Postion / Subject
Nick Holford Associate Professor, Univ of Auckland, New Zealand /
Modeling of Disease: The Time Course of Depression
-- What Happens in Clinical Trials?
Mats Karlsson Professor, Uppsala Univ, Sweden /
Modelling of the glucose-insulin system
Suneel Gupta Vice president, ALZA corporation, USA /
Pharmacokinetic and Pharmacodynamic Guided Product Design
Pascal Girard INSERM - EA 3738 Univ Lyon I, France /
Impact of non compliance on anticancer oral drugs: in silico study using PK-PD models with application to continuous and categorical biomarkers
Jaap Mandema Quantitative Solutions Inc, USA /
Value of model-based meta-analyses for drug development and approval
Paolo Vicini Associate Professor, Univ of Washington, USA /
Promises and challenges: what lies ahead for population modeling?
Terry Blaschke Professor, Stanford Univ, USA /
Antiretroviral Drugs for HIV Infection: What Allowed Surrogate Endpoints to be Used for Approval?
Hui Kimko Johnson & Johnson, USA /
Utility of Monte Carlo Simulation in Anti-infective Agent Development
Carl Peck Professor, UCSF, USA /
Factors Affecting Impacts of PKPD in Drug Development & Regulation
Dongwoo Kang Pfizer, USA /
Application of adaptive design to enhance clinical trial
Howard Lee Adjunct Associate Professor, Univ of Pittsburgh, USA /
Talking Technology to Nontechnoligical Audience
Atsunori Kaibara Astellas Pharmaceutical Corp., Japan /
Modeling and simulation approach for study design of FK506 (tacrolimus) in patients with ulcerative colitis
Yoshitaka Yano Associate Professor, Kyoto Univ, Japan /
Prediction of pharmacokinetic profile in pediatric patients from data in adults for intravenous beta-lactam antibiotics
Yusuke Tanigawara Professor, Keio Univ, Japan /
Importance of PK/PD in Internationally Harmonized Drug Development
Kenichiro Yoshida Taiho Pharmaceutical Corp. Japan
Application of PPK modeling and simulation to clinical development of S-1, a DPD inhibitory fluoropyrimidine
Tomoo Funaki Otsuka Pharmaceutical Corp. Japan /
Population PK/PD analysis of compound X to find appropriate dosage regimen in clinical trial
Takahiko Tanigawa Bayer Yakuhin,Ltd, Japan /
Detection and prediction of drug safety
Takuya Okagaki Tanabe Seiyaku Co., Ltd, Japan /
PK/PD model building and validation
Liping Zhang Bristol-Myers Squibb Co., USA /
Simultaneous versus sequential population PK/PD modeling

Nick Holford


Dr Holford is currently an Associate Professor at the University of Auckland. His research interests include population PKPD analyses of clinical trials of drugs and clinical trial simulation. He is currently developing the use of disease progress models for understanding clinical pharmacology with an emphasis on the effects of levodopa in Parkinson's Disease, drugs affecting post-menopausal bone loss, and the time course of response to anti-depressants.

A brief description of the presentation
It is widely accepted that anti-depressant drugs take some weeks to reach their greatest effect in the relief of depression. Clinical trials of anti-depressants often demonstrate marked responses to placebo treatment. The time course of the placebo response can be quantitated and the patterns of response used to understand the magnitude and time course of anti-depressant drug effects. Patterns of response within the time frame of a clinical trial include a monotonic improvement (decrease) in the Hamilton Depression (HAM-D) rating scale or an initial improvement with subsequent worsening. These patterns of response are partly explained by the design of the clinical trial especially the frequency of HAM-D observation. In the analysis of clinical trial outcome it is commonly assumed that the response to active treatment is additive to the placebo response. Clinical trial data were supplied by three pharmaceutical companies. Data included responses to placebo, marketed anti-depressants and drugs being investigated for anti-depressant effect. Based on the assumption that placebo response and active drug response are additive it is has been possible to describe the time course and magnitude of change in HAM-D attributable to anti-depressant drugs. A dose response relationship has been demonstrated with a rapid onset of action. There is no evidence that anti-depressant drugs take weeks to achieve their peak effect.

