The 3rd UMBC- Stanford Workshop on Clinical Trials and Regulatory Science

Transcription

1 The 3rd UMBC- Stanford Workshop on Clinical Trials and Regulatory Science Real World Evidence, Globalization, and Regulatory Science University of Maryland Baltimore County (UMBC) September 14 15, 2018 UMBC, (ITE Building,102 and 104, Lecture Halls) 1000 Hilltop Circle, Baltimore, MD 21250

2 Objectives The series of the UMBC-Stanford Workshop on Clinical Trial and Regulatory Science aims to bring together regulators, academic researchers, and industry professionals to discuss prominent issues of common interest, to share and exchange information and experiences, and to improve close collaborations to promote biomedical innovation in modern regulatory science. Target audience Regulatory scientists, statisticians, health policy professionals, clinicians, biopharmaceutical product development professionals, and other relevant research scientists. Organizing committee Faculty from UMBC, Stanford University, UM-CERSI, and leaders from FDA and industry. Sponsors & Supporting Organizations UMBC, Office of Provost and Department of Mathematics and Statistics M-CERSI, University of Maryland Center for Excellence of Regulatory Science and Innovation, and US FDA. Stanford University, Center for Innovative Study Design. ICSA, International Chinese Statistics Association. International Society for Biopharmaceutical Statistics (ISBS) Registration Online registration is required for everyone. Conference website: Regular registration for Sat. workshop: $199 (before or on Aug.31), $249 (after Aug. 1); government employees and academia: $50 (before or on Aug. 31), $80 (after Aug. 31); short course registration: $100; students with valid ID: $25 for workshop, $25 for short course. Dual registration for workshop and short course: $249 (before or on Aug. 31), $299 (after Aug. 31). Credit card is acceptable online, and check or cash payment is acceptable onsite (Sep.14-15). Lodging When making reservation, please use the reservation link provided under conference website: Double Tree BWI - (Hilton hotel chain) 890 Elkridge Landing Road Linthicum, MD Free airport shuttle to BWI: Yes Free WIFI: Yes Complimentary breakfast: No, but have restaurant Taxi cost to UMBC campus: $15-20 UMBC rate (standard room): $129 per night For more Information Please contact Dr. Yi Huang, Department of Mathematics and Statistics, University of Maryland Baltimore County (UMBC), 1000 Hilltop Circle, Baltimore, MD yihuang@umbc.edu. 1

3 The 3 rd UMBC-Stanford Workshop on Clinical Trials and Regulatory Science Real World Evidence, Globalization, and Regulatory Science Scientific Program Friday Sept. 14 Program Registration: Lobby of ITE building, open after 1:30pm Welcome Speech by Professor Bimal Sinha 2:00 pm - 2:05 pm, ITE Building 102 or 104, Lecture Hall Short Course: Multiple hypotheses, non-proportional hazards, group sequential analyses. Software: R (most recent version), gsdesign (3.0-4 from github/keaven/gsdesign, gmcp) Instructor: Keaven Anderson, PhD, Executive Director, Merck Research Laboratories Moderator: Yi Huang, UMBC Venue: ITE Building 102 or 104, Lecture Halls Time: 2:05 pm 3:50 pm, Short course session I 3:50 pm 4:10 pm, Coffee Break 4:10 pm 5:40 pm, Short course session II Conference Reception Lobby of ITE building, 5:40pm 6:50pm, Networking and conference mixer with catered food Poster Session Lobby of ITE building, open: 4:00pm 6:40pm (Poster session is also open from 9:00 am 5:00 pm during the conference on Sat. Sept. 15) (Friday 2:00pm 4:00pm, poster setup by participants. Poster stand and board will be provided) Saturday Sept. 15 Program (ITE Building 102 and 104, Lecture Halls) Registration: Lobby of ITE building, open after 8:00 am 8:00 am 8:30 am: Continental Breakfast 8:30 am 9:00 am: Opening and welcome remarks (ITE 104) Professor Antonio Moreira, Vice Provost of Academic Affairs, UMBC (10 min) Professor James Polli, Co-PI of M-CERSI, School of Pharmacy, UMB (10 min) Professor Tze Leung Lai, Stanford University (6 min) 2

