PMDA s perspective on regulatory science in pharmaceutical regulation

Transcription

1 PMDA s perspective on regulatory science in pharmaceutical regulation Dr Yoshiaki Uyama Director, Office of Medical Informatics and Epidemiology Pharmaceuticals and Medical Devices Agency (PMDA) Visiting Professor, Graduate School of Medicine, Chiba University Visiting Professor, Graduate School of Medicine, Nagoya University 1

2 Circumstances surrounding drug regulation 2

3 Huge increase of costs to get a Drug ($ MM) PhRMA R&D JPMA R&D Number of Drugs approved by FDA Clinical Non-Clinical Costs/drug 3 DiMasi JA et al, J Health Econ. 2003, 22: Paul SM et al, Nat Rev Drug Discov. 2010, 9:

4 Improving but still unmet medical needs Diabetes Contribution of drug to medical therapy Fibromyalgia Schizophrenia Depression High unmet medical needs Breast Cancer Asthma Myocardial infarction 4 Pancreatic cancer Satisfaction of medical therapy Alzheimer s

5 International competitiveness in review for approval New active substance median approval time for six regulatory authorities in Published by The Center for Innovation in Regulatory Science 2016 EMA FDA PMDA More pressures to shorten the review period, but such competitiveness among regulatory agencies would not be constructive for public health 5

6 Rapid Evolution of Science 6

7 The Novel Prize in Physiology or Medicine 7

8 Scientific Innovation Example: ips cell-derived products ips cell-derived retinal pigment epithelial cell sheets 8

9 What is Regulatory Science? 9

10 GAP between expectation and Reality Concerns and Needs for medical services Traditional Science Current Issues SAE after approval, Lower success rate, Scientific uncertainty etc. New study design and analytical tool Predictable model for efficacy/safety Medical Needs Advancing Regulatory Science Ensure Social Balance New approach on risk communication and management New tool/methods for benefit/risk assessment Regulatory Science Traditional Science

11 Regulatory Science Bridge PMDA s definition of Regulatory Science the science aimed at the optimal introduction into society of new products of science, such as discovered substances and new scientific tools and technologies as well as knowledge and information. 11 Tominaga T et al, Clin Pharmacol Ther, 90: 29-31, 2011

12 Regulatory Science Bridge Data assessment Products of science (Substance, Knowledge, Information) Patients/ Society Tominaga T et al, Clin Pharmacol Ther, 90: 29-31,

13 Microscopic feature of Regulatory Science Data assessment based on clinical trials to conclude benefit/risk of a drug For example Evaluating efficacy on the primary endpoint Evaluating safety based on dose-response relationship Microscopic observation 13

14 Real-world feature of Regulatory Science Cohort Study Case Report Case Report Rumors News item Article Placebocontrolled RCT Article News item Cohort study Expert Opinion Expert Opinion Active-controlled RCT Value to the Society in promoting the Health Scientific, Non-bias, Objective, Regulatory Science Truth Evaluation based on Regulatory Science 14

15 Ethics Multi-disciplinary team of regulatory science and More Practical Drug Use Sociology Biostatistics Jurisprudence Veterinary Medicine Regulatory Science Tree Agricultural Science Pharmaceutical Science Seeds for a drug Business Administration Medical Science Education Experts in various fields need to collaborate for better decision Economics Technological Science 15

16 PMDA efforts for promoting innovative drug development and advancing regulatory science 16

17 Message from Dr Kondo, Chief Executive (PMDA) Nature Reviews Drug Discovery 13, 490 (2014) 1.More scientific contributions during development through consultation 2.Utilizing BIG DATA for improving quality of approval review and safety assessment 3.Promoting regulatory science Developing methods and criteria for responding to advances in science and more 17

18 Special consultations on Pharmaceutical Regulatory Affairs Promoting innovative drug development by academic institute and venture enterprises in Japan Focusing on early stage of drug development including quality and non-clinical as well as clinical matters Discovery (Identifying a candidate product) Manufacturing / quality assessment Non-clinical (Pharmacology/ ADME/Toxicology etc.) Clinical Review Post-Market Special consultation on Pharmaceutical Affairs NDA Approval 18

19 Scientific Consultations in PMDA Non-Clinical PhaseⅠ Clinical Review Post-Market IND PhaseⅡ NDA PhaseⅢ PhaseⅣ Pre P-I Pharmaceutical Affairs Consultation Pre P-II End of P-II Pre NDA Prior-Assessment Consultation Pre-post marketing End of Reevaluation period Special Consultation on PGx/Biomarker Qualification 19 Modified from Figure by Ichimaru K et al, Clin Pharmacol Therapeut, 88: , 2010

20 SAKIGAKE Strategy MHLW launched a new system termed Strategy of SAKIGAKE as a Package to lead the world in the practical application of innovative medical products in

21 Original Review General Framework of SAKIGAKE" Consultation 2 months 12 months Non-clinical research/ Clinical research Clinical trial Phase I/II Consultation on clinical trial Clinical trial Phase III Review Covered by insurance Commercialization in market <1> Priority Consultation <2> Prior Review <3> Priority Review Review under SAKIGAKE Designation System 6 months 21 Consultation Non-clinical research/ Clinical research Designation as SAKIGAKE Clinical trial Phase I/II Prior Review Consultation on clinical trial 1 months Clinical trial Phase III Review *Accept the data of Phase III after the application depending on conditions Covered by insurance Commercialization in market Early Access to the innovative medical products <4> Review Partner <5>Extending re-evaluation period (post-market exclusivity)