Mats Karlsson

Mats Karlsson is professor of Pharmacometrics at Uppsala University, Sweden where he leads a research group of about twenty modellers. He received his PhD in pharmacokinetics from this university in 1989 and has been a research fellow at University of Glasgow and University of California, San Francisco, and a visiting professor at Georgetown University, Washington DC. He has received the Giorgio Segre Prize from EUFEPS and is editor for the Journal of Pharmacokinetics and Pharmacodynamics. His research interests focus on methodological aspects of non-linear mixed effects model building and applied PKPD modelling. He has published over one hundred original research articles in the area of PK and PKPD.

A brief description of the presentation
He will describe of a joint non-linear mixed effects model for glucose and insulin across several tolerance tests. It will discuss also glucose - HbA1c modeling following long-term therapy.

Suneel Gupta


Dr. Gupta is presently Sr. Vice President of Non-clinical and clinical R&D and a member of the Management Board at ALZA Corporation, a Johnson & Johnson company. Dr. Gupta joined ALZA in 1989 and has held several positions since joining ALZA. Previously he also held senior position at Ciba-Geigy (now Norvatis) in manufacturing and scale-up of pharmaceuticals. He received PhD from University of Manchester under Prof Rowland and completed a postdoctoral fellowship from UCSF under Prof. Benet. He is presently responsible for Departments of pre-clinical pharmacology, Toxicology, Pharmacokinetics and Dynamics, Clinical Research, Clinical Operation, Biostatistics and Clinical Development. At present, he is responsible for leading the discovery of products based using drug delivery. He is winner of Alza Founders Award (highest honor in ALZA) in 2001 for his vision in leading research. He is also winner of Johnson and Johnson Medal in 2002 (J&J’s highest scientific honor) for his creative scientific and technologically commercially successful innovations in the field of clinical pharmacology. He has been a lead member of clinical teams working for the approval of several products, such as Duragesic®, Nicoderm®, Effidac®, Covera-HS®, Ditropan-XL and Concerta® and Ionsys®. He has conceived and patented the effect of delivery profile on clinical value including once a day oxybutynin and unique controlled release methylphenidate product. At present his research interests focus on the influence of rate and route of drug delivery to maximize clinical utility and/or effectiveness. He has more than 36 patents and co-authored over 200 publications, chapter and presentations dealing with these subjects. He is a reviewer for many scientific journals, and is a member of AAPS, AACP and ASCPT.

A brief description of the presentation
PK-Pd modeling is generalized utilized to describe the PK and PD data and developing correlations to generate and test various hypotheses. More recently modeling is being used to design the clinical trials and make dosing recommendation. Modeling has also been successful in developing clinically differentiated products using same basic principles. This talk will focus on several examples of successful products.

Pascal Girard

Pascal Girard, PhD, is currently INSERM researcher working at Lyon University in a clinical oncology team. His research interest is population pharmacokinetic-pharmacodynamic (PK-PD) modelling and non compliance to oral treatment. He has successively been working as researcher at Lyon Clinical Pharmacology Unit with Prof. Boissel, then visiting assistant Professor at UCSF with Prof. Lewis Sheiner and as senior scientist at Pharsight Corp, applying PK-PD to various domains as cardiology, endocrinology and now oncology. He is one of the historical founding members of the Population Approach Group in Europe (PAGE).

A brief description of the presentation
Nowadays, more and more oral anticancer chemotherapies are developed either for cytotoxic or new targeted drugs. This relatively new route of administration in oncology means new issues in treatment management and among all deviation of the actual way patients take their treatment with the prescription. After a brief review on recent developments about oral chemotherapies, the presentation will show how population PK-PD modelling & Monte Carlo simulation can be used to quantify the impact of non compliance to oral anticancer prescriptions, on either continuous or categorical biomarkers.

