Indiana University-Purdue University Indianapolis (IUPUI) / Adverse drug events (ADEs) are injuries resulting from drug-related medical interventions. ADEs can be either induced by a single drug or a drug-drug interaction (DDI). In order to prevent unnecessary ADEs, many regulatory agencies in public health maintain pharmacovigilance databases for detecting novel drug-ADE associations. However, pharmacovigilance databases usually contain a significant portion of false associations due to their nature structure (i.e. false drug-ADE associations caused by co-medications). Besides pharmacovigilance studies, the risks of ADEs can be minimized by understating their mechanisms, which include abnormal pharmacokinetics/pharmacodynamics due to genetic factors and synergistic effects between drugs. During the past decade, pharmacogenomics studies have successfully identified several predictive markers to reduce ADE risks. While, pharmacogenomics studies are usually limited by the sample size and budget. In this dissertation, we develop statistical methods for pharmacovigilance and pharmacogenomics studies. Firstly, we propose an empirical Bayes mixture model to identify significant drug-ADE associations. The proposed approach can be used for both signal generation and ranking. Following this approach, the portion of false associations from the detected signals can be well controlled. Secondly, we propose a mixture dose response model to investigate the functional relationship between increased dimensionality of drug combinations and the ADE risks. Moreover, this approach can be used to identify high-dimensional drug combinations that are associated with escalated ADE risks at a significantly low local false discovery rates. Finally, we proposed a cost-efficient design for pharmacogenomics studies. In order to pursue a further cost-efficiency, the proposed design involves both DNA pooling and two-stage design approach. Compared to traditional design, the cost under the proposed design will be reduced dramatically with an acceptable compromise on statistical power. The proposed methods are examined by extensive simulation studies. Furthermore, the proposed methods to analyze pharmacovigilance databases are applied to the FDA’s Adverse Reporting System database and a local electronic medical record (EMR) database. For different scenarios of pharmacogenomics study, optimized designs to detect a functioning rare allele are given as well.

Quinolones are a group of antibiotics that have gained significant popularity on a global scale since the end of the last century. This popularity was predominantly based on their proven potency, broad coverage against a wide range of bacteria, in addition to possessing a favorable pharmacologic profile. Whereas quinolone-associated adverse reactions are generally tolerable and self-limiting, some reactions have generated heightened concerns due to their serious nature, which have resulted in label changes or even market withdrawal in some instances. This thesis investigates the association between quinolone antibiotics and two adverse reactions of an acute and serious nature: acute liver failure and retinal detachment. Each adverse reaction is investigated through integrating evidence from three studies utilizing different designs based on data from different sources, with each source offering a unique perspective on this issue. The first study type (chapter 2 for acute liver failure ‘ALF’ and Chapter 5 for retinal detachment ‘RD’) analyzes spontaneous reports submitted to the US Food & Drug Administration (FDA) adverse event reporting system database. Chapters 3 and 6 systematically identified all relevant (published and unpublished) clinical trials for occurrences of ALF and RD, respectively, among trial participants. Finally, chapters 4 (ALF) and 7 (RD) involved case-control analysis of a major US database of electronic health records for nearly 70 million inpatients admitted to more than 500 hospitals between 2000 and 2016. The FAERS analysis revealed a positive ALF signal with ciprofloxacin and a marginal signal for RD with moxifloxacin. Examination of the evidence from clinical trials revealed only two cases of ALF, one associated with gemifloxacin and one with moxifloxacin. No cases of RD were reported in any of the identified clinical trials. Primary analyses of the Health Facts® data revealed no overall association between quinolones and the risk of ALF or RD. However, elevated risk was identified in some subgroups, including African Americans (ALF, RD), Caucasians (ALF), women (ALF, RD), men (ALF), those ≤60 years of age (ALF) or 56-70 years of age (RD), and those with no or few comorbidities (ALF). Evidence from analyses of data from spontaneous reports and clinical trials provided some evidence for an elevated risk of ALF or RD following the systemic administration of quinolone antibiotics. Some evidence of elevated risk was also identified in the case-control analyses of inpatient EHR records. Findings from our six epidemiologic studies are in line with current advisories by FDA and Health Canada.

付記する学位プログラム名: 充実した健康長寿社会を築く総合医療開発リーダー育成プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(薬学) / 甲第22402号 / 薬博第840号 / 新制||薬||241(附属図書館) / 京都大学大学院薬学研究科薬学専攻 / (主査)教授 金子 周司, 教授 松原 和夫, 教授 土居 雅夫 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

The U.S. Food and Drug Administration (FDA) uses the FDA Adverse Event Reporting System (FAERS) to monitor adverse events resulting from pharmaceutical drug use. However, this system has limitations such as not allowing real-time data collection. To address these limitations, the FDA launched the Sentinel Initiative in 2008. This comparative case study was conducted to describe perceptions of investigating the efficacy of the Sentinel Initiative compared with the FAERS. The study was based on the theory of preemption as it emphasized the need for efficient means for providing unquestionable proof that consumers suffered adverse drug effects. The sample included interivews of 20 individuals, who worked closely with the FAERS program and were familiar with the Sentinel Initiative. In-depth key-informant interviews had been conducted to determine the perceptions of the participants regarding the challenges and benefits of the Sentinel Initiative compared with FAERS. To analyze data, content analysis was used. The study concluded that the FAERS and Sentinel Initiative provided a systematic database, which included health data, that could be used to improve public health. Due to the FAERS and Sentinel Initiative, adverse effects of drugs will be recognized and the safety of the patients and the public will be prioritized. The findings of this study have potential social impact for positive change at the societal level, organizational level, and individual level in terms of overall safety of the drugs. Sentinel initiative at its present state complements the existing FAERS and leverage its benefits by connecting at a grass roots level patients to an organization level as well as stakeholders to make an impact in providing safer drugs on the market.