4 Professor Yi Huang, UMBC (4 min) 9:00 am 9:50 am: Keynote speech (ITE 104) Chair: Dr. Jingyu (Julia) Luan, US FDA Dr. Woodcock s presentation Dr. Janet Woodcock, Director, Center for Drug Research and Evaluation, US FDA 9:50 am 10:00 am: Conference Group Photo (ITE 104) 10:00 am 10:20 am: Coffee Break 10:20 am 11:20 am: Keynote speech (ITE 104) Chair: Dr. Jie Chen, Merck Research Laboratories Platform Trials Michael Krams, MD, Global Head of Quantitative Science, Janssen Pharmaceuticals 11:20 am 12:20 pm: Panel discussion (ITE 104) Chair: Jie Chen, PhD, Merck Research Laboratories Real World Evidence and Regulatory Science Panelists: Aloka Chakravarty, PhD, Acting Director, Office of Biostatistics, US FDA Joseph Heyse, PhD, AVP, Merck Research Laboratories Michael Krams, MD, Global Head of Quantitative Science, Janssen Pharmaceuticals Tze Leung Lai, PhD, Stanford University (subject to future changes, more panelists may join) 12:20 pm 1:40 pm: Lunch Break Catered lunch at the lobby of the ITE building 1:40 pm 2:40 pm: Keynote speech (ITE 104) Chair: Professor DoHwan Park, PhD, UMBC Dr. Yuki Ando s presentation title Yuki Ando, PhD, Senior Scientist for Biostatistics, Pharmaceuticals and Medical Devices Agency (PMDA), Japan. 2:40 4:10 pm Concurrent Session Session 1- Room ITE 102 Multi-Regional Clinical Trials Organizer: Bill Wang, PhD, Merck Research Laboratories Chair: TBD Invited Speakers Bruce Binkowitz, PhD, Shionogi Inc. Title TBD Bill Wang, PhD, Merck Research Laboratories Title TBD Speaker 3, Affiliation Title TBD (subject to future changes) Session 2 Room ITE 104 Hot Topics from FDA Organizer: Jingyu (Julia) Luan, PhD, US FDA Chair: Jingyu (Julia) Luan, PhD, US FDA Invited Speakers 3

5 Laura Lee Johnson, PhD, Director, Division of Biometrics III, Office of Biostatistics, FDA/CDER Rare diseases Thomas Gwise, Ph.D., Deputy Division Director, Division of Biometrics V, Office of Biostatistics, FDA/CDER Current Statistical Topics in Oncology Dionne Price, Ph.D., Division Director, Division of Biometrics IV, Office of Biostatistics, FDA/CDER PDUFA VI pilot program Discussant: Shein-Chung Chow, Ph.D., Associate Director, Office of Biostatistics, FDA/CDER Coffee Break 4:10 4:30 pm 4:30 6:00 pm Concurrent Session Session 3 Room ITE 102 Real World Evidence and Data Synthesis in Drug Safety Assessment Organizers: Elande Baro, PhD, US FDA, and Yi Huang, PhD, UMBC Chair: Elande Baro, PhD, CDER, FDA Invited Speakers Mark Levenson, PhD, Division Director, DB VII, OB, CDER, FDA From Quantitative Drug Safety to Real-World Evidence: Activities at the US FDA Yi Huang, PhD, UMBC Marginal Meta-Analysis for Combining Multiple Randomized Clinical Trials with Rare Events Shaun Bender, PhD, Boehringer-Ingelheim Use of Real World Data for Post-marketing Drug Assessment: Experience from the Industry Perspective Session 4 Room ITE 104 Biopharmaceutical Globalization Organizer: Tony Guo, PhD, BeiGene, and Jie Chen, PhD, Merck Research Laboratories Chair: Tony Guo, BeiGene Panelists Yuki Ando, PhD, PMDA, Japan Amit Bhattacharyya, PhD, ACI Clinical Ning Li, PhD, CStone Pharmaceuticals Weili He, PhD, AbbVie Jeen Liu (or Ray Zhu), PhD, Allergan plc Yi Tsong, PhD, US FDA (subject to future changes, more panelists may join) Lu Tian, PhD, Stanford University Exact Inference on the Random-Effects Model for Meta-Analyses with Few Studies Conference Mixer Lobby of ITE building, 6:00 7:00 pm Closing remark by Dr. Rouben Rostamian, Department Chair, UMBC (5min) Networking for all participants to promote collaborative research (foods and non-alcoholic beverages provided) 4