Jaap Mandema

Jaap is currently President and CEO of Quantitative Solutions, a
consultancy firm that provides modeling and simulation solutions to the pharmaceutical industry. Prior to starting Quantitative Solutions, Jaap was Chief Scientific Officer at Extropy Pharmaceuticals from 2004 to 2005. Extropy was a startup pharmaceutical company focused on developing drugs to treat children’s illnesses. Before joining Extropy, Jaap was Senior Vice President and Chief Scientific Officer at Pharsight from 1996 to 2004. Pharsight provides software and consulting services to the Pharmaceutical industry to improve the efficiency of drug development. Previous to joining Pharsight, Jaap was Director of New Products Discovery at ALZA Corporation, responsible for defining new product opportunities for Alza’s delivery technologies. Jaap started his professional career as an Assistant Professor of Pharmaceutical Sciences at the Department of Anesthesia, Stanford University School of Medicine. He received his Ph.D. (cum laude) from the division of pharmacology at the Center for Bio-Pharmaceutical Sciences, University of Leiden and his master’s degree (cum laude) from the school of Pharmacy, University of Utrecht, the Netherlands. Jaap’s research interests afre application of modeling and simulation to optimize treatment strategies, trial designs, and drug development decision-making. He has published extensively and received several awards for his academic contributions, among which in 2000 the Tanabe Young Investigators Award from the American College of Clinical Pharmacology and in 2005 the Leon Goldberg Young Investigator Award from the American Society for Clinical Pharmacology and Therapeutics.

A brief description of the presentation
Value of model-based meta-analyses for drug development and approval
Modeling applications in pharmaceutical development have undergone some significant changes over the past few years. Application has shifted from analysis of independent trial results to integration of large quantities of data from multiple compounds and scaling between multiple endpoints. The purpose of which is two-fold: 1) to better understand the likely clinical safety and efficacy profile of the compound in development by borrowing information from competitors, pre-clinical experiments, and biomarker studies; 2) to better understand the competitive landscape and (clinical) value of the compound early in development. In this presentation several examples will be shown that illustrate the value of model-based approaches to drug development. Because of the value that has been illustrated by these and other examples, drug and disease models are starting to play a crucial role in guiding drug development decisions and regulatory interactions. They can play this role because the models provide an objective summary of the knowledge on the compound in development, disease, patients, and competitors. It is my belief that this model-based approach to drug development improves the efficiency of the development process by fully leveraging available information and by unleashing more efficient trial designs.

Paolo Vicini

Paolo Vicini, Ph.D., is currently an Associate Professor with the Department of Bioengineering at the University of Washington. He received his Laurea degree in Electronics Engineering from the University of Padova, Italy, in 1992, and his doctoral degree in Bioengineering from the Polytechnic of Milan, Italy, in 1996. He directs the Resource Facility for Population Kinetics (RFPK,, a NIH/NIBIB research resource focused on the advancement and dissemination of technology for biomedical data modeling, especially nonlinear mixed effects modeling. His research focuses on open problems in the development of mathematical and statistical models of clinical and other biological data. In particular, he has worked on optimal design of experiments, parameter estimation techniques, issues of model selection and various practical applications of mathematical modeling and simulation. He received the IEEE/EMBS Early Career Award in 2003.

A brief description of the presentation
It will describe some of the opportunities and challenges awaiting pharmacostatistical model development, or population analysis, in the coming years. Promises lie in the increased amount of interest and confidence awarded to this relatively new technology in various areas of science and biomedical research, where it is widely regarded as a very useful tool and sometimes the only feasible avenue to extract information from data that would be otherwise impossible to gauge. Challenges lie in the sophistication of the technology, the difficulty of making drastic methodological advances and the relative scarcity of trained professionals, but especially of opportunities for training. Strategies and possibilities to increase the potential of population modeling and simulation in drug development and academic research alike will be discussed.

Terry Blaschke

Terrence F. Blaschke, MD, is Professor of Medicine and of Molecular Pharmacology (Active Emeritus) at Stanford University School of Medicine, Adjunct Professor of Biopharmaceutical Sciences at UCSF and Adjunct Professor of Medicine at Indiana University
Dr. Blaschke received his medical degree from Columbia University College of Physicians and Surgeons, and after residency training in Internal Medicine at UCLA Center for Health Sciences, he was a Clinical Associate in the NCI/Metabolism Branch at the National Institutes of Health. Following fellowship training in Clinical Pharmacology at the University of California, San Francisco, Dr. Blaschke joined the faculty at the Stanford University School of Medicine in 1974.
Dr. Blaschke’s research has been primarily in the area of clinical investigation, with considerable involvement related to the clinical pharmacology of drugs used in patients with HIV infection, and an emphasis on modeling exposure-response relationships. He was a member of the AIDS Clinical Trials Group at its inception, and has served as chair of the Pharmacology Committee and a member of the Executive Committee of the ACTG. His current efforts in HIV are directed at questions related to the use of antiretroviral agents in less developed countries. His interest in exposure-response has led to a related interest in the topic of patient adherence with prescribed treatment regimens in HIV-infected patients. His involvement in clinical trials and with the pharmaceutical industry has also lead to a strong interest in approaches to improve the drug development process.
Dr. Blaschke is a past president of the American Society for Clinical Pharmacology and Therapeutics. In 2002 he received the Rawls-Palmer award from ASCPT for significant contributions to drug investigation that bring the efforts of modern drug research to the care of patients and in 2006 received the Henry W. Elliott distinguished service award of the Society. He has been a consultant and past Chair of the Generic Drugs Advisory Committee of the US FDA and is currently a member of the Nonprescription Drugs Advisory Committee. He chaired the Drug Utilization Review Panel of USP from 1995-2000.

