2015 Archived Content
The pharmaceutical industry has been frustrated by the high failure rates of drug development programs, which suggest that the decision making process on various stages of the programs can benefit from some enhancement. One of the approaches rapidly gaining credibility, and showing good promise for informing better decision making is Quantitative Systems Pharmacology (QSP). Cambridge Healthtech Institute will be holding its Inaugural Quantitative Systems Pharmacology conference as part of Discovery on Target with the goal of bringing together experts in QSP and researchers who may be interested in using this methodology. The conference is designed as a knowledge and opinion exchange forum, and will be focusing on strategy and implementation of QSP from early discovery all the way to early clinical development.
Final Agenda
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Wednesday, September 23
11:30 am Registration
12:55 pm Plenary Keynote Program
2:40 Refreshment Break in the Exhibit Hall with Poster Viewing
3:25 Chairperson’s Opening Remarks
Arijit Chakravarty, Ph.D., Director, Modeling and Simulation (DMPK), Takeda Pharmaceuticals International Co.
This session will focus on the application of Quantitative Systems Pharmacology in the pharmaceutical industry setting. The session will be practically focused, addressing real-world issues faced in pharma. Admirers and skeptics of QSP will both find the session useful, as speakers will draw out key themes that are discussed and debated in the hallways of our respective organizations:
- What does QSP offer that ‘traditional’ PK/PD modeling doesn’t?
- How do we know that our QSP models ‘work’?
- What are the key factors driving the effective use of QSP?
3:35 Right Target, Right Dose, Right Trial with Limited Animal Use: QSP Doubles the 3R Benefits
Valeriu Damian-Iordcahe, Ph.D., Head, Modelling and Translational Biology, GSK
Lack of efficacy is the most significant reason for late stage clinical failures. Drug discovery efforts are often based on qualitative link between the target and clinical outcomes and are supported by studies using animal models that may have limited clinical translation. Quantitative Systems Pharmacology provides the missing quantitative link between the target modulation and clinical outcomes allowing the selection of the best target, estimating the optimal target engagement, identifying the patients that would benefit the most from the therapy, and enabling the design of best trial. In this talk I will demonstrate these QSP benefits by using several case studies in dermatology, rare diseases and ophthalmology.
4:05 The QSP Extensibility Concept: A Physiology-Based Multi-Scale Model as a Platform to Address Wide-Ranging Clinical Questions
Mark C. Peterson, Ph.D., Director, Global Pharmacometrics, GIPB Clinical Pharmacology, Pfizer, Inc.
A key aspect of QSP models (QSPMs) is the multi-scale linking of target modulation to clinical outcomes (efficacy, safety). The physiologic linking renders a tool for asking/answering clinically relevant trial design and program development questions. Beyond the initial application, added value and accelerated understanding can be derived in alternate pathologies via QSPM extension. In this session, extensions of an existing QSPM will be presented, highlighting cross-disease area utility.
4:35 Creating and Performing Research with PhysioPD™ Research Platforms: Overview and Case Study
Ananth Kadambi, Ph.D., Senior Vice President, PhysioPD™, Rosa & Co.
Rosa describes in detail the process of creating and conducting research using PhysioPD Platforms to drive scientific innovation in the pharmaceutical industry. PhysioPD Platforms are quantitative systems pharmacology (QSP) models that are designed with multidisciplinary client team input. The PhysioPD research approach is designed to impact client decisions and has been successful in multiple therapeutic indications.
5:05 Refreshment Break in the Exhibit Hall with Poster Viewing
5:40 Diverse Application with a Common Underlying Workflow
Dr. Kapil G. Gadkar, Senior Scientist, Genentech
QSP can be applied to numerous therapeutic areas and throughout the drug development process, from research to late clinical stages. Furthermore, QSP encompasses a broad range of technical approaches and model types. One significant consideration for the robust execution of QSP projects is a general workflow relevant to different model types and applications. Here we present a unified workflow along with diverse examples of QSP efforts in our group in which it has been applied.
6:10 Building Translational Quantitative Pharmacology: The Merck Experience
Prajakti Kothare, Ph.D., Scientific Lead, Early Phase Quantitative Pharmacology & Pharmacometrics, Pharmacokinetics, Pharmacodynamics & Drug Metabolism, Merck
The emerging discipline of Quantitative and Systems Pharmacology has generated increasing interest recently across industry, academia and regulators. Built on the successful implementation of model-informed drug development, Merck has focused its efforts in the last few years on building similar capabilities in drug discovery. An overview of Merck’s experience in building translational and quantitative pharmacology in the discovery space will be presented and exemplified through case studies. A broad-based integration of these approaches through all facets of the discovery paradigm is critical to improving the probability of success to downstream pipeline milestones.
