Qing Liu, Ph.D., ASA Fellow

Consult in gene therapy and rare disease drug development and medical device clinical trial design and analysis, servicing both biopharmaceutical companies and investors. Develop clinical strategy, program and trial designs; research, develop and apply complex innovative designs and analysis, including analysis single-arm trial with small sample size (e.g. N = 1) with natural history study of real-world evidence, to improve efficacy and probability of technical and regulatory success; and perform statistical monitoring of blinded data to improve statistical analysis plans.

Substantial effort in the past year had been devoted to the migalastat NDA submission and response to FDA information requests. To fully understand efficacy of migalastat for adult Fabry patients with amenable mutations, a new set of analyses were performed following the 2016 FDA draft guidance on IVD and therapeutic co-development. Specific analyses for the FDA information requests include 1. a permutation-based exact multiple imputation method to support the validity and robustness of complete case analysis, 2. a new stratified permutation test procedure for ANCOVA LSMeans analysis when there is a significant treatment by baseline interaction, 3. an integrated analysis of efficacy that combines both inter-group and intra-patient comparisons of efficacy for a critical sub group. After a decade of development, migalastat was approved by the FDA on August 10, 2018. To overcome the difficulty of small sample size for rare disease trials, we develop the most advanced trial designs and technologies and statistical analyses and drive regulatory and clinical innovations in clinical development. Specific novel designs include a randomized delayed start design with integrated analysis of efficacy of both inter-group and intra-patient comparisons, resulting in reduction of sample size by up-to 80%. This design was accepted by the FDA for a confirmatory trial. We are also developing a RWE randomized withdrawal design using a new efficient inter-group comparison that reduces the sample size by 50% - 70%. In addition, we develop a precision virtual matched control methodology to compare new therapies to external retrospective RWE studies; the methodology can be applied to AI big data-mining for selection of optimal treatment in real world medical practice.

There are 7,000 rare disease affecting 30 million Americans and 350 millions world wide. During the first 25 years of the Orphan Drug Act (passed in 1983), only 326 new drugs were approved by the FDA and brought to market for all rare disease patients combined. A substantial challenge to develop new drugs for rare disease is that small populations often restrict study design and replication, and use of usual inferential statistics. At Amicus, we apply the most advanced trial designs and technologies and innovative statistical analyses to clinical development of rare disease drugs.

L&A due diligence, research and publication in innovative clinical trial designs, consulting in drug, biologics and medical device trial designs and analysis.

Rare disease trials and analysis in narcolepsy and amyotrophic lateral sclerosis (ALS); research in adaptive design theoretical foundation and methodology for efficient sample size calculate.

Joined The R.W.J. Phamaceutical Research Institute, a JNJ company, after leaving the FDA as the project statistician for a COX 2 inhibitor for pains. Successfully filed a dispute resolution on FDA’s non approval decision on the use of topiramate for the treatment of Lennox-Gastaut syndrome with an innovative analysis that won FDA approval; developed an adaptive statistical analysis planning (ASAP) process and analytics for blinded statistical monitoring of ongoing clinical trial data that led to better statistical analysis and fast top line delivery.

Statistical reviewer the division of biometrics 1/CDER. Broad review experience in CNS, psychiatry, oncology and hematology, and cardiovascular drugs including rare disease NDAs; pioneered and initiated FDA research in adaptive designs for drug development; first advocated multiplicity adjustment for secondary endpoints; and pioneered MMRM for longitudinal data analysis.

Pediatric rare cancer clinical trial design and analysis; PK/PD modeling; historical data analysis and case control study of genetic mutations; statistical support for grant applications in pharmaceutical science and WHO pandemic research.