A brief description of the presentation
The history of antiretroviral drug development will be reviewed and the value of various data sources and disease models in establishing HIV RNA copy number and CD4 cell counts as surrogate markers will be illustrated.

Hui Kimko


Dr. Hui Kimko works at Johnson & Johnson Pharmaceutical Research & Development in New Jersey from 2002 by joining Advanced Pharmacokinetic/Pharmacodynamic Modeling and Simulation Department. She teaches at School of Pharmacy of Rutgers University as an adjunct professor and mentors a PhD student of Department of Industrial & Systems Engineering. Before joining the company, she was an assistant professor at the Center for Drug Development Science of Georgetown University Medical School in Washington, D.C.
She got her PhD in Pharmaceutical Science from the State University of New York at Buffalo on Pharmacokinetic and Pharmacodynamic Modeling of Direct and Indirect Responses. She holds a B.S. degree in Pharmacy from Seoul National University and an M.S. degree in Biochemistry from University of California, Riverside. She edited the book titled Simulation for Designing Clinical Trials: A Pharmacokinetic/Pharmacodynamic Modeling Perspective (published by Marcel Dekker, Inc. 2003). The book explains how to optimize clinical trial design via pharmacokinetic-pharmacodynamic modeling and clinical trial simulation in order to enhance study success rate and, in return, help reduce the skyrocketing cost of conducting trials with human subjects. Optimization of clinical trial designs is her current interest.

A brief description of the presentation
The decision processes of designing clinical trials have followed a largely ad hoc manner, driven by empiricism and embracing concepts such as ‘what was done previously’ and ‘it has always been done this way’. In contrast, other disciplines have been effectively designing experiments using statistical techniques to aid design for many years but it is only recently that these methods have filtered into the clinical pharmacological arena. Simulation has become a powerful tool for the practitioner due to its generality of application to a wide array of potential problems. In addition, simulation gains credibility with the non-scientist since it can be explained in essentially non-scientific terms, which allows its transparency to be grasped with ease. It is not surprising, therefore, that clinical trial simulation (CTS) has been used in designing clinical trials in drug development (1-2).
CTS is to generate responses of virtual subjects by approximating (a) trial design, and (b) human behavior, (c) disease progress and (d) drug behavior using mathematical models and numerical methods. The trial design that is needed for CTS includes to-be-decided dosage regimen, subject selection criteria, study period and study size. Human behavior includes trial execution characteristics such as adherence in drug administration (pertaining to enrolled patients) and missing records (pertaining to the investigators). Disease status may change during a trial, for which a disease progress model may need to be developed. The drug behavior in the body is generally characterized by pharmacokinetic (PK) and pharmacodynamic (PD) models. These models are developed from prior experience and/or prior data.
Understanding the relationship between antibiotic concentration and the antimicrobial effect is necessary for eradicating the pathogen. The Monte-Carlo approach represents the state of the art methodology in anti-infective research for dose-selection of new drug entities. These methods take the exposure-response relationship into consideration and allow examination of what if scenarios such as the effect of administering a dose not studied during development. Monte Carlo computations are fairly rigorous and explicitly account for sources of variability that can impact the possibility of successful treatment with a new drug entity. The sources of variability include a) inter-subject PK variability; b) non-linear bioavailability due to various solubility rate limited absorption; c) formulation and food effect on relative bioavailability; d) within-species pathogen sensitivity to the drug, e) between-species pathogen sensitivity to the drug; and f) natural occurrence frequency of pathogens in a clinical setting. By taking into account sources of biological variability and by recognizing the pharmacological interaction between the pathogen, host and drug, an educated decision can be made regarding a dosing regimen that is most probable of succeeding in a future clinical trial.

