Contents:
Keynote: Impact of Artificial Intelligence in Understanding Toxicological Insights
Stefan Platz, DVM
Senior Vice President of Clinical Pharmacology and Safety Sciences, AstraZeneca
Wednesday, June 5, 2019
4-5pm
Johns Hopkins Bloomberg School of Public Health
615 N. Wolfe St
Baltimore, MD 21205
Becton Dickinson Hall (W1020)
Stefan Platz is the Senior Vice President of Clinical Pharmacology and Safety Sciences within AstraZeneca’s R&D BioPharmaceuticals unit. In this role, Stefan is responsible for the non-clinical safety assessment of all drug candidates, delivery of non-clinical and clinical bioanalysis strategies and clinical pharmacology and pharmacometrics. He leads a global department of 600 scientists spread across Sweden, UK and the US.
Stefan has a degree in veterinary medicine from the University of Munich and is a German certified veterinary pathologist as well as Diplomate of the American Board of Toxicology. He started his career in 1996 at Boehringer-Ingelheim. Before joining AstraZeneca in February 2012, Stefan led the non-clinical safety organisations for Hoffmann-La Roche in both Basel and Palo Alto. During this time period he also had extended periods of strategic responsibilities for the early safety screening as well as biologics safety.
Stefan is particularly interested in exploring novel approaches and technologies to better predict human safety based on in vitro and in silico data. Recent investments by AstraZeneca in microphysiological systems may help to understand safety risks in patients based on a dynamic cell system mimicking full organ functionality. Together with modelling and simulation of human data this might accelerate drug development and result in a reduction in number of animal used in preclinical testing.
The keynote will be streamed live. Please use the following link to join:
http://www.ustream.tv/channel/johns-hopkins-bloomberg-school-of-public-health
Questions? Email caat@jhu.edu
Image credit: The Scientist
AI Beats Animal Testing at Finding Toxic Chemicals (The Scientist)
CAAT Director Thomas Hartung recently penned an editorial for The Scientist.
Excerpt:
There are more than 100,000 chemicals in consumer products. For the vast majority, there is very little information about their toxicity. Traditionally, researchers will test chemicals of interest in animals. As an extreme example, a pesticide undergoes about 30 animal tests, costing about $20 million and consuming more than 10,000 mice, rats, rabbits, and dogs over five years. About 20 kilograms of the chemical are needed for this testing; obtaining such a volume can be quite a challenge for a substance not yet on the market. Other substances receive less scrutiny, but even products with lower regulatory standards, such as industrial chemicals, can require $5 million worth of animal testing before entering the marketplace.
Our group, the Center for Alternatives to Animal Testing (CAAT) at Johns Hopkins University, sought a better way. As so many biologists are doing these days, we turned to intelligent computer programs for help. We showed that artificial intelligence (AI) could mine existing data on chemical toxicity and generate new information. In 2016, we compiled a database of 800,000 toxicological studies on more than 10,000 chemicals registered under the European REACH legislation for industrial chemicals, and used it to feed an advanced predictive algorithm that enabled us to predict the toxicity of any chemical without setting foot in the animal lab.
The software takes advantage of the power of big data and transfer learning, a machine learning method that applies information from one task or set of items to another. Similar chemicals have similar properties. Based on that principle, the software builds a map of the chemical universe. Similar chemicals are put close to each other, dissimilar ones more distant. Then, the model can place new chemicals on the map, assess what is known about their neighbors, and from that information surmise their potentially harmful health and environmental effects. The more data are fed into the model, the more powerful it becomes.
Full Article (The Scientist)
Thomas Hartung to Deliver Keynote at American College of Toxicology Annual Meeting
Thomas Hartung will deliver the keynote talk at the 2019 American College of Toxicology Annual Meeting on Tuesday, November 19th in Phoenix, Arizona. Hartung's talk is From Microphysiological Micropathophysiological Models. The meeting takes place from November 17-20th.
This November gathering brings together a community of toxicologists at small venues conducive to idea exchange, professional networking, and continuing education. The scientific sessions are member driven, pharma-focused (but not pharma-exclusive), and organized to maximize learning opportunities. The 40th Annual Meeting will include a wide-ranging scientific program, a welcome reception and dinner, the popular traditional poster session reception, an awards ceremony and luncheon, distinguished plenary speakers, and numerous professional networking events.
Full Details and Registration
New Algorithm Allows Faster, Animal-Free Chemical Toxicity Testing (Rutgers Today)
Hao Zhu is a CAAT grantee and co-authored the paper along with Thomas Hartung.
From the article:
Using animals to test the toxicity of chemicals may eventually become outdated thanks to a low-cost, high-speed algorithm developed by researchers at Rutgers and other universities.
Toxicity testing – or determining the amount of exposure to a chemical that is unsafe for humans – is vital to the safety of millions of workers in various industries. But of the 85,000 compounds used in consumer products, the majority have not been comprehensively tested for safety. Animal testing, in addition to its ethical concerns, can be too costly and time consuming to meet this need, according to the study published in the journal Environmental Health Perspectives.
