Department of Biomedical Engineering, NUS Engineering, National University of Singapore, Singapore.
Nanoscale Horiz. 2019 Mar 1;4(2):365-377. doi: 10.1039/c8nh00233a. Epub 2018 Oct 15.
The field of nanomedicine has made substantial strides in the areas of therapeutic and diagnostic development. For example, nanoparticle-modified drug compounds and imaging agents have resulted in markedly enhanced treatment outcomes and contrast efficiency. In recent years, investigational nanomedicine platforms have also been taken into the clinic, with regulatory approval for Abraxane® and other products being awarded. As the nanomedicine field has continued to evolve, multifunctional approaches have been explored to simultaneously integrate therapeutic and diagnostic agents onto a single particle, or deliver multiple nanomedicine-functionalized therapies in unison. Similar to the objectives of conventional combination therapy, these strategies may further improve treatment outcomes through targeted, multi-agent delivery that preserves drug synergy. Also, similar to conventional/unmodified combination therapy, nanomedicine-based drug delivery is often explored at fixed doses. A persistent challenge in all forms of drug administration is that drug synergy is time-dependent, dose-dependent and patient-specific at any given point of treatment. To overcome this challenge, the evolution towards nanomedicine-mediated co-delivery of multiple therapies has made the potential of interfacing artificial intelligence (AI) with nanomedicine to sustain optimization in combinatorial nanotherapy a reality. Specifically, optimizing drug and dose parameters in combinatorial nanomedicine administration is a specific area where AI can actionably realize the full potential of nanomedicine. To this end, this review will examine the role that AI can have in substantially improving nanomedicine-based treatment outcomes, particularly in the context of combination nanotherapy for both N-of-1 and population-optimized treatment.
纳米医学领域在治疗和诊断开发领域取得了重大进展。例如，纳米粒子修饰的药物化合物和成像剂导致治疗效果和对比效率明显提高。近年来，研究性纳米医学平台也已进入临床，Abraxane®和其他产品已获得监管批准。随着纳米医学领域的不断发展，已经探索了多功能方法，将治疗和诊断剂同时整合到单个粒子上，或者同时递送多种纳米医学功能化疗法。与传统联合治疗的目标类似，这些策略可以通过靶向、多药物递送来进一步提高治疗效果，同时保持药物协同作用。此外，与传统/未修饰的联合治疗类似，纳米医学药物递送通常在固定剂量下进行探索。在所有形式的药物给药中，一个持续存在的挑战是，药物协同作用在治疗的任何给定时间点都是时间依赖性、剂量依赖性和患者特异性的。为了克服这一挑战，纳米医学介导的多种疗法共同递送的发展使得将人工智能（AI）与纳米医学接口以维持组合纳米治疗中的优化成为现实。具体来说，在组合纳米医学管理中优化药物和剂量参数是人工智能可以发挥作用的一个特定领域，以充分发挥纳米医学的潜力。为此，本文将探讨人工智能在大幅提高基于纳米医学的治疗效果方面可以发挥的作用，特别是在针对个体患者和群体优化治疗的联合纳米治疗方面。
