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Regulatory Governance of AI in Medicine in the Greater Bay Area

Calvin WL Ho

Funding Scheme : General Research Fund

Project Number : 17624622

Project Title (in English and Chinese ) :

Regulatory Governance of AI in Medicine in the Greater Bay Area


Principal Investigator (English) : Calvin WL Ho

Co - Investigator(s) :

  • Dr DU, Li

  • Dr Ji, Ping

  • Prof Leung, Gilberto Ka-kit

  • Dr Zhang, Haihong

Exercise Year : 2022 / 23

Fund Approved : HK$ 554,741

Completion Date : 30-4-2024

Abstract as per original application (English/Chinese):

The main aim of the proposed study is to examine how a participatory and collaborative approach to the regulatory governance of medical devices based on artificial intelligence (AI) or machine learning (ML) should be developed and implemented in Hong Kong SAR, as part of the Guangdong-Hong Kong-Macau Greater Bay Area (GBA). In this connection, it also seeks to explicate what it means to be “participatory” and “collaborative”; these being regulatory principles that have been put forward by the International Medical Device Regulators Forum (IMDRF), and implicit in the “Guangdong-Hong Kong- Macau Greater Bay Area Pharmaceutical and Medical Device Regulatory Innovation and Development Work Plan” (GBA Medical Device Work Plan). AI/ML-based medical devices are increasingly being incorporated into medical workflows and clinical care pathways. Expected benefits include earlier and more cost-effective interventions, greater diagnostic and prognostic accuracy, better access to care, and more effective cost control. However, ethical and legal challenges that need to be addressed include means to ensure the safety and effectiveness of these devices, improper data appropriation and use, decisional opacity, bias and liability. The three constituent jurisdictions in the GBA currently have different regulatory approaches to govern medical devices, and there is no specific ethical or regulatory guidance on AI/ML-based medical devises. Findings in this study are expected to: (1) Identify obstacles to the uptake of AI/ML-based medical devices in the GBA from the perspectives of the healthcare institutions, healthcare providers and device developers/manufacturers (“key stakeholders”); (2) Indicate the extent that these obstacles are attributable to different ethical, professional, institutional and/or regulatory differences; and (3) Set out possible solutions or responses to these obstacles that are proposed by the key stakeholders. In collaboration with the Hong Kong Academy of Medicine, this study will contribute directly to the development of new ethical and professional guidelines and new training programmes for healthcare institutions in Hong Kong, Macau and the University of Hong Kong – Shenzhen Hospital (this being the first designated medical institution under the GBA Medical Device Work Plan). To support regulatory alignment and/or convergence within the GBA, findings on regulatory obstacles and possible solutions will be shared with the Hong Kong Department of Health (and the Medical Device Control Office), Macau Health Bureau, Guangdong Health Commission and the National Medical Products Administration. Additionally, the research team will work with healthcare institutions to develop a system to track the uptake of AI/ML-based medical devices.

對於基於人工智能 (AI) 或機器學習 (ML) 的醫療設備,本研究項目的主要目的是製定一種參與性和協作性的監管治理,以在香港和大灣區 (GBA) 實施。在這方面,該項目還試圖解釋“參與”和“協作”的含義; 這些是“國際醫療器械監管機構論壇”(IMDRF)推薦的監管原則。 這些原則也隱含在《粵港澳大灣區藥品醫療器械監管創新發展工作方案》中 (醫療器械工作計劃)。 越來越多基於 AI/ML 的醫療設備被納入醫療工作流程和臨床護理路徑。預期的好處包括更早和更具成本效益的醫療護理、更高的診斷和預後準確性、更好的醫療服務以及更有效的成本控制。然而,道德和法律挑戰包括缺乏明確的法規來確保這些設備的安全性和有效性、不當的數據挪用和使用、決策不透明、偏見和不明確的法律責任。大灣區的三個組成轄區目前對醫療器械有不同的監管方法。 基於 AI/ML 的醫療設備也沒有具體的倫理或監管指導。本研究的結果預計將: (1) 從醫療機構、醫療保健提供者和設備開發商/製造商(“關鍵利益相關者”)的角度,識別大灣區採用基於人工智能/機器學習的醫療設備的障礙; (2) 指出這些障礙可歸因於不同的道德、專業、制度和/或 監管差異; 和 (3) 列出關鍵利益相關者針對這些障礙提出的可能解決方案或應對措施。 與香港醫學專科學院合作,這項研究將直接有助於為香港、澳門和香港大學深圳醫院的醫療機構制定新的倫理和專業指南以及新的培訓計劃。 港大-深圳醫院是大灣區醫療器械工作計劃下的首家定點醫療機構。有關監管障礙和可能解決方案的調查結果將與香港衛生署(和醫療器械司)、澳門衛生局、廣東省衛生委員會和國家藥品監督管理局分享。 目標是支持大灣區內的監管協調和/或融合。此外,研究團隊將與醫療機構合作開發一個系統,用於跟踪基於 AI/ML 的醫療設備的使用情況。

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