Microfluidic Systems to Study the Biology of Human Diseases and Identify Potential Therapeutic Targets in Caenorhabditis elegans
Iniewski Krzysztof in Integrated Microsystems, 2017
Drug discovery is the process of identifying drugs for human diseases. Typically, this involves screening for a large number of chemical compounds against certain targets in cells using in vitro and in vivo disease models [1]. In general, the process includes five stages: target identification and validation, lead screening, optimization, preclinical development, and clinical trials. A protein or biochemical pathway that plays a key role in the origin or progression of the disease is identified in the target identification and validation stage. The lead screening stage involves screening of a large number of chemical compounds against the biomolecular target protein or gene in order to identify candidates with potential therapeutic effect. This is followed by an optimization stage in which small chemical modifications of the initial lead compounds are made and screened to produce an optimal chemical species. The preclinical stage involves testing the candidates in various other animal models for efficacy as well as toxicity, and finally, in the clinical stage, testing is carried out in humans on a smaller scale. If successful, the drug is made commercially available in the market.
Big Data Analytics
Lawrence S. Chan, William C. Tang in Engineering-Medicine, 2019
New drug discovery is essential to healthcare. Optimal care can be delivered to the patients so long as we have the proper medications to offer. Some of the enemies of human, cancer cells and infectious microorganisms, for example, can mutat-genetically in response to treatment and become drug resistant (Choi et al. 2018, Wang et al. 2018). Thus, we are in constant need for new medication in responding to these resistances. Big Data, when properly acquired and interpreted, could enhance project timelines and reduce clinical attrition by improving early decision making (Brown et al. 2018). Additionally, Big Data, in conjunction with artificial intelligence, can potentially help accelerating medicinal chemistry in the drug discovery process (Griffen et al. 2018). A good example is Alzheimers disease, for which a large number of data is present. New informatics analysis platform, if developed, can be used to organize and extract Big Data resources into actionable mechanism to assist effective drug repurposing or de novo drug design (Maudslev et al. 2018).
Organoids as an Emerging Tool for Nano-Pharmaceuticals
Harishkumar Madhyastha, Durgesh Nandini Chauhan in Nanopharmaceuticals in Regenerative Medicine, 2022
Developing novel drugs (drug discovery) and identifying novel therapeutic molecular targets is a long, costly, and challenging task because of limited success in the initial screening process at the in vitro level. As a result, there have been significant advancements towards adopting more biomimetic platforms for drug screening platforms with higher fidelity for testing bioactivity and toxicity. To this end, in recent years, there have been encouraging efforts towards switching from 2D assays to physiologically more acceptable 3D system of assays, including cell-based assays and multicellular spheroid models as well miniaturised organ on chip systems (Ranga et al. 2016). In particular, in last few years, there have been consistent attempts to develop complex multicellular constructs termed “Organoid” equivalents for organs towards providing high-value de-risking platforms for recapitulating properties of respective organs. These 3D assays can potentially fill the gap and connect the missing link between primary drug screening of compounds and forward lead optimisation into animal and human clinical trials (Figure 7.3).
Inkjet dispensing technologies: recent advances for novel drug discovery
Published in Expert Opinion on Drug Discovery, 2019
Sina Azizi Machekposhti, Saeid Mohaved, Roger J. Narayan
A process of discovering new candidate medications is known as drug discovery. Multiple tests should be conducted in the drug discovery process to examine new drug and verify various factors such as the efficacy, safety, and dose of the drug. Inkjet printing technologies can rapidly develop more reliable and cost-effective in vitro models, which will enhance the prediction of the efficacy, toxicity, and pharmacokinetics of the drug compounds in humans. In the following section, we will consider the working principles of the DOD inkjet bioprinters and will review recent studies of the various types of printing technologies. The critical parameters and current limitations of the inkjet printing technology will be examined in Section 3. Popular inks will be reviewed in Section 4. Section 5 will briefly explain regulatory affairs associated with inkjet printing technology. Concluding remarks and the future direction of this technology will be considered at the end of this article.
A multiparametric organ toxicity predictor for drug discovery
Published in Toxicology Mechanisms and Methods, 2020
Chirag N. Patel, Sivakumar Prasanth Kumar, Rakesh M. Rawal, Daxesh P. Patel, Frank J. Gonzalez, Himanshu A. Pandya
The drug discovery process was initiated in the year 1806 when a hypnotic agent called morphine was synthesized. However, the first attempt of drug discovery was mostly attributed to the Avogadro’s atomic hypothesis and coal-tar derivatives synthesis in the 1870s. The process of drug discovery starts with the identification of biological target and lead discovery (candidate, synthesis, characterization, high-throughput screening and assays for therapeutic efficacy) followed by lead optimization through pharmacokinetics and pharmacodynamics studies with preclinical and clinical development (phase-1, 2, 3 and 4). The newly synthesized drug should be approved by United States Food and Drug Administration (USFDA) before introducing to the market. This whole process takes around 15–20 years with massive financial investment. The rational drug design includes new drug discovery based on the knowledge of biological target pertain to therapeutic benefit. However, it mainly focuses on the accurate calculations of binding affinity calculations through customized structure-based approaches.
Advances of droplet-based microfluidics in drug discovery
Published in Expert Opinion on Drug Discovery, 2020
Yuetong Wang, Zhuoyue Chen, Feika Bian, Luoran Shang, Kaixuan Zhu, Yuanjin Zhao
Typically, a standard drug discovery approach can conceptually be broken down into three components, target selection, lead identification, and preclinical research [5]. First of all is to identify a potential molecular target, evaluate the activity modulation, and determine the feasibility of screening. A target can be a protein, protein complex, or RNA molecule, which is present in human or parasite/infective agent, associated with specific diseases [14–16]. The second component is the identification of the active ingredient, as a ‘lead’, from a natural remedy or design based on an understanding of the target [17,18]. In general, before becoming the drug candidate, the lead is optimized through screening up to ~10 6 compounds [9] via a high-throughput in vitro assay [19]. It is evaluated according to several indicators including the receptor-binding affinity [20], sustained functional activity, demonstrable selectivity against key undesired targets, viable synthetic routes, and promising commercial opportunities.
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