6:40 Close of Day
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Thursday, September 24
7:30 am Registration
8:00 Interactive Breakfast Breakout Discussion Groups
This interactive session provides conference delegates and speakers an opportunity to choose a specific roundtable discussion group to join. Each group has a moderator to ensure focused discussions around key issues within the topic. This format allows participants to meet potential collaborators, share examples from their work, vet ideas with peers, and be part of a group problem-solving endeavor. The discussions provide an informal exchange of ideas and are not meant to be a corporate or specific product discussion.
Partnerships between Academia, Government and Industry to Implement QSP as A New Paradigm for Drug Discovery
Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation, Professor of Computational and Systems Biology, University of Pittsburgh
• What business models are possible?
• How can data on failed drugs be shared?
• Can the FDA handle the emergence of polypharmacology?
Preclinical-to-Clinical Translation in Oncology: Principles and Best Practices
Arijit Chakravarty, Ph.D., Director, Modeling and Simulation (DMPK), Takeda Pharmaceuticals International Co.
• Xenografts as a preclinical cancer model: myths and realities
• Leveraging PDX models for indication selection
• Using modeling to optimize dose and schedule decisions
• Challenges of combination development
Additional Roundtables to be Announced
8:45 Chairperson’s Remarks
Oliver Ghobrial, Ph.D., Senior Research Scientist III, Translational Modeling and Simulation, AbbVie
8:55 A Quantitative Systems Pharmacology (QSP) Framework for Oncology Translational and Early Clinical Development
Arijit Chakravarty, Ph.D., Director, Modeling and Simulation (DMPK), Takeda Pharmaceuticals International Co.
We have developed a QSP framework for translational and early clinical development that is underpinned by an assumption of cancer as an evolutionary process. Our framework is based on rigorous empirical assessments in the preclinical and early clinical settings, and relies on the assessment and iterative refinement of model-based decision analytics as the guiding principle for early development. The proposed talk will outline the framework and provide examples of its application in a range of different contexts.
9:25 Applying Evolutionary Systems Biology To Design Dosing Regimens To Minimize Resistance
Franziska Michor, Ph.D., Professor, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute,Department of Biostatistics, Harvard School of Public Health
Recent advances in high-throughput profiling of cancer genomes have enabled the generation of an unprecedented amount of data. The analysis of this data requires the development of novel computational and mathematical modeling approaches. This presentation will discuss state-of-the art modeling methods addressing treatment response and the evolution of resistance.
9:55 Development and Application of the Coagulation Systems Model
Fei Hua, Ph.D., Clinical Pharmacology Lead, PharmaTx Clinical R&D, Pfizer, Inc.
We have modified the coagulation systems model from literature and validated with internal data. The model has been used to help multiple programs on the pathways and the range of questions the model has addressed ranging from early discovery to clinical.
10:25 Coffee Break in the Exhibit Hall with Poster Viewing and Poster Winner Announced
11:10 Applications of Quantitative Systems Pharmacology (QSP) in Crohn’s Disease Drug Discovery and Development
Oliver Ghobrial, Ph.D., Senior Research Scientist III, Translational Modeling and Simulation, AbbVie
A CD QSP platform was developed to describe the homeostatic interactions between the gut microbiome, epithelial barrier, damage and repair mechanisms, and immune system in health and disease. A novel approach to virtual patient development will be presented and utility of this approach to explore competing hypotheses of CD pathophysiology will be demonstrated.
11:40 Adaptive Resistance and Fractional Response of Cancer Cells to Therapy
Mohammad Fallahi-Sichani, Ph.D., Merck Fellow of the Life Sciences Research Foundation, Department of Systems Biology, Harvard Medical School
Drug adaptation in melanomas and other cancers driven by different oncogenic pathways limits therapeutic effectiveness leading to temporary responses in patients, the primary challenge facing targeted therapy. I will describe a systems pharmacology approach combining multiplex biochemical measurements and computational modeling to characterize drug-induced adaptive responses and their consequences for cancer cell fate and to use that information to guide development of strategies to enhance drug maximal effect and to prevent drug resistance.
