional unit that synergically works to maintain organs/tissues homeostasis of the entire body. NVS alterations have recently emerged as a common distinct feature in the pathogenesis of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Despite their undeniable involvement, neurovascular signalling pathways remain still far unknown in ALS. This review underlines the importance of endothelial, mural, and fibroblast cells as novel targets for ALS investigation and identifies in the interplay between neuronal and vascular systems the way to disclose novel molecular mechanisms behind the pathogenesis of ALS.
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Affiliation(s)
- Stefano Sorrentino
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy
| | - Alessandro Polini
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy
| | - Valentina Arima
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy
| | - Alessandro Romano
- San Raffaele Hospital, Division of Neuroscience, Institute of Experimental Neurology, San Rafaele Scientifc Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Angelo Quattrini
- San Raffaele Hospital, Division of Neuroscience, Institute of Experimental Neurology, San Rafaele Scientifc Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Giuseppe Gigli
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy; Department of Mathematics and Physics "Ennio De Giorgi", University of Salento, via Arnesano, 73100, Lecce, Italy
| | - Pamela Mozetic
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy; San Raffaele Hospital, Division of Neuroscience, Institute of Experimental Neurology, San Rafaele Scientifc Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Lorenzo Moroni
- CNR Nanotec - Institute of Nanotechnology, Campus Ecotekne, via Monteroni, Lecce, 73100, Italy; Maastricht University, MERLN Institute for Technology-Inspired Regenerative Medicine, Complex Tissue Regeneration Department, Universiteitssingel 40, 6229ER, Maastricht, The Netherlands.
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