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Short Courses



Morning Courses | 9:00 am—12:00 pm*

Marshall BioResourcesAddressing Safety Concerns for Biologics and Biosimilars

  • What are typical biologics safety data and program approaches?
  • Application of safety studies (Tox, Safety Pharm, Safety Pharm-Reg tox hybrid)
  • Overview of the current guidance in ICH S6 and the ICH S6 addendum
  • Unique safety challenges and risk mitigation strategies
  • Data interpretation and follow-up studies
  • Overview of biosimilar drug development, including the reduced, but comparative nonclinical program and the choice of reference product

Noël Dybdal, Ph.D., D.V.M., Associate Director, Principal Scientist, Safety Assessment, Genentech, Inc.
Ulrich Certa, Ph.D., Head, Molecular Toxicology, Non-Clinical Safety, pRED, F. Hoffman-La Roche
Anne Ryan, Ph.D., Executive Director, Drug Safety Research and Development, Pfizer, Inc.

Utilization of Cardiac Contractility Assays for Preclinical Safety Testing 

  • Basics of cardiovascular physiology and definition of myocardial contractility 
  • In vitro and in vivo models and measurements 
  • Assessment of myocardial contractility and ventricular vascular coupling from pressure-volume loops ("gold" standard) and load dependent methods 
  • Translational challenges: What change in myocardial contractility constitutes a drug liability? If we do not know, why measure it? 
  • Data interpretation and limitations 

Robert Hamlin, Ph.D., Professor, Veterinary Biosciences, Ohio State University
Jonathan Heyen, Principal Scientist, Global Safety Pharmacology, Pfizer Global Research & Development

Animal Models of Pain: Progress and Challenges

  • Classical models of acute, tonic and chronic pain
  • Limitations of these classical models
  • Refinement of classical models via a consideration of modulatory factors (sex, genetics, testing environment, social modulation)
  • Development of new animal models (e.g., operant methods, spontaneous behaviors)

Jeffrey S. Mogil, Ph.D., E.P. Taylor Professor of Pain Studies, McGill University

Design and Interpretation of Stability Studies for Product Development

Developing a Line-of-Sight for Product Stability – Forced Stress Testing Through ICH Stability Requirements

Robert A. Reed, Ph.D., Vice President, CMC & Technical Operations, Celsion Corp.

Best practices have been established for forced stressed degradation studies that allow an accurate prediction of chemical “potential” for a reaction to occur. Furthermore, in-silico prediction software is emerging as a useful tool to fully consider likely reactive pathways that may play an important role in the drug stability. This talk will attempt to provide a high level introduction for best practices to establish degradation potential for a drug substance and some of the pit falls that one may encounter in bridging to ICH stability studies.  Case examples will be presented to highlight some of the presented concepts. Overall, the goal is to develop confidence in the predictability and interpretation of early drug development product stability studies for the commercial market.

Controlling Reactive Components in Polymeric Pharmaceutical Excipients for Improving the Stability of APIs

Shaukat Ali, Ph.D., Technical Sales Manager, BASF Corp.

Excipients play important roles in the stability of APIs in the drug development. The key attributes leading to instability of a drug could vary from the nature of an API and the excipients used in the formulation dosages.  Most importantly, the drugs sensitive to peroxides may have direct implication on the stability of product development. This presentation will cover the understanding of underlying mechanisms for oxidation of drugs and identifying the appropriate measures or safe guards to improve the stability of an API  from the excipients’ perspectives.  

Integrating Mechanistic Drug Degradation Pathways and Mathematical Modeling in Stability Assessment and Prediction

Ajit S. Narang, Ph.D., Sr. Research Investigator, Drug Product Science & Technology, Bristol-Myers Squibb, Co.

Predicting the kinetics of drug degradation on storage stability can be challenging. Integrating mechanistic understanding of the drug degradation pathway along with kinetic mathematical modeling of the degradation rate can not only help predict drug product stability, but also quantify the effect of underlying variables and identify mitigation strategies. In this talk, case studies would be presented where mechanistic understanding was combined with mathematical modeling to understand and mitigate stability risks during the manufacturing and stability of an oral solid dosage form.