(1) N.G.H. Holford, H.C. Kimko, J.P.R. Montelone & C.C. Peck: Simulation of Clinical Trials. Annu. Rev. Pharmacol. Toxicol. 49:67-95, 2000
(2) H.C. Kimko & S.B. Duffull, eds: Simulation for Designing Clinical Trials - A Pharmacokinetic-Pharmacodynamic Modeling Perspective. Marcel Dekker, 2003
(3) G.L. Drusano, S.L. Preston, C. Hardalo, R. Hare, C. Banfield, D. Andes, O. Vesga, W.A. Craig. Use of preclinical data for selection of a phase II/III dose for evernimicin and identification of a preclinical MIC breakpoint. Antimicrob. Agents Chemother. 2001; 45:13-22.

Carl Peck

Dr. Peck obtained a B.A. in mathematics and chemistry from the University of Kansas in 1963 and the M.D. in 1968. Following training in internal medicine, he undertook a research fellowship in clinical pharmacology at the University of California San Francisco (1972-74). From 1974 to 1980, Dr. Peck was employed at the Letterman Army Institute of Research, San Francisco, CA, as Chief of the Army Blood Preservation Research Program. In 1980, Dr. Peck became Director of the Division of Clinical Pharmacology and, Professor, Departments of Medicine and Pharmacology, Uniformed Services University, Bethesda, Maryland. Dr. Peck joined the FDA as Director, Center for Drug Evaluation and Research, in October 1987. He was promoted to Assistant Surgeon General in the Public Health Service in October 1990. Retiring from FDA in late 1993, Dr. Peck was appointed “Boerhaave” Professor of Clinical Drug Research at Leiden University in The Netherlands. In 1994 Professor Peck joined the faculty of the Georgetown University Medical Center, as the founding Director of the Center for Drug Development Science. In 1999, Dr. Peck received the FDA Distinguished Alumnus Award. Sweden’s University of Uppsala conferred an honorary doctorate degree (Doctor Honoris Causa) to Dr. Peck in January 2002 in recognition of "outstanding contributions to the science of drug development". Dr. Peck founded NDA Partners LLC in 2003 and in 2004, CDDS moved to UCSF, located in the UC-Washington Center. His research interests center on optimizing drug development and regulation. He is an author of more than 100 original research papers, chapters and books. Dr. Peck serves on numerous scientific advisory boards to industry and government institutions, and is a member of several boards of directors.

A brief description of the presentation

Integration of PKPD modeling and simulation (M&S) in new drug development programs may afford one or more of the following advantages over traditional empirical development approaches: (1) enhanced learning about relationships among drug dosage, metabolism, and tissue concentrations to biomarkers and clinical measures of safety and effectiveness, (2) testing of assumptions critical to safety, effectiveness and market acceptance, with respect to drug actions, dosage regimens, routes of administration, etc, (3) informative trial design and optimization of trial design features, (4) enhanced data analysis for learning and confirming from all trials, and (5) enlightened regulatory guidance, review and approval of M&S-intensive regulatory submissions.

Despite the above listed advantages, utilization of rapidly advancing PKPD M&S technology by the pharmaceutical and biotech industries and regulatory agencies has been slow and incomplete. This presentation will identify barriers to greater integration of PKPD M&S in drug development and regulation, factors that may enhance acceptance, and avenues for further advancement of advantageous incorporation in future new drug development programs and regulatory procedures.

Dongwoo Kang

* BS in Eletrical Engineering, Seoul National University, Seoul, South Korea,1989
* Biomedical Engineering Lab., Seoul National University Hospital, Seoul, South Korea,1995
* MS in Biomedical Engineering, University of Southern California, Los Angeles, CA, 1998
* PhD in Biomedical Engineering, University of Southern California, Los Angeles, CA, 2000
* Postdoc Training in Biopharmaceutical Sciences, University of California San Francisco, San Francisco, CA, 2003
* Scientist at ALZA Corp., A Johnson & Johnson Company, Mountain View, CA, 2006
* Scientist at Pfizer Global Research & Development, San Diego, CA, Present

