SESSION A – The Annual Deming Conference on Applied Statistics

TITLE: Selected Topics of Statistics in Clinical Drug Development: A Statistical and Regulatory Perspective
SPEAKER: Dacheng Liu, Boehringer Ingelheim
Moderator: Naitee Ting

Abstract:

Clinical drug development is a complex process that involved years of investment and high failure rate. There are many areas that statistics can contribute to improve the efficiency of drug development, ranging from early phase dose finding to confirmatory trial designs. Novel statistical approaches have been implemented in recent years to improve this process. There have been notable shift in the regulatory landscape supporting these approaches, such as the FDA complex innovative design (CID), model informed drug development (MIDD) programs. In this short course, we will provide a broad perspective of how such statistical innovations contribute to clinical drug development. We will discuss relevant regulatory guidance. Topics to be covered include early phase dose finding, dose ranging, confirmatory adaptive designs, multiplicity, covariate adjustment, Go/NoGo decision making, Bayesian borrowing, estimand and missing data. We will provide examples from recent trials and drug reviews/approvals.

Instructors’ Biography:

Dacheng Liu is a Highly Distinguished Therapeutic Area and Methodology Statistician at Boehringer Ingelheim, with nearly two decades of experience in the pharmaceutical industry. He provides leadership in driving the statistical quality and fostering innovation of companywide clinical development programs across all therapeutic areas. He represents Boehringer Ingelheim in industry-wide groups and leads collaborations with US partners from both industry and academia. Before his current role, Dacheng held positions as the Global Head of Clinical Data Sciences and the US Head of Statistics, where he led both US and global teams in clinical drug developments of the company pipeline. He has extensive experience leading early and late-phase development in multiple disease areas, including landmark studies, regulatory submissions, and FDA advisory committee meetings. He has over 40 publications in areas of clinical research, trial design, statistical methodologies, and machine learning.