2019年年末，新冠肺炎COVID-19疫情在各國迅速擴散，為此，各領域之專家學者創立專利開放平台Open COVID Pledge，呼籲免費提供專利和版權，以利各國在公共衛生危機得以加速解決疫情危機。
因科技進步，人工智慧（Artificial Intelligence，AI）已可執行創作及思考，甚至參與科學研發，對發明有實質上之貢獻。惟現行專利制度，不承認非人類之發明人，使人工智慧發明面臨適用上之困境。且就現階段而言，於醫學製藥領域，已有人工智慧研發之藥物順利進入臨床試驗階段，因而衍生出此類藥物於專利法上的法律問題。
依此，本文將透過探討美國、歐盟及台灣專利法規制度，嘗試定義人工智慧藥品發明之專利適格性，以及專利要件判斷標準提出相應判斷方式之修正，並延伸至人工智慧產出發明之專利適格性及專利要件審查標準之修法建議。後進一步透過歸納人工智慧於研發過程之角色定位及貢獻程度，以及人工智慧發明人地位之認定及發明專利權之權利歸屬問題，試圖賦予人工智慧部分權利主體與建立因應現行科技發展之權利歸屬系統。
本文認為，人工智慧正處於快速發展之過程，現行專利法相關規定及審查標準應與時俱進，於不同類型之人工智慧產出發明做出相應之調整；於權利主體方面，藉由判斷實際對該發明之貢獻程度定義人工智慧之發明人適格性、以及分析相關自然人之利益分配與現行法制規範建構人工智慧產出發明之權利歸屬系統，使人工智慧產出發明得順利取得專利權，以促進人工智慧產業創新發展。

In recent years, issues related to Artificial Intelligence (AI) have garnered significant attention, with its associated technologies widely used across various fields, including the medical and pharmaceutical industries. At present, AI-generated drug has successfully entered multi-regional Phase II clinical trials, leading to legal debates regarding patent law in this area.
Intellectual property law such as patent law is enacted to encourage invention and creation, and the current premise of legal protection should be the mental activity of human, however, the only subject of rights of inventor and creator is “natural persons”. It may cause problems when AI with the advancement of technology, has begun to engage in creating and thinking, and can contribute to research and development, becoming a genuinely contributory inventor. Thus, it is crucial to determine in advance whether to grant eligibility for AI as a subject of rights.
Therefore, this article discusses the patent eligibility of AI-generated pharmaceutical inventions and extends inference to AI-generated inventions. In addition, it will cut through the legislative purpose of patent law and analyze the identification of the status of AI inventor and the issue of the patent right ownership.

壹、 中文部分

一、 專書

1. Michael Negnevitsky著，顧立栩、沈晉惠譯（2007），人工智慧:智慧型系統導論，第二版，全華圖書。
2. 王澤鑑（2020），民法總則，修訂新版。
3. 李茂堂（1997），專利法實務，初版，健行文化。
4. 松尾豐著，江裕真譯（2016），了解人工智慧的第一本書：機器和人工智慧能否取代人類？，初版，經濟新潮。
5. 張志勇、廖文華、石貴平，王勝石、游國忠（2007），人工智慧，二版，全華圖書。
6. 陳文吟（2020），我國專利制度之研究，七版，五南。
7. 曾陳明汝著，蔡明誠續著（2009），兩岸暨歐美專利法，修訂三版，新學林。
8. 楊智傑（2014），專利法，一版，新學林。
9. 楊智傑（2015），美國專利法與重要判決，初版，五南。
10. 楊智傑（2019），智慧財產權法，三版，新學林。
11. 經濟部智慧財產局（2004），歐洲專利須知─申請人指南第1部分，十版，台北: 經濟部智慧財產局。
12. 經濟部智慧財產局（2021），專利法逐條釋義，2021年6月版。
13. 蔡明誠（2023），智慧權法原理，初版，元照。
14. 謝邦昌、蘇志雄（2020），人工智慧導論，初版，方集。
15. 謝銘洋（2023），智慧財產權法，增修12版，元照。
16. 魏季宏、張維平、柯清邁（2022），AI資通科技應用，一版，新學林。