A brief description of the presentation

An adaptive design allows an investigator to monitor the acruing efficacy data to make important decisions (such as sample size, dose levels, etc) concerning the future course of the study. Thus, the investigator can have the options to make adaptive changes to the initial design with verification of design assumptions (variance, effect size, covariate effects, etc.) and to either terminate for futility, change dose levels, drop ineffective arms, or divert key resources to more promising studies. By taking advantage of these opportunities, the investigator can reduce the clinical study cost or achieve the study objective more efficiently. An adaptive design is employed in a phase II study to make a go/no-go decision as well as to characterize the dose reponse. A simulation study is used to demonstrate the utility and advantage of the proposed adaptive design study.

Howard Lee

Howard Lee, MD, PhD, is an Adjunct Associate Professor of Biopharmaceutical Sciences, School of Pharmacy, UCSF. Dr. Lee also serves as the Director for the Center for Drug Development Science, UC Washington Center. Prior to that, Dr. Lee was
a Research Assistant Professor (2005-2006), Center for Clinical Pharmacology, Department of Medicine, University of Pittsburgh School of Medicine, and served as the Associate Director for the Clinical Investigation Core. Dr. Lee was an Assistant Professor (2002-2004), Georgetown University Medical Center, and Assistant Clinical Professor and Associate Director (2004), Center for Drug Development Science, University of California San Francisco, affiliated with School of Pharmacy.
Dr. Lee is a graduate of the Seoul National University College of Medicine, Seoul, Korea, where he received the MD (1988), MSc (1991, Epidemiology), and PhD (1997, Preventive Medicine and Epidemiology) degrees. He has a diploma in Advanced Management Program for Health Industry (1997, Sejong University, Graduate School of Public Administration, Seoul, Korea). Dr. Lee also completed internship and residency training in the Seoul National University Hospital (1988 - 1991), and is board certified in Family Medicine. Dr. Lee also undertook a postdoctoral fellowship in clinical pharmacology, pharmacometrics, and drug development science at the Center for Drug Development Science, Department of Pharmacology, Georgetown University Medical Center under the supervision of Prof. Carl C. Peck (2000-2001). During his fellowship, Dr. Lee worked as a Guest Medical Reviewer for 4 months at the Division of Cardio-Renal Products, Center for Drug Evaluation and Research, US Food and Drug Administration.
Dr. Lee was the co-PI for clinical pharmacology of the Washington Obstetric Pharmacology Research Unit Network grant (NIH HD-03-017) affiliated with Georgetown University Medical Center, and has also served as the co-I of the Collaborative Pediatric Pharmacology Research Unit Network grant (NIH HD-03-001). Dr. Lee is the PI of the Merck Foundation Grant, entitled “A Systematic Policy Analysis to Identify Key Strategies for Implementing Good Review Practices into the Korea Food and Drug Administration”.
Dr. Lee’s current research interests include:
1. Drug dosage changes since regulatory approval: This is to determine the hazard of dosage change after approval for drugs approved 2000-2005 and compare it to the one of previously approved drugs (i.e., 1980-1999)
2. Key factors for successful regulatory approval: This is to assess the impact of good clinical pharmacology practices on the likelihood of drug approval
3. Disease progression modeling: This is to develop a disease progression model for rheumatoid arthritis clinical endpoints
4. PK-PD model for the safety endpoints: This is to explore the methodological framework for a PK-PD model of the safety endpoint

A brief description of the presentation
The target audiences for the results of a pharmacokinetic-pharmacodynamic model are often lacking background knowledge and experience in quantitative sciences. Therefore, it is important for modelers to develop strategic communication skills, and this becomes more crucial when talking to the regulatory reviewers. In this presentation, an overview of the issues of technological communication in the context of the nontechnolgical audience will be made. Some points to consider will be also addressed.

Atsunori Kaibara

Dr. Atsunori Kaibara is Senior Manager of Clinical Pharmacology, Astellas Pharma Inc., Japan. He received B.S., M.S. and Ph.D. degree in pharmaceutical sciences from Kyoto University. He had experienced preformulation, drug metabolism, and clinical/non-clinical PK/PD analysis in his earlier career at Fujisawa Pharmaceutical Company after joining in 1990. In 1995-6, he worked with Professor Lewis Sheiner at UCSF as a postdoctoral fellow. In the recent 10 years, he has been responsible for clinical pharmacology of global projects. Since 2003, he has also joined the Clinical Evaluation Department, Drug Evaluation Committee of Japanese Pharmaceutical Manufacture Association (JPMA).

