Starting from drug discovery, through research and development, to clinical trials and FDA approval, artificial intelligence (AI) plays a vital role in planning, developing, assessing modelling, and optimization of product attributes. In recent decades, machine-learning algorithms integrated into artificial neural networks, neuro-fuzzy logic and decision trees have been applied to tremendous domains related to drug formulation development. Optimized formulations were transformed from lab to market based on optimized properties derived from AI Technologies. Research and development in pharmaceutical industry rely upon computer-driven equipment and machine learning technology to extract data, perform simulations, modelling, and optimization to get optimum solutions. Merging AI technologies in various steps of pharmaceutical manufacture is a major challenge due to lack of in-house technologies. In silico studies based on artificial intelligence are widely applied as effective tools to screen the market needs of medications and pharmaceutical services through inspecting scientific literature and prioritizing medicines for specific illnesses or a particular patient. Specialized personnel who excel in scientific and data science with analytical knowledge are essential for transformation to smart manufacturing and offering services. However, privacy, cybersecurity, AI-dependent unemployment, and ownership rights of AI technologies require proper regulations to gain the benefits and minimize the drawbacks.

中文翻译：

---

人工智能技术应用于医药产品和服务开发的当前和未来前景的优缺点

从药物发现开始，经过研究和开发，再到临床试验和 FDA 批准，人工智能 (AI) 在规划、开发、评估建模和产品属性优化方面发挥着至关重要的作用。近几十年来，集成到人工神经网络、神经模糊逻辑和决策树中的机器学习算法已应用于与药物制剂开发相关的巨大领域。基于人工智能技术的优化特性，优化的配方从实验室转变为市场。制药行业的研发依靠计算机驱动的设备和机器学习技术来提取数据、进行模拟、建模和优化以获得最佳解决方案。由于缺乏内部技术，将人工智能技术融入药品制造的各个步骤是一个重大挑战。基于人工智能的计算机研究被广泛应用作为有效工具，通过检查科学文献并优先考虑针对特定疾病或特定患者的药物来筛选药物和制药服务的市场需求。擅长科学和数据科学并具有分析知识的专业人员对于向智能制造和提供服务转型至关重要。然而，隐私、网络安全、人工智能相关的失业和人工智能技术的所有权需要适当的监管才能获得好处并最大限度地减少弊端。