二、 專書論文

1. 沈宗倫（2018 ），人工智慧科技與智慧財產權法制的交會與調和，收於：人工智慧相關法律議題芻議，頁181-214。
2. 謝銘洋（2004），德國專利制度，收於：「智慧財產權之制度與實務」，頁83-106。

三、 期刊論文

1. 尹守信（2005），淺析美國專利法上之非顯而易知性要件，智慧財產權月刊，84期，頁68-81。
2. 尹守信（2005），淺析美國專利法上之新穎性要件，智慧財產權月刊，78期，頁52-70。
3. 李素華（2016），我國藥品專利保護之現況與未來—從專利連結制度之研擬談起，智慧財產權月刊，216期，頁5-28。
4. 林宗緯（2020），勾勒邊際－論人工智慧發明人資格，專利師，43期，頁58-72。
5. 邱俊銘（2023），變更專利申請人主體認定原則之研析（下）——以我國規定及司法判決為例，智慧財產權月刊，293期，頁29-44。
6. 姚信安（2018），論共同發明人之判斷──以美國生化領域實務見解簡評智慧財產法院一○二年度民專上字第二三號民事判決，月旦法學雜誌，275期，頁122-138。
7. 孫永年（2019），人工智慧的醫療照護應用，科學發展，555期，頁42-47。
8. 徐道義（2009），當人工智慧融入數位媒體藝術，美育，169期，頁30。
9. 徐龍（2021），論人工智慧創作之法律屬性與保護，東吳法律學報，第33卷第1期，頁139-181。
10. 袁建中（1999），「電腦軟體相關發明專利審查基準」介紹(一)─談新基準之審查觀念，智慧財產權，11期，頁25-34。
11. 高慶仁（2023），論專利制度該如何應對人工智慧之創作，專利師，55期，頁73-101。
12. 許忠信（2020），論 AI 專利申請之程序性與允許性要件，高大法學論叢，16卷第1期，頁43-95。
13. 陳家駿（2021），AI新藥開發設計應用暨其可專利性之主客體法律議題探析，月旦民商法雜誌 73期，頁99-128。
14. 陳陽升（2023），從法治原則探索人工智慧之應用界限，台灣法律人，26期，頁97-106。
15. 童厚傑、王信傑（2023），生成式人工智慧的專利的現況，萬國法律，251期，頁48-62。
16. 黃仁志（2023），生成式 AI 的應用，風險與對應政策，經濟前瞻，208期，頁80-86。
17. 楊利華（2023），人工智能生成技術方案的可專利性及其制度因應，中外法學，206期，頁346-364。
18. 葉雪美（2007），美國設計專利類型的揭露要件與權利保護，智慧財產權，101期，頁30-63。
19. 葉雲卿（2019），新一代Alice／Mayo二階段軟體專利適格性判斷基準之形成與運用，智慧財產評論，15卷2期，頁21-80。
20. 趙慶泠（2015），電腦軟體專利標的適格性之測試法演進─從歐洲觀察美國，智慧財產權月刊，201期，頁5-47。
21. 劉依蓁（2021），國際生技醫藥管理政策與重大議題分析，醫藥生技，64期，頁13-17。
22. 鄧哲明（2013），新藥的研發流程概論，科學月刊，第44卷第2期。
23. 鄭中人（2001），論我國發明專利要件之立法政策及其演變，智慧財產權，32期，頁3-40。
24. 賴文智（2023），從歐盟首部 AI監管法，看臺灣 AI立法方向與挑戰？，會計研究月刊，457期，頁102-107。
25. 顏吉承（2015），擬制喪失新穎性與先占之法理—以智慧財產法院102年度行專訴字第114號判決為中心，專利師，23期，頁40-55。