Afternoon Courses | 2:00—5:00 pm*

Use of Stem Cells for Safety Screening 

  • Types of stem cells being used for drug toxicity testing- What can they offer? 
  • Comparing testing and use of stem cells versus primary cells 
  • Overcoming technical challenges related to working with stem cells 
  • Maintaining and characterizing stem cells for routine predictive safety testing 
  • Regulatory challenges with using stem cells 

Matthew Peters, Ph.D., Principal Scientist, Safety Assessment, AstraZeneca
Additional Instructors to be Announced

Introduction to Drug Metabolism and Its Role in Drug Toxicity

  • Basic concepts of drug metabolism
  • In vitro tools to investigate drug metabolism
  • Biotransformation pathways
  • Understanding the role of reactive metabolites in idiosyncratic drug toxicity
  • Role of drug transporters in toxicity
  • In silico tools to aid drug metabolism research

John Erve, Ph.D., D.A.B.T., former Principal Scientist, DMPK, Elan Pharmaceuticals, Inc.

Epigenetic Mechanisms of Pain 

  • Introduction to epigenetic mechanisms 
  • Identifying and validating targets 
  • Unique challenges and opportunities with epigenetic targets 
  • Current state of drug discovery in this area 

Chas Bountra, Ph.D., Professor of Translational Medicine & Head, Structural Genomics Consortium, University of Oxford
Additional Instructors to be Announced

Development of Nanotechnology Application into Innovative Therapies

  • Fundamentals of design, formulation and nanoparticle characterization for nanotechnology-based therapies
  • Effective design & utilization of in vivo small and large animal models for preclinical evaluation of nanomedicine
  • Challenges for the successful introduction of novel nanomedicine products into clinical trials and the commercial markets

Seungpyo Hong, Ph.D., Assistant Professor of Pharmaceutics and Bioengineering, Department of Biopharmaceutical Sciences, University of Illinois College of Pharmacy
Uma Prabhakar, Ph.D., Consultant, Office of Cancer Nanotechnology Research NCI-NIH

Roadmap for Outsourcing of Preclinical Imaging


This complimentary workshop is designed as a one stop shop event for individuals from industry to get a sense of the preclinical imaging CRO landscape. With the recent trend of outsourcing more and more preclinical imaging to CROs, pharma companies are often missing the critical information of imaging and scientific capacities of various imaging CROs.
Participants include: Maccine, InviCRO, Molecular Imaging, Inc. 

InviCROProcessing, Analyzing, Reporting and Archiving Images in Drug Discovery and Development

Matthew Silva, Ph.D., Director, Imaging Research, inviCRO, LLC

Improvements in pre-clinical imaging instrumentation over the past decade enabled an increase in novel, translational in vivo imaging applications. While molecular probes and image acquisition protocols have translated well, however, there has not been an analogous translation of image processing protocols. Using case studies, this talk will focus on improving the reproducibility and throughput of pre-clinical image processing protocols across a broad spectrum of applications.

MaccineApplication of Imaging Technologies to Drug Discovery and Development Studies in Nonhuman Primates

Mahesh Mistry, Ph.D., Executive Director, Preclinical Development, Maccine Pte Ltd

The wider application of imaging technologies to preclinical drug efficacy and safety research has the potential to greatly improve prediction of clinical success; especially when applied to non-human primate studies. Herein we describe how PET, CT and MRI imaging modalities are being applied to nonhuman primate efficacy, ADME/PK and safety studies.

Molecular Imaging Research, Inc.Pharmacology Imaging: Molecular Imaging's Unique Approach to in vivo Studies

Patrick McConville, Ph.D., COO & CSO, Molecular Imaging, Inc.

This is an overview of pharmacoimaging at Molecular Imaging. By combining extensive pharmacological expertise with broad imaging capabilities, our preclinical studies benefit from richer and clinically relevant data enabling better decision making, improved clinical trial design and more confident lead candidate selection.

Wednesday , June 5

Dinner Short Courses | 6:00 pm—9:00 pm*

»Advances in Imaging Quantitation 

Scientific Advisor and Course Moderator
James Gee, PhD, Professor and Director, Penn Image and Computing Science Laboratory, University of Pennsylvania

The short course includes three lectures: 

I. Image Segmentation I
Instructor: Paul Yushkevich, Ph.D., Assistant Professor, Department of Radiology, University of Pennsylvania
In a multitude of image analysis applications, segmentation plays a crucial supporting role. It is a necessary first step for measuring the volume, thickness, and shape of anatomical structures. It is equally necessary for measuring physiological properties of tissues and organs. After decades of research, fully automatic segmentation remains elusive for many applications. Furthermore, some of the most effective automatic segmentation methods are highly application-specific, require extensive training data in the form of expert manual segmentations of example images, and thus very difficult for end-users to implement. Despite these challenges, more and more general-purpose software tools for image segmentation are becoming available, making accurate automatic segmentation more broadly available to imaging researchers. In this lecture, we will discuss effective automatic, semi-automatic and manual segmentation approaches that can be practically implemented using freely available software.

