There has been a significant increase in the cost and timeline of delivering new drugs for clinical use over the last three decades. Despite the increased investments in research infrastructure by pharmaceutical companies and technological advances in the scientific tools available, efforts to increase the number of molecules coming through the drug development pipeline have largely been unfruitful. A non-systematic review of the current literature was undertaken to enumerate the various strategies employed to improve the success rates in the pharmaceutical research and development. The review covers the exploitation of genomics and proteomics, complementarity of target-based and phenotypic efficacy screening platforms, drug repurposing and repositioning, collaborative research, focusing on underserved therapeutic fields, outsourcing strategy, and pharmaceutical modeling and artificial intelligence. Examples of successful drug discoveries achieved through application of these strategies are highlighted and discussed herein. Genomics and proteomics have uncovered a wide array of potential drug targets and are facilitative of enhanced scrupulous target identification and validation thus reducing efficacy-related drug attrition. When used complementarily, phenotypic and target-based screening platforms would likely allow serendipitous drug discovery while increasing rationality in drug design. Drug repurposing and repositioning reduces financial risks in drug development accompanied by cost and time savings, while prolonging patent exclusivity hence increased returns on investment to the innovator company. Equally important, collaborative research is facilitative of cross-fertilization and refinement of ideas, while sharing resources and expertise, hence reducing overhead costs in the early stages of drug discovery. Underserved therapeutic fields are niche drug discovery areas that may be used to experiment and launch novel drug targets, while exploiting incentivized benefits afforded by drug regulatory authorities. Outsourcing allows the pharma industries to focus on their core competencies while deriving greater efficiency of specialist contract research organizations. The existing and emerging pharmaceutical modeling and artificial intelligence softwares and tools allow for in silico computation enabling more efficient computer-aided drug design. Careful selection and application of these strategies, singly or in combination, may potentially harness pharmaceutical research and innovation.

中文翻译：

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探索提高药物发现和开发项目成功性的不同方法：综述

在过去的三十年中，为临床使用提供新药的成本和时间表都有显着增加。尽管制药公司增加了对研究基础设施的投资，并且在可用的科学工具方面取得了技术进步，但是增加通过药物开发渠道获得的分子数量的努力在很大程度上没有取得成果。对当前文献进行了非系统的综述，以列举用于提高药物研究和开发成功率的各种策略。综述涵盖了基因组学和蛋白质组学的开发，基于靶标和表型功效筛选平台的互补性，药物的重新定位和重新定位，合作研究，侧重于服务不足的治疗领域，外包策略，以及药物建模和人工智能。本文重点介绍并讨论了通过应用这些策略获得成功药物发现的示例。基因组学和蛋白质组学已经发现了许多潜在的药物靶标，并有助于加强对严格靶标的识别和验证，从而减少了与功效相关的药物消耗。当互补使用时，表型和基于靶标的筛选平台可能会允许偶然发现药物，同时增加药物设计的合理性。药物的重新定位和重新定位降低了药物开发中的财务风险，并节省了成本和时间，同时延长了专利独占性，从而增加了创新公司的投资回报。同样重要 协作研究有利于交叉应用和改进思想，同时共享资源和专业知识，从而减少了药物发现早期的间接费用。服务不足的治疗领域是利基药物发现领域，可用于试验和启动新型药物靶标，同时利用药物监管机构提供的激励性利益。外包使制药行业可以专注于自身的核心竞争力，同时提高专业合同研究组织的效率。现有和新兴的药物建模以及人工智能软件和工具可进行计算机计算，从而实现更高效的计算机辅助药物设计。仔细选择或单独或组合使用这些策略，