四、 碩博士論文

1. 王茹玉（2016），藥廠專利侵權訴訟外之紛爭解決機制探討，東吳大學法學院法律學系法律專業碩士論文。
2. 林美伶（2016），以深度卷積神經網路做人臉辨識，國立中央大學資訊工程研究所碩士論文。
3. 洪嘉蔚（2018），論美國專利法上發明與發現之區分，國立成功大學法律學研究所碩士論文。
4. 張秉貹（2010），論醫藥品專利之權利範圍與侵害－以延續性醫藥品為中心，東吳大學法學院法律學系法律專業碩士論文。
5. 黃雯琪（2020），人工智慧專利保護要件之研究，國立高雄大學財經法律學系研究所碩士論文。
6. 劉慧如（2023），AI相關發明申請專利之特殊性，國立成功大學法學系碩士在職專班碩士論文。

五、 法院判決

1. 智慧財產法院98年度民專上字第39號民事判決。
2. 智慧財產法院102年度民專上字第23號民事判決。
3. 智慧財產法院104年度民專上字第22號。
4. 智慧財產及商業法院 110 年度行專訴字第 3 號判決。
5. 智慧財產及商業法院民事判決111年度民專上字第24號。

六、 網路資源

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4. 吳培安 ，Exscientia鎖定難以成藥標靶 免疫調節AI新藥獲BMS授權2千萬美元入袋，環球生技，2021年08月19日，https://news.gbimonthly.com/tw/article/show.php?num=42314 （最後瀏覽日：2023年08月09日）。
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8. 科技新報，將精準醫療推向下一哩路，AI 手術機器人助醫師開創手術最大綜效，2020 年10月14日， https://technews.tw/2020/10/14/rosa-ai-robot-surgical-robotics-machine-learning/ （最後瀏覽日：2023年05月06日）。
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10. 許文馨，《變人》劇情起點：人工智慧可以作為專利申請的發明人嗎？DABUS案在各國與臺灣的最新進展，科學月刊，479期，2021年11月16日，https://www.scimonth.com.tw/archives/5443 （最後瀏覽日：2023年04月18日）。
11. 彭梓涵，AI Labs腦轉移AI再下一城！DeepMets獲越南B類醫材許可，環球生技月刊，2023年08月23日，https://news.gbimonthly.com/tw/article/show.php?num=61407 （最後瀏覽日：2023年09月06日）。
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15. 黃韻玲，歐洲議會通過採納《歐盟人工智慧法案》 率全球之先希望監管AI，公視新聞網，2023年06月15日，https://news.pts.org.tw/article/641674 （最後瀏覽日：2023年07月06日）。
16. 經濟部智慧財產局，第一篇程序審查及專利權管理，2022年版https://topic.tipo.gov.tw/patents-tw/cp-682-870070-5036b-101.html （最後瀏覽日：2023年07月27日）。
17. 經濟部智慧財產局，第二篇專利實體審查基準，2023年版https://topic.tipo.gov.tw/patents-tw/cp-682-870087-abf9a-101.html （最後瀏覽日：2023年07月27日）。
18. 劉馨香，AI藥物開發夯盤點12家2022年募資破千萬美元新創，環球生技，2022年08月30日，https://news.gbimonthly.com/tw/article/show.php?num=52814（最後瀏覽日：2023年12月05日）。
19. 劉馨香，產學研醫大秀醫療成果，AI技術加速精準診斷，衛生福利部食品藥物管理署智慧醫療器材資訊暨媒合平台，2022年06月20日，https://imdis.fda.gov.tw/docDetail.aspx?uid=99&pid=99&docid=50196 （最後瀏覽日：2022年11月25日）。
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貳、西文部分（按作者首字母排序）

I. Books

1. Frankish K. and Ramsey W. M. (2014). The Cambridge Handbook of Artificial Intelligence. Cambridge University Press.
2. Hibbard B. (2002). Super-Intelligent Machines. Springer New York.
3. Levy D. (2005). Robots Unlimited Life in a Virtual Age. Wellesley Massachusetts: A K Peters/CRC Press.
4. Merges, R. P. (1997). Patent Law and Policy. (2nd ed). Matthew Bender.
5. Plotkin, R. (2009). The Genie in The Machine: How Computer-Automated Inventing is Revolutionizing Law and Business. Stanford Law Books.
6. Posner, R. A. (2003), Economic analysis of law (6th ed.)

