Held on October 18, 2007 at the Radisson Hotel Northbrook.
The Program consisted of three presentations:
- Continuous Reassessment Method in Phase 1 Dose Finding Studies Yi-Lin Chiu, Ph.D., Abbott Laboratories
- Statistical Considerations and Challenges in Adaptive Designs that Combine Phase II and III - A Case Study Charlie Cao, Ph.D., TGRD
- Non-Inferiority Testing in Thorough QT/QTc Studies Balakrishna Hosmane, Ph.D., Northern Illinois University
Continuous Reassessment Method in Phase 1 Dose Finding Studies by Yi-Lin Chiu, Ph.D., Abbott Laboratories
Biographical Background Dr. Chiu is currently employed as an Associate Director of Statistics at Abbott. She has 10 years of industry experience in the Pharmaceutical Business. She is an Associate Fellow of the Volwiler Society for Exceptional Abbott scientists and researchers. She has experience in a many therapeutic areas including, gastro-intestinal, anti-viral, infectious diseases, cardiovascular, diabetes, and oncology. During her career in the pharmaceutical industry, she has performed a wide variety of analyses, including, analyses of pharmacokinetic and pharmacodynamic data, special population studies (pediatric, hepatic impairment, etc), efficacy/safety, and non-inferiority studies, QT studies, in-vitro dissolution studies, pharmacogenomic studies, animal studies, bridging studies, investigator-initiated studies, and post marketing studies. She has participated in 27 regulatory submissions. Dr. Chiu has PhD and a Master’s degree in statistics both from Northwestern University. Before joining Abbott, she also worked as a Biostatistician at the Northwestern University Medical School and Children’s Memorial Hospital.
Abstract Background: Abbott compound ABT-X is being developed for treating selected types of malignancy. The primary objective of a Phase I dose-escalation study is to determine the maximum tolerated dose (MTD) in humans. The conventional rule-based 3+3 design and a continual reassessment methodology (CRM) utilizing either maximum likelihood (ML) or Bayesian approach have been considered. The objective of this research is to evaluate the operating characteristics of the three methods via simulations. MTD is defined as the dose at which 30% of subjects experience a dose-limiting toxicity (DLT).
Methods: In the study, three subjects will be treated per dose level, beginning with the starting dose of 10 mg. For the conventional 3+3 design, if 0/3 subjects experience a DLT, 3 subjects will be enrolled at the next dose level based on a modified Fibonacci sequence. If a DLT is observed in 1/3 subject, an additional cohort of three subjects is enrolled at this same dose level, and if DLTs are observed in ³2/6 subjects, subjects may be enrolled at a lower dose level. The MTD is selected as the highest dose level at which DLT occurs in less than 33% of the subjects. For the proposed CRM, there are two stages. In Stage 1, the study drug dose will be escalated with a doubling of dose not to exceed an increase of 100 mg until the first DLT is observed. Stage 2 will use a dose escalation strategy based on a two-parameter logistic regression model for the relationship between dose and DLT rate. ABT-X dose will be escalated/de-escalated according to the model-estimated MTD, utilizing the maximum likelihood or Bayesian methods. Non-informative priors for the slope and MTD are used for the Bayesian approach.
Results and Conclusions: We assessed 14 dose-toxicity curves, spanning the expected dynamic range of ABT-X doses. The operating characteristics (estimated MTD, true DLT rate associated with the estimated MTD, sample size, and subjects dosed above a dose corresponding to 90% toxicity rate [D90]) are evaluated among the CRM-ML, CRM-Bayesian and the conventional rule-based 3+3 design. Compared with a conventional rule-based 3+3 design, both the ML and Bayesian approaches within the CRM design are expected to estimate the ABT-X MTD more accurately while studying fewer subjects overall and/or at potentially toxic doses. Furthermore, both of the proposed CRM approaches may reduce the number of subjects exposed to non-efficacious doses. Although the Bayesian approach does not provide remarkable savings in the number of subjects over the ML method, the Bayesian methodology allows for interval estimation of MTD.
Statistical Considerations and Challenges in Adaptive Designs that Combine Phase II and III - A Case Study by Charlie Cao, Ph.D., TGRD
Biographical Background Dr. Cao is currently an Associate Director of Statistics at Takeda Global Research & Development Center. Prior to joining Takeda, Dr. Cao worked at Abbott Laboratories and prior to this, he worked for Glaxo. He has over 15 years of Pharmaceutical experience. Dr. Cao has a PhD degree in Statistics from Duke University. He has a wide range of therapeutic work experience within the pharmaceutical industry covering Phase I to IV studies. He has contributed to various scientific publications and conferences and continues to work on independent research in various areas of interest.
Abstract In this discussion, we will focus on the statistical considerations and challenges with regard to seamless study designs that combine Phase II and Phase III studies within the context of adaptive designs. These will be discussed in the context of a case study to illustrate these types of designs and to help illustrate the challenges that one may encounter from a statistical perspective. This study was discussed with FDA and other agencies and agreed as a single pivotal trial for NDA filing.
Non-Inferiority Testing in Thorough QT/QTc Studies by Balakrishna Hosmane, Ph.D., Northern Illinois University
Biographical Background Dr. Hosmane is a Statistics Faculty at Northern Illinois University and has been teaching there for the last 23 years. He serves as Director of Consulting Services at NIU. His main research interest is in categorical data, linear and nonlinear mixed models and pharmaceutical statistics. He has been working with statisticians and pharmacokineticists of Abbott Laboratories for the last 18 years as a consultant. He received his PhD from the University of Kentucky and has published over 35 research articles both in applied and theoretical journals.
Abstract Evaluation of new drugs for unwanted effects on electrical properties of the heart is receiving heightened attention from pharmaceutical companies and regulatory agencies. This attention arises from recent scientific research that links drug effects in cellular ion channels to changes in electrical characteristics of the electrocardiogram (ECG) that predict clinically important cardiac arrhythmias. An assessment of non-inferiority of the higher dose to placebo is performed in four-period cross-over study as well as four-group parallel study by the union- intersection test within the framework of a linear mixed effects analysis. For the purposes of planning such a study, the joint distribution of the estimate of the difference in means of high dose of investigational drug and the placebo was derived. The power of thorough QT/QTc study evaluated using the joint distribution and the simulation study were quite close.