Short Course: Quantitative-System-Pharmacology: Why, How and When in Drug

Discovery and Development

Quantitative system pharmacology (QSP) integrates the drug related information (physico-chemical

properties, exposures, pharmacokinetics, etc.) to the biology and pharmacology (disease, target,

biomarkers, etc.) and attempts to understand the system as a whole. Although complex, such an

approach provides immense opportunities in terms of drug discovery, lead identification, optimization,

and development in the clinic.

This short course will offer a holistic approach to understanding the vital role of QSP by taking a step-

wise approach to its application throughout the drug development process. Through the use of real-

world case studies and examples, this course provides a unique opportunity for attendees to better

understand the rapidly growing field of QSP as well as appreciate how it can be applied immediately to

their work.

Learning Objectives:

• Understand QSP as it relates to the minimum information required to build QSP model.

• Gain insight on QSP’s value and utility to various steps of drug discovery and development.

• Attempt to construct and apply QSP in their own scenario to address critical questions.

Presentations All presentations will be available on the workshop website, no later than 24 hours following the

workshop. Presentations will remain online for registered attendees until August 7, 2019.

AAPS Disclaimer Statement All scientific presentations at AAPS-sponsored events must adhere to the highest standards of scientific

ethics, including acknowledgements or references to sources (both scientific and financial), and the

absence of promotional content or endorsement of commercial products. Any conflict of interest must

be disclosed prior to the meeting. Authors and speakers are responsible for the content and ideas stated

in their oral and written presentations. AAPS is not responsible for, nor do we endorse, the material

published in any final program materials or any oral or written statements made by presenters at this

meeting.

Workshop Planning Committee Nidhi Sharda, Ph.D., Bristol Myers Squibb Anjaneya Chimalakonda, Ph.D., Bristol Myers Squibb

Thank You AAPS Sustaining Sponsors for Your Support

Join AAPS at These Future Meetings

Workshop Agenda Sessions will take place in the Washington Convention Center, room 146 B

Sunday, November 4, 2018

9:00 am – 9:10 am Brief Introduction on Session, Learning Objective and Speaker's Panel

Nidhi Sharda, Bristol-Myers Squibb

9:10 am – 9:45 am General Scope in Drug Discovery and Development

Tarek Leil, Bristol-Myers Squibb

9:45 am – 10:15 am QSP in Drug Discovery: Target Identification and Lead Candidate

Selection/Optimization

Joshua Apgar, Applied Biomath

10:15 am – 10:45 am Current Landscape of QSP in Pharmaceutical Industry

Maria Nijsen, Abbvie

10:45 am – 11:00 am Coffee Break

11:00 am – 11:40 am QSP in Early Clinical Development and Translational Research (case

studies where QSP was used for FIH dose selection and translating PK-

PD-efficacy from nonclinical species to human)

Mary Spilker, Pfizer

11:40 am – 12:15 pm QSP in Full Clinical Development: Application in design of Phase II and

Phase III studies

Konstantinos (Kostas) Biliouris, Novartis

12:15 pm – 12:50 pm Regulatory Perspective on Application of QSP in Drug Development

Yaning Wang, U.S. Food and Drug Administration

12:50 pm – 1:00 pm Concluding Remarks

Nidhi Sharda, Bristol-Myers Squibb

1:00 pm – 2:00 pm Lunch Break

Speaker Biographies and Abstracts

General Scope in Drug Discovery and Development Quantitative Systems Pharmacology (QSP) uses mathematical computer models to characterize

biological systems, disease processes and drug pharmacology. QSP can be used to generate

biological/pharmacological hypotheses in-silico to aid in the design of in-vitro or in-vivo non-clinical and

clinical experiments. This presentation will provide an introduction to QSP and its current scope within

drug discovery and development. It will also highlight the complexities and anticipated challenges and

opportunities for QSP in the future.

Tarek Leil, MS, Ph.D. Bristol-Myers Squibb

Tarek Leil, Ph.D., is currently the Head of the Quantitative Clinical Pharmacology

(QCP) group within Clinical Pharmacology and Pharmacometrics (CP&P) at Bristol-

Myers Squibb (BMS). The QCP group at BMS uses model-based approaches,

including quantitative systems pharmacology (QSP), physiologically based PK

(PBPK), and model-based meta-analysis (MBMA), to integrate clinical and non-

clinical data in a quantitative way to generate actionable predictions. These

predictions can be used to support decision making in pharmaceutical research

and development, to optimize the design of patient clinical trials, and to facilitate communications with

regulatory authorities. Dr. Leil and his group at BMS have published numerous reports demonstrating

the utility of QSP and other modeling & simulation approaches in Pharmaceutical R&D. Prior to joining

BMS in 2011, Dr. Leil worked at Pfizer as a Clinical Pharmacologist in the Department of Clinical

Pharmacology. While at Pfizer he used modeling & simulation approaches to characterize the PK/PD of

compounds in exploratory clinical development for the purpose of informing the clinical development

strategy. Prior to moving to industry, Dr. Leil completed Clinical Pharmacology postdoctoral training at

the Mayo Clinic.

