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      Human-Derived Organ-on-a-Chip for Personalized Drug Development

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          Abstract

          To reduce the required capital and time investment in the development of new pharmaceutical agents, there is an urgent need for preclinical drug testing models that are predictive of drug response in human tissues or organs. Despite tremendous advancements and rigorous multistage screening of drug candidates involving computational models, traditional cell culture platforms, animal models and most recently humanized animals, there is still a large deficit in our ability to predict drug response in patient groups and overall attrition rates from phase 1 through phase 4 of clinical studies remain well above 90%. Organ-on-a-chip (OOC) platforms have proven potential in providing tremendous flexibility and robustness in drug screening and development by employing engineering techniques and materials. More importantly, in recent years, there is a clear upward trend in studies that utilize human-induced pluripotent stem cell (hiPSC) to develop personalized tissue or organ models. Additionally, integrated multiple organs on the single chip with increasingly more sophisticated representation of absorption, distribution, metabolism, excretion and toxicity (ADMET) process are being utilized to better understand drug interaction mechanisms in the human body and thus showing great potential to better predict drug efficacy and safety. In this review, we summarize these advances, highlighting studies that took the next step to clinical trials and research areas with the utmost potential and discuss the role of the OOCs in the overall drug discovery process at a preclinical and clinical stage, as well as outline remaining challenges.

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          Most cited references107

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          Lab-on-a-chip: microfluidics in drug discovery.

          Miniaturization can expand the capability of existing bioassays, separation technologies and chemical synthesis techniques. Although a reduction in size to the micrometre scale will usually not change the nature of molecular reactions, laws of scale for surface per volume, molecular diffusion and heat transport enable dramatic increases in throughput. Besides the many microwell-plate- or bead-based methods, microfluidic chips have been widely used to provide small volumes and fluid connections and could eventually outperform conventionally used robotic fluid handling. Moreover, completely novel applications without a macroscopic equivalent have recently been developed. This article reviews current and future applications of microfluidics and highlights the potential of 'lab-on-a-chip' technology for drug discovery.
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            Is Open Access

            The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995–2010

            Background The escalating use of prescribed drugs has increasingly raised concerns about polypharmacy. This study aims to examine changes in rates of polypharmacy and potentially serious drug-drug interactions in a stable geographical population between 1995 and 2010. Methods This is a repeated cross-sectional analysis of community-dispensed prescribing data for all 310,000 adults resident in the Tayside region of Scotland in 1995 and 2010. The number of drug classes dispensed and the number of potentially serious drug-drug interactions (DDIs) in the previous 84 days were calculated, and age-sex standardised rates in 1995 and 2010 compared. Patient characteristics associated with receipt of ≥10 drugs and with the presence of one or more DDIs were examined using multilevel logistic regression to account for clustering of patients within primary care practices. Results Between 1995 and 2010, the proportion of adults dispensed ≥5 drugs doubled to 20.8%, and the proportion dispensed ≥10 tripled to 5.8%. Receipt of ≥10 drugs was strongly associated with increasing age (20–29 years, 0.3%; ≥80 years, 24.0%; adjusted OR, 118.3; 95% CI, 99.5–140.7) but was also independently more common in people living in more deprived areas (adjusted OR most vs. least deprived quintile, 2.36; 95% CI, 2.22–2.51), and in people resident in a care home (adjusted OR, 2.88; 95% CI, 2.65–3.13). The proportion with potentially serious drug-drug interactions more than doubled to 13% of adults in 2010, and the number of drugs dispensed was the characteristic most strongly associated with this (10.9% if dispensed 2–4 drugs vs. 80.8% if dispensed ≥15 drugs; adjusted OR, 26.8; 95% CI 24.5–29.3). Conclusions Drug regimens are increasingly complex and potentially harmful, and people with polypharmacy need regular review and prescribing optimisation. Research is needed to better understand the impact of multiple interacting drugs as used in real-world practice and to evaluate the effect of medicine optimisation interventions on quality of life and mortality. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0322-7) contains supplementary material, which is available to authorized users.
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              Drug Discovery: A Historical Perspective

              J. Drews (2000)
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                Author and article information

                Journal
                Current Pharmaceutical Design
                CPD
                Bentham Science Publishers Ltd.
                13816128
                April 16 2019
                April 16 2019
                : 24
                : 45
                : 5471-5486
                Affiliations
                [1 ]Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA 02139, United States
                [2 ]Department of Bioindustrial Technologies, College of Animal Bioscience and Technology, Konkuk University, Seoul 05029, Korea
                [3 ]Department of Stem Cell and Regenerative Biotechnology, KU Convergence Science and Technololgy Institute, Konkuk University, Seoul, 05029, Korea
                Article
                10.2174/1381612825666190308150055
                6587585
                30854951
                7dac2ad8-57d1-4528-a3e5-db169740f931
                © 2019
                History

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