Abstract
摘要:生物技術與生技製藥工業已成為21世紀台灣命脈所繫之關鍵工業,但新藥研發是資源密集,長期投資與技術密集之高風險與高附加價值之工業,也是導致藥價昂貴的主要原因,為減少藥品研發之成本及降低藥品價格,我國生技製藥工業應以國外市場為對象發展學名藥及療效對等藥品為出發點。
全世界各國藥政主管機構均是以生物相等性審核學名藥以對等性或非劣等性審核療效對等藥品。而統計在評估生體對等性與療效對等性或非劣等性上拌演重要及不可或缺的角色,因此本專題研究為三年計劃共包括三部份:(1)平均生體對等性之評估,(2)個體生體對等性之評估,(3)療效對等性或非劣等性之評估。
學名藥評估主要資料為交叉設計下根據藥品有效或分布在血中濃度所導衍之藥物動力學的反應值。針對平均相等性方面,目前的方法是使用信賴區間評估生體對等性,但是它並非在原始尺度上學名藥與原研發等族群平均值比的最小變異估值發展出評估平均生體對等性的方法與其所需的樣本數,並以模擬試驗與現行的方法針對第一種錯誤機率與檢定力進行比較。針對個體的對等性方面,目前評估方面所使用的信賴上限亦非美國食物與藥品管理局所訂定評估參數之信賴上限。我們亦將導衍評估參數之不偏
Abstract: Biotechnology and biopharmaceutical industry is the key industry for Taiwan in the 21st century. New drug development is a high added value and high-risk business that requires huge capitals, long-term investment and intensive technology. This is the primary reason why patented pharmaceutical products are expensive. To cut down the development cost and to reduce drug price, development of generic drugs and therapeutically equivalent pharmaceuticals should be the starting point for Taiwan’s biopharmaceutical industry. Bioequivalence is employed to evaluate and approve generic drugs and therapeutically equivalence/non-inferiority is used to assess and approve therapeutically equivalent drug products by the health authorities around the world. Statistics therefore plays an important and indispensable role in evaluation of bioequivalence and therapeutically equivalence/non-inferiority. Hence this 3-year research project consists of three parts: (1) evaluation of average bioequivalence, (2) assessment of individual bioequivalence, and (3) appraisal of therapeutically equivalence/non-inferiority. For evaluation of bioequivalence, the data are the pharmacokinetic responses derived from the plasma concentration-time curve of the active ingredient under a crossover design. With respect to average bioequivalence, the confidence interval currently used for average bioequivalence is not the confidence interval for the ratio of the population means between the generic and innovative drugs on the original scale of the pharmacokinetic responses. A statistical procedure and its required sample size therefore will be developed based on the minimum variance unbiased estimator for the ratio of the population means between the generic and innovative drugs on the original scale for evaluation for evaluation of average bioequivalence. A simulation study will be conducted to compare the size and power between the current approach and ours. On the other hand, the current method for evaluation of individual bioequivalence recommended by the US FDA employs an upper confidence limit that is not a upper confidence limit for the parameter derived from individual bioequivalence criterion. We will develop a statistical procedure for evaluation of individual bioequivalence based on the distribution of an unbiased estimator of the individual bioequivalence criterion. Finally, under two different designs for the blinded reader study and based on the ratio of diagnostic accuracy between the test and reference drugs, we will develop statistical methods for appraisal of therapeutically equivalence/non-inferiority. A simulation study will also be conducted to investigate and to compare the size and power of different methods for evaluation of therapeutically equivalence/non-inferiority. Our method for therapeutically equivalence/non-inferiority can be directly applied to evaluation of diagnostic accuracy of biochips and biological products.
Keyword(s)
生物技術與生技製藥
生體相等性
療效對等性
重複交叉設計
盲性評估
Biotechnology and Biopharmaceutical
Bioequivalence
Therapeutic Equivalence
Replicated Crossover Design
Blinded Reader Study