QSP in Drug Discovery: Target Identification and Lead Candidate

Selection/Optimization In drug discovery there are several critical decision points that modeling and simulation can impact: the

selection of the drug target, the definition of the minimal requirements for a drug candidate to be

developable, and the selection of the clinical candidate. For any drug discovery program, it is important

to establish as early as possible the feasibility of achieving the desired target product profile (TPP) in

particular as related to the chosen indication(s), the dose amount and frequency and the route of

administration. Moreover, it is often critical to establish the best-in-class profile for a particular drug

target to enable rational screening and clinical candidate selection, for example which target binding

affinity and drug half-life will be required to achieve best-in-class target occupancy as required per TPP.

In this session, we show how QSP modeling can inform these questions, and how performing these

analyses early can de-risk programs, accelerate timelines, and enable best-in-class therapeutics.

Joshua Apgar, Applied Biomath

Josh Apgar is a Co-founder and Chief Science Officer of Applied Biomath. His

work leveraged physics-based models to: translate in vitro and in vivo data,

assess target feasibility, understand drug mechanism of action, and predict

human doses. The ultimate goal of this work was to reduce late stage attrition

in drug development through a deep and quantitative interrogation of drug

pharmacology and disease pathophysiology. Before co-founding Applied

BioMath, Josh was a Principal Scientist in the Systems Biology Group of the

Department of Immunology and Inflammation at Boehringer Ingelheim

Pharmaceuticals. Prior to that he received his PhD from MIT in Biological Engineering where he worked

on experiment design for Systems Biology, focusing on the identification of tractable experiments that

could allow for the estimation of unknown parameters and reveal complex mechanisms in signal

transduction networks. Before that Josh worked at Avaki to develop a highly scalable software platform

to support High Performance Computing, and Enterprise Information Integration in the Life Sciences,

and Engineering.

Current Landscape of QSP in Pharmaceutical Industry To better understand the current landscape in preclinical QSP modeling and to stimulate the exchange

of knowledge in QSP practices across the biopharmaceutical industry, a preclinical QSP working group

within the IQ DMLG was formed in 2016, consisting of representatives from 17 pharmaceutical

companies, ranging from small biotech to large pharma companies. One of the objectives of the

preclinical QSP working group was to understand current challenges and opportunities for preclinical

QSP modeling within R&D, as well as evaluate the organizational structures of preclinical QSP modelers

within the industry and their interface with other functional experts across R&D and regulatory

agencies. Therefore, a survey was conducted across 50 pharmaceutical companies and was developed

with the support of the International Consortium for Innovation & Quality in Pharmaceutical

Development (IQ). IQ is a not-for-profit organization of pharmaceutical and biotechnology companies

with a mission of advancing science-based and scientifically-driven standards and regulations for

pharmaceutical and biotechnology products worldwide. The results of the survey will be shared in this

workshop session and will provide an understanding of the landscape of QSP across the Pharmaceutical

Industry and its role in drug discovery & development and lead to further dialogues on the value and

application of this approach to improve the probability of clinical success for future drugs.

Maria Nijsen, Ph.D., Abbvie

Marjoleen Nijsen holds a Ph.D. in Pharmacology from the faculty of Medicine at

the University of Utrecht, the Netherlands. Since then she has focused her

pharmacology career in the areas of Neuroscience, Cardiovascular System and

Gastrointestinal Emerging Diseases. In 2003 she switched her career towards the

areas of ADME, bioanalysis, human PK/DDI projection, mechanistic physiological-

based PK (PBPK) and translational PKPD modeling as well as quantitative systems

pharmacology (QSP). She’s currently Vice President of DMPK-BA at Abbvie, to

support drug discovery and development in target validation, compound selection, biomarker

measurements, clinical efficacious dose and DDI predictions across several therapeutic areas, including

Oncology, Neuroscience and Immunology. She is a member of AAPS, ISSX, ISoP, chair of the IQ DMLG

QSP working group and co-member of the IQ CPLG QSP working group.

QSP in Early Clinical Development and Translational Research (case studies where

QSP was used for FIH dose selection and translating PK-PD-efficacy from nonclinical

species to human) The forward and reverse translation of knowledge between non-clinical and clinical researchers is

critical for the successful development of therapeutics. In this context, QSP models provide a framework

to integrate biological knowledge and appropriately tailor the system to non-clinical and clinical

scenarios for translation and in silico exploration of the biological system. This presentation will provide

selected case studies that demonstrate the utility of QSP models for FIH dose selection and the

translation of PK-PD-Efficacy relationships from non-clinical species to humans. It will also discuss the

challenges and opportunities when implementing QSP models in early clinical development and

translational research.