II. Journal Papers

1. Abbott, R. (2016). I Think, Therefore I Invent: Creative Computers and the Future of Patent Law, Boston College Law Review, 57(4), 1079.
2. Abbott, R. (2018). Everything is Obvious, 66 UCLA L. Rev. 2, 6.
3. Afshar, M. S. (2022), Artificial Intelligence and Inventorship - Does the Patent Inventor Have to Be Human?, Hastings Science and Technology Law Journal, 13(1), 55-72.
4. Afshar, M. S. (2022), Artificial Intelligence and Inventorship – Does the Patent Inventor Have to be Human?, Hastings Science & Technology Law Journal, 13, 55-72.
5. Aliper, A., Plis, S., Artemov, A., Ulloa, A., Mamoshina, P., & Zhavoronkov, A. (2016). Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data, Molecular Pharmaceutics, 13(7), 2524.
6. Beck, B. R., Shin, B., Choi, Y., Park, S., & Kang, K. (2020). Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model. Computational and structural biotechnology journal, 18, 784-790.
7. Born, J., Manica, M., Cadow, J., Markert, G., Mill, N. A., Filipavicius, M., & Martínez, M. R. (2020). PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models. arXiv 2005.13285.
8. Burki, T. (2020), A new paradigm for drug development, Lancet Digit Health, 2, 225-227.
9. Chen, Y. T., Xie, J. Y., Sun, Q., & Mo, W. J. (2019). Novel drug candidates for treating esophageal carcinoma: A study on differentially expressed genes, using connectivity mapping and molecular docking. International Journal of Oncology, 54(1), 152-166.
10. Clifford, R. D. (1997), Intellectual Property in the Era of the Creative Computer Program: Will the True Creator Please Stand Up?, Tulane Law Review, 71, 1675-1703.
11. Cunningham, J. M., Koytiger, G., Sorger, P. K., & AlQuraishi, M. (2020). Biophysical prediction of protein–peptide interactions and signaling networks using machine learning. Nature methods, 17(2), 175-183.
12. De, T., Giri, P., Mevawala, A., Nemani, R., & Deo, A. (2020). Explainable AI: a hybrid approach to generate human-interpretable explanation for deep learning prediction. Procedia Computer Science, 168, 40-48.
13. Denicola, R. C. (2016). Ex machina: copyright protection for computer generated works. Rutgers University Law Review, 69, 251-287.
14. Dornis, T. W. (2020). Artificial Intelligence and Innovation: The End of Patent Law As We Know It, Yale Journal of Law & Technology, 23, 97-159.
15. Fogel, D. B. (2018). Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: a review. Contemporary clinical trials communications, 11, 156-164.
16. Fraser, E. (2016), Computers as Inventors – Legal and Policy Implications of Artificial Intelligence on Patent Law, SCRIPTed, 13, 305-333.
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III. Cases

1. U.S. Court of Appeals case: Thaler v. Vidal, 2021-2347, 2022 WL 3130863 (Fed. Cir. Aug. 5, 2022)
2. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1373 (Fed. Cir. 2011).
3. Burroughs Wellcome Co. v. Barr Labs., Inc., 40 F.3d 1223, 1228 (Fed. Cir. 1994).
4. Hybritech Inc. v. Monoclonal Antibodies, Inc.， 802 F.2d 1367, 1376（Fed.Cir.1986）
5. Johnson v. Duquesne Light Co., 29 F.2d 784 (1928).

IV. Official Documents

1. EPO publishes grounds for its decision to refuse two patent applications naming a machine as inventor
2. Press Communiqué on decisions J 8/20 and J 9/20 of the Legal Board of Appeal
3. Press Communiqué of 6 July 2022 on decision J 8/20 (AI system as inventor)
4. USPTO Petition decision: Inventorship limited to natural persons.
5. GOV.UK, A pro-innovation approach to AI regulation.
6. Oct. 2019 Patent Eligibility Guidance Update, 84 Fed. Reg. 202.

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