22 SAKIGAKE Designated Products Drugs, as of Oct Name of drug Proposed indication Name of applicant Sirolimus (NPC-12G) NS-065/NCNP-01 Angiofibroma associated with tuberous sclerosis Duchenne muscular dystrophy (DMD) Nobelpharma Co., Ltd. Nippon Shinyaku Co., Ltd S Influenza A or B virus infection Shionogi & Co., Ltd. BCX7353 ASP2215 Management of angioedema attacks in patients with hereditary angioedema (HAE) First-relapsed or treatment-resistant FLT3 mutation-positive acute myeloid leukaemia Integrated Development Associates Co., Ltd. Astellas Pharma Inc. Pembrolizumab (genetical recombination) Unresectable, advanced and recurrent gastric cancer MSD K.K. 22

23 SAKIGAKE Designated Products Medical devices and Regenerative Medical Products, as of Feb Name of medical products Proposed indication Name of applicant Titanium Bridge (Hinge-type plate with titanium) Bioresorbable adhesion barrier (THN-01: Trehalose solution) Adduction-type spasmodic dysphonia Postoperative adhesion prevention Nobelpharma Co., Ltd. Otsuka Pharmaceutical Factory, Inc. STR01 Nerve syndrome and (Autologous bone marrow-derived dysfunction caused by spinal mesenchymal stem cell) cord injury NIPRO Medical Co., Ltd. G47 (Growth-controlled oncolytic herpes simplex virus type 1) Autologous cardiac progenitor/stem cells Malignant glioma Pediatric congenital heart disease (single ventricle physiology) Daiichi Sankyo Co., Ltd. The University of Tokyo, Institute of Medical Sciences Japan Regenerative Medicine Co., Ltd. 23

24 BIG DATA utilization for better assessment and promoting public health 24

25 CDISC data submission on NDA formally started on October 1 st, 2016 NDA etc. CDISC data Database of Clinical Trial Results Analysis Modeling & Simulation: Concentration-Response Model, PBPK: Physiologically-based Pharmacokinetic Model etc. NDA Review B/R evaluation with raw data analysis Scientific Consultation Scientific advices based on the information obtained from analyses including M&S Cross-Products Analysis More effective & High quality review More efficient & Successful development More evidences & Advancing Regulatory Science Establish disease models Identifying common risk factors among different drugs etc. 25

26 MIHARI PROJECT (PEpi Assessment based on EHR) PMDA MHLW Hospital/ Medical institutes Conventional information sources Electronic Healthcare Data utilization Literatures Spontaneous ADR report DB Overseas regulatory actions Claims DB MID-NET (EMR DB) Safety measure Risk Management/communication Presentations in Academic Meetings etc. DPC DB a new database of medical information of Japanese patients 26

27 MID-NET Project The Medical Information Database Network in Japan for a real-time assessment of drug safety (currently 4M patients) PMDA Hospital Database HIS data Claims data DPC data Hospital DB Hospital Hospital DB 23 hospitals In closed network Hospital DB DB 27

28 Example: MID-NET Data Utilization -Prazaxa-induced GI bleeding- Compare risk of GI bleeding between Prazaxa and Warfarin Number of Prescription Results from 1 cooperative hospital of MID-NET Number of Patients GI Bleeding Patient number Prazaxa % warfarin 14,534 1, % % (%) 5,0 4,0 3,0 2,0 1,0 0,0 prazaxa warfarin Patients distribution based on Cr at the time of first prescription Results from 1 cooperative hospital of MID-NET Number of patients Normal -0.9mg/dL Mild mg/dL Moderate mg/dL Severe 2.7-mg/dL No Lab-test n % n % n % n % n % prazaxa % % 7 4.3% 0 0.0% % warfarin 1, % % % % % 28

29 PMDA Regulatory Science Center (planned in 2018) CDISC Data EMR Data Regulatory Science Center Archives of e-data Active Utilization BIG DATA -utilized Assessment & Regulation Utilization of e-data for better regulatory decision in Development Pre-Approval Pharmacovigilance Better B/R balance 29

30 Advancing Regulatory Science & PMDA RS Center Start routine PEpi analysis for safety assessment Pilot studies in using CDISC data Start e-data (CDISC) submission for NDA (Oct 2016) More PEpi studies including MID-NET pilot studies Reinforcement of collaboration among PMDA Offices (New Drug Review, Safety, M&S Group, PEpi Group) FY2016-FY2017 Start cross-product analysis (M&S) Launch MID-NET for PEpi analysis Launch PEpi consultation Launch PMDA Regulatory Science Center FY2018-FY2019 Full scale cross-product analysis Full scale PEpi analysis Publish more guidelines Strengthening international collaboration on utilization of BIG-DATA FY2020-FY2021 Collaboration with academia/industries on BIG-DATA analysis Routine regulatory measure based on BIG DATA analysis FY2022-FY2023 FY2014-FY

31 Data assessment Data assessment Innovative Drug A Products of science (Substance, Knowledge, Information) Patients/ Society Stronger & More Complete Regulatory Science Bridge will help us in the future drug developments 31 Tominaga T et al, Clin Pharmacol Ther, 90: 29-31, 2011

32 Information PMDA web site Thank you for your kind attention