6 Abstracts (Abstracts are listed in the alphabetic order of speaker s last name and first name. Presenter s names are asterisked in case of multiple authors) Use of real world data for post-marketing assessment: experience from the industry perspective Shaun Bender, PhD, Senior Statistician, Boehringer Ingelheim Pharmaceuticals Inc. Real world evidence (RWE) is playing an increasing role in health care decision making. RWE provides important information that complements evidence from clinical trials and holds the promise to transform patient management and outcomes. Across the pharmaceutical industry, companies are exploring more ways to incorporate RWE into the drug development process from early phase to the post-marketing setting. In this presentation, the speaker will provide an industry perspective on the use of real world data for post-marketing assessment through prospective observational studies in the rare disease setting of Idiopathic Pulmonary Fibrosis. Current Statistical Topics in Oncology Thomas Gwise, Ph.D., US FDA The field of oncology is being pushed forward by stunning innovations, from CAR-T cell therapy to Immuno-Oncology treatments. Coming with the innovations in oncology are new challenges for statisticians. This presentation will be an overview of some of the newer statistical challenges FDA s oncology product reviewers are facing, some of the ways in which the Agency is addressing those challenges, as well as some areas that are open for innovative solutions. Among the discussion points are challenges in interpreting data not following proportional hazards assumptions, real world evidence utility, and Bayesian approaches. Marginal Meta-Analysis for Combining Multiple Randomized Clinical Trials with Rare Events Yi Huang, University of Maryland Baltimore County; Elande Baro, US FDA; Yun-Yu Cheng, University of Maryland Baltimore County; and Guoxing Soon, US FDA Meta analysis (MA) is commonly used in the postmarketing safety studies of FDA regulated medical products, including drugs, medical device, and etc. Avandia Studies (Nissen et al, 2007, 2010) is a powerful example to show how important MA is in real life for quantifying the safety concerns with policy impacts. However, the fact that the re-analysis of same Avandia data could reach different conclusions showed clearly the statistical challenges and difficulties associated with standard fixed effect and random effect MA methods for combining trials with extremely rare events. Specifically, the inclusion and exclusion of zero trials, changing the effect estimand to risk difference, and/or using other fixed effect MA methods rather than Peto, would lead to different conclusions. Lesson learned from Avandia studies enlightened the problems associated with the critical effect at random assumption underlying standard MA approaches, and inspired our discovery of a more relaxed Study at Random assumptions. Particularly for MA with rare events, two more motivations for this study are low power in homogeneity test associated with standard approaches and limited interpretability of popular MA estimands due to their non-collapsibility. Even though they may bias the results, various types of ad-hoc 5

7 continuation corrections were proposed and widely used to improve the performance of standard MA estimators. In this paper, we proposed a marginal meta analysis approach with natural weights which provided a consistent estimate for marginal causal effects combining randomized clinical trials in safety studies under study homogeneity assumption. This estimator is particularly useful when the outcome is rare, and double zero trials are naturally accounted in the estimation without add-doc continuity correction. Systematic simulation studies show that the proposed estimator performs reasonably well under various rationales. This is a joint work with my students, Elande Baro, Yun-Yu Cheng, and colleague from FDA, Guoxing Soon. Platform Trials Michael Krams, Quantitative Sciences, Janssen R&D Platform trials can be viewed as an enabler for a patient centric strategy in clinical development of investigational pharmacological treatments. So what would it take for the concept to be much more broadly applied across pharmaceutical R&D? We will use a study in Alzheimer s Disease to illustrate the journey from ideation to implementation. From Quantitative Drug Safety to Real-World Evidence: Activities at the US FDA Mark Levenson, US FDA In the last decade, the FDA has initiated numerous efforts to continue to improve its evaluations of drug safety both in the premarket and post-market realms. These efforts have entailed making use of novel data sources and novel statistical designs and analyses. Recently there have been increased interests in making additional use of novel data sources to provide evidence of efficacy, an area known as real-world evidence. Under the 21st Century Cures Act, the FDA is required to develop a program to evaluate the use of real world evidence to help support the approval of a new indication for an approved drug or to satisfy post approval study requirements. This talk will review the FDA drug safety and RWE efforts and provide some illustrative examples. Use of Real World Data for Post-Marketing Drug Assessment: Experience from the Industry Perspective Wenbo Tang, Boehringer-Ingelheim Exact Inference on the Random-Effects Model for Meta-Analyses with Few Studies Lu Tian, Stanford University We describe an exact, unconditional, nonrandomized procedure for producing confidence intervals for the grand mean in a normal-normal random effects meta-analysis. The procedure targets meta-analyses based on too few primary studies, <7 say, to allow for the conventional asymptotic estimators or non-parametric resampling-based procedures. Meta-analyses with such few studies are common, with one recent sample of 22,453 heath-related metaanalyses finding a median of 3 primary studies per meta-analysis (Davey et al 2011). Reliable and efficient inference procedures are therefore needed to address this setting. The coverage level of the resulting CI is guaranteed to be above the nominal level, up to Monte Carlo error, provided the meta-analysis contains more than 1 study and the model assumptions are met. After employing several techniques to accelerate computation, the new CI can be easily constructed on a personal computer. Simulations suggest that the proposed CI typically is not overly conservative. We 6

8 illustrate the approach on several contrasting examples of meta-analyses investigating the effect of calcium intake on bone mineral density. 7