A brief description of the presentation
Immunosuppressive therapy with FK506 (tacrolimus) is now under developing for an alternative treatment option to total colectomy for patients with ulcerative colitis (UC) in Japan. PK/PD analysis has justified drug concentration oriented dosage of FK506. Modeling & simulation utilized to establish appropriate control method of dosage for achieving desirable concentration profile will be discussed.

Yoshitaka Yano

* Current Position:
Associate Professor, Graduate School of Pharmaceutical Sciences, Kyoto University, Japan. (May, 2006 - )
* Professional Experiences:
Research Scientist in Shionogi Research Laboratories, Shionogi & Co., Ltd., Japan. (April, 1990 - April, 2006);
Postdoctoral fellow at University of California, San Francisco (UCSF; Prof. L.B. Sheiner and S. L. Beal). (April, 1998 - March, 1999)
* Education:
Ph.D. Pharmaceutical Sciences, Kyoto University. (1990);
B.S. Pharmaceutical Sciences, Kyoto University. (1985)

A brief description of the presentation
A prediction method of pharmacokinetic profile in a pediatric patient based on an empirical Bayesian method for intravenous beta-lactam antibiotics will be presented. Based on retrospectively collected data, a mixed effect modeling was applied to the allometric relationship of the pharmacokinetic parameters and individual body weights and also inter-drug and intra-drug variability of the allometric parameters were estimated. Using these estimates as prior information, an empirical Bayesian method was applied to predict drug specific allometric parameters, and then individual pharmacokinetic parameters in a pediatric patient were predicted. The method was evaluated by a leave-one-out method. A procedure to draw a predicted drug concentration curve in a patient will be also discussed.

Yusuke Tanigawara

Prof. Yusuke Tanigawara is currently a Professor and Director of the Department of Pharmacy, University Hospital, School of Medicine, Keio University. His responsibilities are multidisciplinary; management of the pharmacy in University Hospital with 1072 beds, teaching and research.
He received his Ph. D. in pharmacy from Kyoto University in 1983. His research interests include pharmacokinetics, pharmacodynamics and pharmacogenomics. He has been studying the population-based analysis of clinical pharmacokinetics and pharmacodynamics for a variety of drugs such as anticancer agents, antimicrobial agents, cardiovascular agents, analgesics and anticonvulsants, and its application to new drug development as well as rational use for patient care. He also investigates pharmacogenomics and proteomics research for the clinical impact of genetic polymorphisms and gene expression on the individual variability of efficacy and safety of drugs.
He is distinguished as one of the ISI highly cited scientists in the world. He is currently the President of the Population Approach Group in Japan, and also President of the Japanese Association for Therapeutic Drug Monitoring. Prof. Tanigawara is a central person in the PK/PD community in Japan.
He serves as a member of Advisory Board Committee for approval of new drugs of the Ministry of Health, Labor and Welfare, Japan. He also completed leadership as Rapporteur to develop the ICH E2E Guideline
“Pharmacovigilance Planning.”

A brief description of the presentation
ICH E5 guideline and the bridging concept Roles of PK/PD and Population PK Typical successful examples Keys to success ICH E2E : Pharmacovigilance New strategy : E5 + E2E combination

Kenichiro Yoshida

Pharmacokinetics Research Laboratory, Taiho Pharmaceutical Co., Ltd., Japan
1987 M.D., in Hiroshima University, Japan
1995 Ph.D., in Osaka Prefecture University, Japan
1987~present Research scientist, in Taiho Pharmaceutical Co., Ltd., Japan

Specialized fields
* General pharmacokinetics
* Clinical pharmacokinetic analysis
* Structural chemistry of organic compounds

* Pharmaceutical Society of Japan
* The Japanese Society for the study of Xenobiotics
* The Japanese Society of Therapeutic Drug Monitoring
* Japan Society for Bioscience, Biotechnology, and Agrochemistry
* The Japanese Society of Carbohydrate Research

A brief description of the presentation

S-1 is a new oral pyrimidine fluoride-derived anticancer agent in which Tegafur (FT) was combined with two modulators, Gimeracil (CDHP, a DPD inhibitor) and Oteracil potassium (Oxo, a OPRT inhibitor). Its pharmacokinetic modeling and simulation as well as its application to clinical development will be discussed.

