采访嘉宾：

Dr Richard Peck is Global Head of Clinical Pharmacology for Roche. He trained in pharmacology and medicine at Cambridge University and has over thirty years’ experience of pharmaceutical industry clinical pharmacology in GlaxoWellcome and Eli Lilly before he joined Roche. His research interests include understanding and utilising variability in drug response to improve drug dosing and clinical benefit in different patient groups; applying clinical pharmacology to enable the development of personalised/stratified medicines and the use of model-based drug development strategies.

作者：

Dewei Shang（尚德为）, Ph. D, Deputy Director of the Pharmacy Department in the Affiliated Brain Hospital of Guangzhou Medical University. Dr. Shang’s research focuses on pharmacometrics, metabolomics and phase I clinical research. He is Master Supervisor in Guangzhou Medical University. He is a member of Professional Committee of Pharmacometrics of China, Chinese Pharmacological Society. He serves as an evaluation expert for Center for Drug Evaluation, NMPA. He is an editorial member of Evaluation and Analysis of Drug Use in Hospital of China and a reviewer of more than 10 academic journals.

Dr. Shang hosts several research projects including Programs of Natural Science Foundation of China and Natural Science Foundation of Guangdong Province. He has participated in publishing more than 100 research papers, of which 19 papers included in SCI were published by the first author or corresponding author.

Dr. Dewei shang on behalf of the organization committee of ISQP:

Dewei shang:

Prof. Richard will have a conference report with topic of “Precision dosing, an industry perspective” in ISQP conference. Before the formal report, on behalf of the organizing committee, I had an email interview with Prof. Richard. Let’s take a look at his perspective on precision dosing.

Dewei Shang: Dear Prof. Richard, as a reputational clinical pharmacologist and pharmacometrician from the industry, could you please share your thoughts on the roles and responsibilities of the industry in pursuing precision dosing?

Prof. Richard: Precision dosing offers the potential to increase the effectiveness of some, perhaps many, of the drugs we use. Imagine if all patients with type I diabetes were treated with the same dose of insulin, some patients would be inadequately treated and become seriously ill with glucose levels that were still much too high, whilst others would be made seriously ill by being overtreated such that they often have glucose levels that are much too low. It is not so different for many of the drugs we are developing. Probably there is a single dose level of a drug that we consider to be acceptable but at this dose many patients are not adequately treated whilst others suffer adverse effects from being overtreated. Probably these drugs could be used much more effectively if the dose were varied for each patient. In my opinion the pharmaceutical industry has a responsibility to explore if precision dosing can help improve drug benefit and decrease risk and then develop the drugs using a precision dosing approach, regulators have a responsibility to demand this and guide how it is done, academia can help develop methods and help demonstrate the benefits of such an approach for drugs already on the market, technology providers have a responsibility to develop the tools to help implement precision dosing because it needs to be made as easy as possible for prescribers and these prescribers have a responsibility to accept precision dosing approaches and demand that payers reimburse them.   

Dewei Shang: In the era of big data, the technologies such as artificial intelligence and machine learning are changing the practice of medical care. Please share your thoughts on the application of these new methods in precision dosing?

Prof. Richard: The potential role of machine learning is very interesting and I think it could be very useful to help develop individual patient treatment algorithms, including individualised dosing. For drugs already approved this could potentially be done with the big data that could be collected from real world use of the drug. Of course this would need agreement on data standards, which data to collect, how to analyse it and where to store it safely such that it is accessible to all researchers who want to use it for high quality research activities. In drug development, especially early clinical development, the concept of big data is perhaps less applicable, often we have only a small number of patients included in phase 1 or 2 clinical trials. However, machine learning techniques such as reinforcement learning, causal inference and others are now being explored, often in combination with and informed by conventional PKPD modelling, as tools that could be used on smaller numbers of patients to identify optimal dosing and develop population and individual dosing algorithms. My group is involved in some of this work and we have high hopes of its eventual utility.

Dewei Shang: What's your expectations for clinical pharmacology in China?

Prof. Richard: Clinical pharmacology in China has grown hugely over the last decade and it is very exciting to see the huge steps forward being made in drug discovery, development and regulation in China by regulatory, academic and indstry scientists. I expect this to continue and for China to take its place as an equal partner with the rest of the world in advancing the discipline of clinical pharmacology and in bringing new drugs to patients and working out how to use the ones we already have much more effectively too.

Dewei Shang:

We thank Prof. Richard for accepting our interview and sharing his thoughts on the roles and responsibilities of the industry in pursuing precision dosing. We look forward to his presentation in the ISQP。

采访主要内容中文翻译：

尚德为（Qusetion）：作为一名业内著名的临床药理学家和药剂学家，您可以跟我们谈一谈工业界在追求精准给药方面的作用和责任吗？

Prof. Richard（reply）：精准给药具有使一些药（也可能是许多药）药效提高的潜力。想象一下，如果所有Ⅰ型糖尿病患者接受相同剂量的胰岛素治疗，那么一些患者将得不到充分的治疗并因血糖过高而病情严重。然而，另一部分人将因过度治疗导致血糖水平过低而加重病情。我们正在开发的许多药物也存在类似的情况。尽管采用单一给药剂量也可以，但在此剂量下，一些患者未得到充分治疗而其他患者则因过度治疗而遭受不良反应。如果给药剂量因人而异，可能会有更好的药效。我认为，制药工业界有责任探索精准给药是否能够提高药物效益，降低风险，并且用精准给药方法开发药物；监管者有责任要求并指导如何实施；学术界开发方法并阐明使用这种方法对已上市药物的益处；因为对医生来说，实行起来需要尽可能的简单，所以技术供应商有责任开发出助推精准给药的工具；医生们有责任接受精准给药方法并且要求患者采用。

尚德为（Qusetion）：大数据时代，人工智能、机器学习等技术正在改变医疗方式。您怎么看待这些新技术在精准给药方面的应用?

Prof. Richard（reply）：机器学习的潜在作用非常有趣。我认为它有助于开发个体患者治疗算法包括个体化给药。对于已经批准的药物，个体化给药可以通过搜集真实世界中药物使用的大数据来实现。当然，对数据标准需要达成一致，包括收集哪些数据，如何分析和数据存在哪里安全又便于所有希望将其用于高质量研究的研究人员访问。在药物研发，尤其是早期临床研发中，大数据的概念可能不太适用，因为通常I期或II期临床试验只有少数患者参与。但是，一些机器学习技术，例如强化学习、因果推理等正在探索中，通常也会结合传统PKPD模型并受其启发。PKPD模型适用于少量患者群体的研究，能够确定最佳剂量，开发群体和个体给药算法。我的团队参与了其中的一些工作，我们对它的最终效用寄予厚望。

尚德为（Qusetion）：您对中国的临床药理有什么期待吗？

Prof. Richard（reply）：在过去的几十年里，中国临床药理学获得了巨大的发展。非常开心能够看到在监管部门、学术界和工业界专家们的共同努力下，中国在药物发现、开发和监管方面取得了巨大进步。我希望能够继续前进，并希望中国作为与世界其他地区平等的伙伴在推进临床药理学科建设、为患者带来新药以及如何使已有药物发挥更强药效方面发挥作用。

焦正 教授