Mary Spilker, Pfizer

Mary Spilker is an Associate Research Fellow and the Oncology Translational

Modeling and Simulation lead within Pfizer’s Medicine Design Department in San

Diego, CA USA. She completed her Ph.D. in Bioengineering at the University of

Washington and pursued post-doctoral research at the Technical University of

Munich. Her research focused on the design and application of mathematical

models to quantify image-derived, time-dependent measurements of chemical

tracers and contrast agents. In 2005, she joined General Electric’s Global

Research Center to continue her research in the development of novel tracers and contrast agents for

medical imaging. Mary transitioned to Pfizer in 2008, where she has applied a variety of mathematical

models to assist with preclinical drug discovery. Her group currently provides modeling support for small

molecule oncology programs from early exploratory stages to first in patient studies. In this capacity,

Mary and her team routinely flex between QSP, PKPD and simpler mathematical expressions/graphical

analyses to efficiently address team questions and impact projects. Mary has served as a board member

for the Association for Women in Mathematics and is a member of the International Society of

Pharmacometrics and American Association of Pharmaceutical Scientists.

QSP in Full Clinical Development: Application in design of Phase II and Phase III

studies Session description unavailable.

Konstantinos (Kostas) Biliouris, Novartis

Kostas Biliouris is currently a Sr. Principal Pharmacometrician at Novartis in

Cambridge, USA. In his role, he is leading the pharmacometrics (modeling and

simulation) strategy for all early stage clinical trials at Novartis Neuroscience.

Before joining Novartis, Dr. Biliouris had interned or collaborated with Biogen,

Ionis, Merck and the FDA. Dr. Biliouris received his Chemical Engineering

Bachelor and Masters degrees with Honors from the Aristotle University of

Thessaloniki, Greece, and his PhD from the University of Minnesota, where he

was elected a top PhD student. His work has been published on different

scientific journals, such as Nature Immunology and CPT:PSP, and was presented more than 30 times at

various National and International Conferences.

Regulatory Perspective on Application of QSP in Drug Development Session description unavailable.

Yaning Wang, U.S. Food and Drug Administration

Yaning Wang is the Director of the Division of Pharmacometrics in the Office of

Clinical Pharmacology at FDA. Before joining FDA, Dr. Wang received his Ph.D.

in Pharmaceutics and master’s degree in Statistics from the University of

Florida from 1999 to 2003. He also obtained a master’s degree in Biochemistry

(1999) from National Doping Control Center and a bachelor’s degree in

Pharmacy (1996) from Peking University in China. Dr. Wang oversees reviews,

research projects, and policy development within the Division of

Pharmacometrics for all disease areas. During his fifteen years of service at

FDA, Dr. Wang received numerous awards, including Award of Merit and FDA Outstanding Service

Award. Dr. Wang served as a committee member for multiple Ph.D. candidates from various

universities. He mentored more than thirty former research fellows (visiting scholars, post-doctoral

scholars, and Ph.D. candidates) at FDA. Dr. Wang has published over 60 papers and given over 150

presentations at various national and international meetings. He served as a board member of the

International Society of Pharmacometrics. He is a member of the Advisory Committee for Chinese

Pharmacometrics Society and a member of the Editorial Advisory Board for the Journal of

Pharmacokinetics and Pharmacodynamics.

Organizing Committee Biographies

Nidhi Sharda, Ph.D., Bristol Myers Squibb

Nidhi Sharda, Ph.D., is currently a Research Investigator in the Metabolism and

Pharmacokinetics (MAP) group at Bristol-Myers Squibb Co. Her primary

responsibilities include providing PK-PD and modeling support for small molecules

and biologics programs in discovery and devising efficient strategies for first-in-human

dose projection and subsequent transition into the clinic. Prior to joining BMS, she

received her Ph.D. degree in Pharmaceutics from University of Minnesota, where she was investigating

the molecular and pharmacokinetic interactions of Amyloid beta protein at the blood brain barrier in

Alzheimer’s disease.

Anjaneya Chimalakonda, Ph.D., Bristol Myers Squibb

Anjaneya Chimalakonda, Ph.D., is currently a Director in the Clinical Pharmacology

and Pharmacometrics group at Bristol-Myers Squibb Co. He is experienced in drug

discovery and clinical development of both small molecules and biologics. He co-led

discovery teams that nominated multiple small molecules and biologics into clinical

development. Anjaneya’s scientific interests are in the area of translational PK-PD

modeling and human dose projection/estimation across various modalities and therapeutic areas. In this

regard, he successfully advised and implemented strategies to understand PK-PD and human dose

projections for discovery programs across therapeutic areas. Prior to joining BMS, he received his Ph.D.

degree in Pharmaceutical sciences from Texas Tech University, in which, he investigated the ADME/PK-

PD of macromolecular steroid conjugates and utility in liver transplantation.