Tomoo Funaki

I used to be an assistant professor at the School of Pharmaceutical Sciences, Showa University, after graduation of Showa University in 1976. In 1986, I received a Ph.D. degree in pharmacy. From 1987 to 1988, I was in the Netherlands to be a guest researcher at the Center for Bio-Pharmaceutical Sciences, Leiden University under the direction of Prof. D.D. Breimer. Nearly 16 years back, I moved to Nippon Roche Research Center/Kamakura, Nippon Roche Clinical Development/ Tokyo, Roche Biometrics/Basel. I have long been working towards R&D of several scientifically interesting and clinically promising candidates. I’m now working at Otsuka Pharmaceutical Co., Ltd.

A brief description of the presentation
The population PK-PD model for compound X in patients was developed that can be used for simulating the effect of different dose regimens on urine osmolarity to support dose selection for upcoming phase III studies for this target group.

Takahiko Tanigawa

Takahiko Tanigawa, Ph.D. is currently Manager of Clinical Pharmacokinetics of Bayer Yakuhin,Ltd. He had experienced bioanalytical and PK/PD analysis in the field of clinical pharmacology. His thesis is titled “The study of application Population Pharmcopkinetic/Pharmacodynamic approach in drug development -useful for ethnicity evaluation and safety evaluation-“. He is a member of the Clinical Evaluation Department, Drug Evaluation Committee of Japanese Pharmaceutical Manufacture Association (JPMA). since 2003.

A brief description of the presentation
My talk is the evaluation of the relationship between plasma concentration of moxifloxacin and QT/QTc interval based on the result of Japanese volunteers studies by Modeling & Simulation approach.

Takuya Okagaki
April 2004 to present
Statistician, Statistical Analysis Section, Clinical Research Division,
Tanabe Seiyaku Co., Ltd.
April 2003 to March 2004
Researcher, Clinical Pharmacokinetics Group, Analysis Development Laboratories,
Tanabe Seiyaku Co., Ltd.
April 1999 to March 2003
Researcher, Drug Metabolism & Pharmacokinetics Division,
Drug Discovery Research Laboratories, Tanabe Seiyaku Co., Ltd.
April 1987 to March 1999
Researcher, Pharmaceutics Research Laboratory,
Tanabe Seiyaku Co., Ltd.

April 2006 to present
Faculty of Engineering, Tokyo University of Science
Master of Pharmacy, March 1987, Kyoto Pharmaceutical University
Bachelor of Pharmacy, March 1985, Kyoto Pharmaceutical University

A brief description of the presentation
A paradoxical result would be obtained occasionally from population PK/PD analyses. It should be considered that probabilistic nature of variables might play various tricks as a cause of the paradox. We will outline our view for effects of random variables on the PK/PD modeling and validation.

Liping Zhang
Liping Zhang, PhD, is currently a senior research investigator in the Strategic Modeling and Simulation Group at Bristol-Myers Squibb Co. Prior to that, she was a research scientist at Eli Lilly and Company from 2003 to 2006. She received her PhD in Biological and Medical Informatics from University of California San Francisco in 2003 under the guidance of Dr. Lewis Sheiner. Her research interest is to apply advanced modeling and simulation techniques to drug development for the treatment of obesity and diabetes

A brief description of the presentation
Two analytic strategies can be taken to the analysis of multi-response data: a multivariate output model can be fit to all the response components simultaneously, or each response component can be fit separately to a univariate output model, conditioning in some way on the non-modeled components, the so-called forcing function approach. Focusing on a special case of multi-response model corresponding to a pharmacokinetic physiological flow model, this presentation will propose an algorithm for applying forcing function approach to multi-response data from a physiological flow model, examine the performance of forcing function approach vs. simultaneous approach, and make recommendations regarding the use of forcing function for multi-response data analysis.


Secretariat of PKPD Yonsei 2006: c/o Ms. Ji Hye Lee, Clinical Trials Center, Yonsei University Medical Center
134 Shinchon-Dong, Seoul 120-752, Korea, Tel: +82-2-2228-0479 / Fax: +82-2-392-0668, E-mail: