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STP Virtual Continuing Education Courses

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The Society of Toxicologic Pathology is offering three continuing education courses virtually in 2021. All course registrants will also be able to download the course book a week prior to each webinar.

 

STP Virtual Continuing Education Courseswith AAVSB RACE Approved for CE Credits logo seal

This program has been approved for 3.50 hours of continuing education credit in jurisdictions that recognize RACE approval.

AAVSB RACE Approved for CE Credits logo seal

Stem Cell-Derived Therapy Nonclinical Safety Assessment

Friday, August 27

Co-Chairs: Kevin Keane, DVM, PhD, FIATP, Novo Nordisk A/S; Jerrold M. Ward, DVM, PhD, DACVP, Global VetPathology; and Ricardo Ochoa, DVM, PhD, DACVP, Pre-Clinical Safety Inc.

This continuing education course will cover the nonclinical aspects of stem cell-derived therapies intended for human disease indications requiring replacement tissues such as type I diabetes, Parkinson’s disease, ocular (macular) degeneration, and myocardial infarction. An introductory lecture on the current state of stem cell differentiation protocols and in vitro characterization will begin the course. The presentations will emphasize the design, implementation, and interpretation of nonclinical studies which are required for regulatory submissions. The topics covered will include considerations of the animal model, cell implant methods, immunological evaluation, and cell fate determination methods. Current regulatory guidances will be also covered and end-of-course panel discussion will be used to wrap up the course.

Gene Therapy via Hematopoietic Stem Cells
Curt I. Civin, MD, University of Maryland School of Medicine, Baltimore, MD

Stem Cell-Derived Models of Neurodegeneration
Valina L. Dawson, PhD, Institute for Cell Engineering, Johns Hopkins Medicine, Baltimore, MD

Regulatory Update on Nonclinical Studies with Stem Cell-Derived Products
Ricardo Ochoa, DVM, PhD, DACVP, Preclinical Safety, Inc., Hollywood, FL

Combining Stem Cell-Derived Products with Biomaterials for Long-Term Implants
Kevin Keane, DVM, PhD, FIATP, Novo Nordisk A/S, Måløv, Denmark

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Registration required to access course.



Course Registration

*A letter of verification from a department chair must accompany student registration.


STP Virtual Registration Fees
(per CE course)
STP Member $ 145
Nonmember $ 195
STP Student Member $ 45
Nonmember (Student) $ 75
STP Member Group Rate*
(Three or More from the Same Company)
$ 125
Nonmember Group Rate*
(Three or More from the Same Company)
$ 175
*To take advantage of the group rate please send your completed registration forms to stp@toxpath.org.
All three forms (or more) should be emailed at the same time.
STP Virtual Continuing Education Courseswith AAVSB RACE Approved for CE Credits logo seal

Applications of Artificial Intelligence and Machine Learning in Toxicologic Pathology

Friday, September 24

Co-Chairs: Famke Aeffner, DVM, PhD, DACVP, Amgen; Oliver C. Turner, BSc(Hons), BVSc, MRCVS, PhD, DACVP, DABT, Novartis Institutes for Biomedical Research; and Manu S. Sebastian, DVM, PhD, DACVP, DABT, ACLAM, MD Anderson Cancer Center

Artificial intelligence (AI) and machine learning (ML) are transforming all aspects of health care—including drug development. This CE course aims at introducing this technology to toxicologists and toxicologic pathologists, as well as highlighting promise and pitfalls. To illustrate the power of machine learning, the session concludes with presentations highlighting practical applications, presented by colleagues with hands-on experience.

Introduction to Artificial Intelligence and Machine Learning
Oliver C. Turner, BSc(Hons), BVSc, MRCVS, PhD, DACVP, DABT, Novartis Institutes for Biomedical Research, East Hanover, NJ

General Uses of AI in Drug Development: AI and ML in Other Aspects of Drug Development
Manu S. Sebastian, DVM, PhD, DACVP, DABT, ACLAM, MD Anderson Cancer Center, Smithville, TX

General Uses of AI in Drug Development: Overview of Partnerships Formed by Pharma with AI Companies in the Pathology Space
Bhupinder Bawa, DVM, MVSc, PhD, DACVP, AbbVie, North Chicago, IL

Implementation: Preparing Pathology Data for ML Experiments
Jürgen Funk, DVM, FTA Pathology, Roche, Basel Switzerland

Implementation: IT Infrastructure Requirements
Julie Boisclair, DVM, DES, MSc, DACVP, DABT, Novartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland

Practical Examples: Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks
Heike A. Marxfeld, PhD, DECVP, EBVS, BASF SE, Ludwigshafen, Germany

Practical Examples: Deep Learning AI in Decision Support for the Bench Toxicologic Pathologis
Daniel G. Rudmann, DVM, PhD, DACVP, FIATP, Charles River Laboratories, Broomfield, CO

Registration



STP Virtual Continuing Education Courseswith AAVSB RACE Approved for CE Credits logo seal

This program has been approved for 3.00 hours of continuing education credit in jurisdictions that recognize RACE approval.

AAVSB RACE Approved for CE Credits logo seal

Moving a Drug into the Clinic: Using PK/PD Modeling to Assess Benefit/Risk and Guide Dosing in Early Trials

(Sponsored by the American College of Toxicology)

Held on Friday, July 23

Co-Chairs: Ryan J. Hansen, PhD, Eli Lilly & Company; and Andrew Vick, PhD, Charles River Laboratories

The process of advancing potentially therapeutic molecules from discovery to early clinical trials can be costly, time consuming, and be associated with considerable uncertainty and risk. There are three key areas where uncertainty and risk need to be evaluated, and important decisions made regarding the future of a candidate molecule: transition to first-in-human development, predicting the human efficacious dose, and selecting the maximum recommended starting dose and dosing scheme for the first in human trial. In this session we will discuss how PKPD and other quantitative pharmacology approaches can be applied to provide a more quantitative assessment of feasibility and risk, and inform better decision making for drug candidates.

Predicting the Optimal Dose and Dose Regimen in Early Clinical Trials
Jessica Hawes, PhD, US FDA/CDER, Silver Spring, MD

The Therapeutic Index: A Tool for Informing Molecule Selection and Advancement
Jay Tibbitts, DVM, PhD, Surrozen, South San Francisco, CA

Nonclinical-to-Clinical Translation: Use of PK/PD Modeling to Help Bridge Gaps
Brian Stoll, PhD, AbbVie, South San Francisco, CA

Leveraging Nonclinical Data to Predict Clinical Performance: KAI-4169 Case Study
Andrew Vick, PhD, Charles River Laboratories, Ashland, OH

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