Introduction: Patent licensing plays a significant role in commercializing research outcomes and inventions for universities. Many universities proactively involve in licensing activity for financial returns and making advanced technologies into practice, especially for drug industry among universities. However, few papers focused on what influence licensing likelihood of the university patents. To bridge this gap, we intend to explore the determinants contributing to licensing activity of universities’ new drug patents and provide pertinent implications for research and practice. Methods: We empirically explore the determinants of patents licensing likelihood by using a panel dataset of 369 patents from IMS Lifecycle database. They include 142 licensed patents of new drug and 227 unlicensed patents of new drugs from various universities during 1980-2015. Based on the patent samples, eight variables are established and categorized into university level, patent level and drug level through United States Patent and Trademark Office, European Patent Office and IMS Lifecycle database. Binary regression model was used to analyze the variables. Results: Multiple regression results indicate our dataset fits the model better than a null regression. Our findings include (1) university research capability and breadth are positively related to the licensing likelihood of new drug patents from universities (2) research age is negatively correlated to the possibility of licensing activity (3) patent recognition, patent industry influence and patent complexity have strong impacts on licensing outcomes of new drug patents from university (4) higher number of drug indications actively helps universities to improve successful licensing likelihood of their new drug patents while drug focus does not. Conclusion: Our findings confirm patent quality as the core determinants that impact the likelihood of licensing outcomes for new drug patent from universities. At the same time, university level and drug level determinants also influence the licensing possibility of new drug from universities. Scientifically building more potential drug indications for new drug patents could help universities improve their licensing outcomes while universities engage in research capability and breadth.

簡介：專利許可被廣泛作為大學商業化其研究成果和發明的重要途徑。許多大 學會主動參與到專利許可的活動中。同時，專利許可在大學間的醫藥領域是非 常常見的行為，值得深入研究。現今很少研究會關注影響大學專利許可概率的 因素。為了填補這個研究空白，我們基於新藥專利嘗試探索大學專利許可的影 響因素和提出中肯的在研究上和實踐中的啟示。 方法： 我們運用 IMS Lifecycle 資料收集了 369 個新藥專利資訊，實證性地探索 專利許可概率的影響因素。這些資料包括來自 1980-2015 年間不同大學的 142 例 許可專利和 227 例未被許可的專利。基於我們收集到新藥專利資訊，我們再通 過美國專利局、歐洲專利局和 IMS Lifecycle 資料庫，構建出八個變量。這些變 量由大學層面、專利層面、藥品層面的潛在影響因素共同組成。隨後，我們採 用二元回歸模型分析這些變量。 結果： 多次的回歸結果顯示我們的資料較好的吻合我們所用的模型。研究發現： （1）大學研發能力和研究的範圍與大學新藥專利的許可概率成正相關關係。 （2）研究年限對專利許可的結果有負向的影響。（3）專利的認可度，專利的 原始影響力和專利的複雜程度均能影響大學藥品專利的許可概率。（4）新藥的 適應症的數量也能幫助提高大學新藥專利被成功許可的概率，而是否治療慢性 病對專利許可的結果沒有顯著影響。 結論：我們的研究驗證了專利品質仍然是影響大學新藥專利許可的核心影響因 素。同時，大學層面和新藥層面的變量也能影響大學新藥專利的許可結果。大 學在加強研發能力和研究的範圍的同時，科學性地構建更多的潛在的適應症將 有助於提高大學藥品專利的許可概率。