  • A decision tree for segmentation approaches and software; 
  • Manual segmentation: tools, protocols, reliability analysis; 
  • Semi-automatic segmentation with active contours using ITK-SNAP; 
  • Atlas-based segmentation and multi-atlas label fusion using ANTS; 
  • Automatic brain segmentation using complex, multi-algorithmic packages FSL and FreeSurfer; 
  • Validation of automatic segmentation. 

II. Image Registration
Instructor: Brian Avants, Ph.D., Postdoctoral Researcher., Department of Radiology, University of Pennsylvania
Overview Biomedical image registration maps a known coordinate system onto unstructured data.  This tool is useful in several application areas:  medical diagnostics, planning and following radiation therapy, tracking pharmaceutical efficacy during longitudinal studies and in brain mapping.  Tremendous algorithmic progress over the last 10 years extends the types of problems that may be studied successfully with this powerful analysis technology.  Furthermore, several advanced image registration tools are now freely available to the public.  We will introduce basic concepts in image registration and illustrate its application within application areas at the cutting-edge of translational biomedical science.

  • Build a population-specific template coordinate system; 
  • Map this coordinate system to new subjects or within a subject over time; 
  • Evaluate the success of longitudinal and cross-sectional transformations; 
  • Collect population information within the template coordinate system; 
  • Do a basic statistical analysis in a template space. 

III. Image Segmentation II
Instructor: Kevin Zhou, Ph.D.,  Research Group Head, Siemens Corporate Research
Overview Efficient, effective, and fully automatic segmentation of anatomical structures is highly desired for many high-throughput 3D imaging applications but still remains elusive. Recently, context learning methods offer promising solutions. They are based on machine learning principles, such as classification and regression, to learn the statistical relationships between the anatomical structures of interest and 3D images from an annotated database consisting of both images and their corresponding annotations. In this lecture, we will present approaches that leverage anatomical context embedded in the medical images and illustrate the efficiency and effectiveness of these approaches using real examples.

  • Challenges and opportunities for efficient and effective image segmentation;
  • Anatomical context and its categorization;
  • Context learning: Classification vs Regression;
  • Context integration;
  • Rapid multi-organ segmentation from human and animal images. 

»Genetically Engineered Mouse Models versus Patient-Derived Xenograft Models: Comparing Strengths and Limitations.

The versatile agenda for this course aimed at comparative assessment of contemporary approaches to model cancer in two best predictive murine
systems will include the following topics:

  • Design, development and preclinical validation of genetically engineered (GEM) and patient-derived xenograft (PDX) mouse models;
  • Review the current spectrum of available GEM and PDX models outlining annotation practices and benefits vs. shortcomings of two different methodologies as highlighted by specific examples;
  • Analyze current and expected impact of modeling cancer in GEMs and PDXs on in-depth disease analysis and designing therapeutic strategies for unmet need” rare cancer types;
  • Discuss informative capabilities of preclinical models to guide decision making at clinical trial steps of oncology drug evaluation;
  • Describe differential approaches in modeling disease evolution vs. advanced/metastatic disease using GEMs and PDXs in the context of multi-facet implications of murine cancer models for e.g. advanced studies on molecular basis of carcinogenesis, biomarker and imaging modality development and preclinical drug efficacy assessment;
  • Provide examples of available integrated GEM and PDX resources, operational workflows and best practices of exploring murine models for translational and preclinical experimentations.



Serguei Kozlov, Ph.D., Principal Scientist, Center for Advanced Pre-Clinical Research, SAIC-Frederick, Inc.
M. Raza Zaidi, Ph.D., Assistant Professor of Biochemistry, Fels Institute for Cancer Research & Molecular Biology, Temple University School of Medicine
Gwenn Danet-Desnoyers, Ph.D., Director, Stem Cell and Xenograft Core, Adjunct Associate Professor, Hematology-Oncology, University of Pennsylvania School of Medicine
Dylan Daniel, Ph.D., Investigator III, Oncology Pharmacology, Novartis Institutes for Biomedical Research
Hui Gao, Ph.D., Investigator III, Novartis Institutes for Biomedical Research

*Separate Registration Required

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