12:10 pm QSP Approaches Enabling Quantitative Decisions in Drug Discovery from Early Research to Clinical Trials
John Burke, Ph.D., Co-Founder, President and CEO, Applied BioMath, LLC
QSP approaches have been used successfully in Pharma and Biotechs to drive quantitative decisions to reduce late stage attrition, and accelerate best-in-class therapeutics to meet unmet medical need. Here we show several case studies in Immuno-Oncology where these approaches have driven quantitative decisions resulting in savings of millions of dollars and shortening timelines.
12:40 Session Break
12:50 Luncheon Presentation (Sponsorship Opportunity Available) or Lunch on Your Own
1:30 Refreshment Break in the Exhibit Hall with Poster Viewing
2:15 Chairperson’s Remarks
Ananth Kadambi, Ph.D., Senior Vice President, PhysioPD™, Rosa & Co.
2:20 Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery in Academia.
Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation, Professor of Computational and Systems Biology, University of Pittsburgh
A sufficient understanding of the biology underlying how disease phenotypes arise from predisposing genetic variations is often the limiting determinant for optimal target and companion biomarker selection for therapeutic development and patient stratification. Consequently, drug candidates exhibiting well defined pharmacokinetic and pharmacodynamics profiles entering Phase II and III trials often fail to demonstrate proof-of-concept. To address this challenge, we describe a broadly applicable, network-centric, quantitative systems pharmacology (QSP) drug discovery and development platform to complement and enhance current target-focused and phenotypic-based approaches. The integration of the clinical, computational and experimental elements of QSP will be addressed in examples from metastatic breast cancer, Huntington’s Disease and Liver diseases.
2:50 Systems Pharmacology Insights for Patient Selection for Liposomal Anti-Cancer Therapy: From Idea to Clinical Evaluation
Birgit Schoeberl, Ph.D., Head, Discovery, Merrimack Pharmaceuticals
Quantitative systems pharmacology modeling of liposomal anti-cancer therapies has led to key insights surrounding the importance of tumor deposition on overall drug delivery. Model insight led to the concept of an imaging diagnostic that has been advanced to clinical evaluation. Model based analysis of patient tumor kinetic data further contributed to a detailed understanding of drug delivery in human tumors.
3:20 Session Break
3:25 Chairperson’s Remarks
Matthew Onsum, Ph.D., President and CEO, Silver Creek Pharmaceuticals
3:30 Engineering Targeted Growth Factors to Repair Heart Tissue Following Ischemic Injury
Matthew Onsum, Ph.D., President and CEO, Silver Creek Pharmaceuticals
Silver Creek is developing a new class of targeted, growth factor-based therapeutics (Smart Growth Factors, SGFs) for treating heart disease that are engineered to have optimized selectivity, pharmacokinetics, and safety profiles. Designed using principles of systems pharmacology, our SGFs selectively activate pro-survival and repair signaling pathways in heart tissue damaged by ischemia and lead to reduced infarct size in vivo without off-target effects
4:00 Kriging is an Emerging Technology that Has the Potential of Improving the Precision of in silico Predictions and Eliminate the Need for Creating Local Models
Istvan Enyedy, Ph.D., Senior Scientist, Chemistry and Molecular Therapeutics, Biogen
We have built databases using in-house or literature compounds with measured hERG patch clamp IC50, volume of distribution, P450 inhibition IC50, MDCK permeability. This data was used to test the usefulness of kriging as a method for building in silico prediction tools. We tested the validity of the models using leave one class out approach which should be the most challenging for kriging. The advantages and disadvantages of this method will be presented.
4:30 A Massively Orthogonal Pharmacology Search Engine: Can All of Our Models and Data Be “GoogledTM”?
Douglas Selinger, Ph.D., Manager, Bioinformatics, Preclinical Safety, Novartis Institutes for BioMedical Research
We’ve developed a search engine which returns target data & predictions for a query small molecule. The search is automatically expanded to include compounds with structural similarity or a shared biological response, e.g. a similar transcriptional profile. Targets are then prioritized by consensus, as well as by algorithms such as PageRank, the algorithm made famous by GoogleTM. Despite searching large numbers of heterogeneous data sets and in silico model results (currently >15 models and/or data sets; ~200 million data)
5:00 Close of Conference
Day 1 | Day 2 | Download Overall Brochure | Download QSP Brochure