探討新藥開發導入大數據整合臨床試驗管理系統的影響

Abstract

本篇文章目的在於探討利用大數據資料分析整合至臨床試驗管理系統Clinical Trial Management System 對於藥廠新藥開發的影響；近年來由於大數據的盛行，許多產業陸續引入大數據的應用來縮短產品開發時程，對新藥開發公司來說，每個藥物從研發進入臨床試驗到上市，平均需要7~15年，因此如何在藥物開發各階段利用大數據縮短時程，對於藥廠來說十分重要。 臨床試驗管理系統CTMS主要應用在臨床試驗階段，分別收集上市前臨床試驗相關紀錄(Phase I、 II & III)及上市後的追蹤(Phase IV)，現行CTMS系統大部分後端都已有相當龐大的醫院跟醫生數據，其中數據報括醫院、醫生資料及各式臨床實驗資料，但在於進行臨床試驗時，並沒有先行利用這些資料來分析哪些醫院或醫生適合進行該臨床實驗，白白浪費了如此有價值的資料在後端；大數據則是著重在針對醫院及醫生資料進行蒐集，包括擅長領域及經手過的臨床案件，統計以往參於臨床試驗時的病患招募率來做為臨床試驗評估要點。 對於臨床試驗進程是否會有顯著影響，將會是本篇論文的討論重點，由於此論文存在量化侷限，因此將透過質化研究的方式來進行探討並進一步改良發展創新模式，透過深度訪談的方式來歸納重點並探討其研究發展價值。

The purpose of this thesis is exploring the impact of Drug Development and import Bid Data integration with Clinical Trial Management System. In recent years, the prevalence of Big Data makes many industries import related applications to decrease product development timeframe. For pharmaceutical company, every new drug development from research to clinical trial completed takes 7 ~ 15 years. Therefore, it is very important for pharma to use Big Data to shorten each stage of drug development. Clinical Trial Management System (CTMS) is using for tracking each stage of clinical trial including Phase I, II, III & IV. Current CTMS already contain large data of sites & investigators including clinical trial data. However, pharma does not use these data to identify which site or investigator suitable for which clinical trial study. The application of Big data in clinical trial can collect site & investigators data and also analysis pass patient recruitment rate as reference. The focus point of thesis is significant impact to clinical trial. Due to this thesis has quantitative limitation, qualitative research will be used to find out any possible modules. This thesis will use depth interview to conclude discussion and develop research value.