Full Article (Rutgers Today)
EBTC's Katya Tsaioun Speaking at World Pharma Week in Boston on June 20th
EBTC's Katya Tsaioun will be speaking at the World Pharma Week in Boston on June 20, 2019, where she will be showing the data from the EBTC modeling project on predicting drug liver toxicity using systematically reviewed published literature, public US EPA ToxCast database, and adverse events databases. She will be highlighting the quality and detail of the data in published literature and other public and proprietary databases.
Full Information
Marcel Leist in Der Spiegel (German)
CAAT Co-direcor Marcel Leist was quoted in Der Spiegel about how scientists are looking for ways to reduce animal research.
Heile Mause (Der Spiegel, PDF in German)
Workshop: Assuring the Quality of Systematic Reviews Published in Toxicology and Environmental Health Journals
May 29-31, 2019
Research Triangle Park
t
4 (Transatlantic Think Tank for Toxicology) workshop for toxicology journal editors: “Assuring the Quality of Systematic Reviews Published in Toxicology and Environmental Health Journals.”
This workshop will bring together editors to develop a joint strategy which will assure the quality of the systematic reviews published in environmental health and toxicological sciences journals. Proceedings will be published in
ALTEX. This workshop is funded by t
4, the Transatlantic Think Tank for Toxicology, a collaboration of the toxicologically oriented chairs in Baltimore, Konstanz, and Utrecht sponsored by the Doerenkamp-Zbinden Foundation and the Evidence-based Toxicology Collaboration (EBTC) at Johns Hopkins University Bloomberg School of Public Health (USA).
EBTC News Page
NOTE: This workshop is by invitation-only.
Evidence Integration Workshop: Integrating Mechanistic/In Vitro Evidence into the Risk Assessment
June 3, 2019
Washington, DC
EBTC Director Katya Tsaioun is serving on the organizing committee of the US National Academies of Sciences series of workshops on integrating mechanistic/in vitro evidence into the risk assessment
Registration and Information
Free Public EBTC Workshop: Application of Evidence-based Methods to Construct Mechanistic Frameworks for the Development and Use of Non-animal Toxicity Tests
June 12, 2019
McMaster University, Hamilton, Ontario, Canada
Webcast Link • Live webcast begins 8:50am (US Eastern Time)
Systematic evidence synthesis methods and adverse outcome pathways are two relatively recent arrivals in the toxicologist's toolbox that promise to bring toxicological research into the 21st Century.
Objectives
The goal of this workshop is to explore, via discussion of four related themes and how systematic review methods and AOP concepts can be combined to develop and use non-animal test methods for predicting the toxicity of chemical substances in an evidence-based manner.
1. How do we distinguish high quality
in vitro studies from low quality ones?
2. What does a systematic approach to AOP development look like?
3. How does one distinguish spurious AOPs from plausible ones?
4. How can one use AOP information to develop non-animal toxicity assays?
Registration for this meeting is free and open to everyone; however, due to limited seating the organizing committee will have to make a final decision on participation depending on demand and the scientific objectives of the workshop. Please do not make any travel arrangements until you receive an official email confirming your attendance.
Registration and Information •
Live Webcast Link (Begins 8:50am Eastern Time)
CAAT-Europe Information Day On Biology-inspired Microphysiological Systems (MPS) to Advance Medicines for Patients' Benefit
June 17, 2019
Berlin, Germany
Co-organized with the Centre for Entrepreneurship (CfE) of the Technische Universität Berlin
The Information day on “Biology-inspired Microphysiological Systems (MPS) to Advance Medicines for Patients' Benefits” will host key international experts from academia, regulatory agencies, and industry.
Microfluidic microphysiological systems (also referred to as tissues-on-a-chip, organ-on-a-chip, multi-organ-chip, human-on-a-chip, body-on-a-chip, or patient-on-a-chip tools) are considered an enabling technology for the development of approaches to reliably predict the safety and efficacy of novel drug candidates prior to their use in humans. A transatlantic toxicology think tank involving academia, industries, and regulatory bodies from all over the world reviewed the status quo of MPS in June 2015 in Berlin (Marx et al., 2016,
ALTEX 33,272-321). Now, four years later, stakeholders will meet again in Berlin to update the review and to examine the roadmap for the reduction and replacement of animals by MPS tools for precision benefits for patients.
Full Details
Submissions Open for Research Topic: Emerging Methodologies for Drug Safety—from In Silico Predictions to Translational Biomarkers
(Frontiers in Artificial Intelligence and Frontiers in Big Data)
Attrition due to safety attrition remains a problem for the pharmaceutical industry. Traditionally, in vivo animal studies have been used to derisk new drugs and years of data are available for most large pharma, often though in multiple formats and kept in a variety of systems/places. In the meantime, the debate on the use of animals has moved on for assessing chemical risk under the 3Rs principles, especially in the European Union (EU), where animal testing for cosmetics was phased out from 2004 with a total ban in 2013. These animal-free approaches have tremendous value to support drug discovery and development, particularly for drug safety.
In recent years, many large pharmaceutical companies have adopted the discovery toxicology paradigms which use in silico methodology and simple in vitro testing to predict potential adverse human outcomes. The challenge here is the extrapolation from in silico and in vitro to animal, if not human, outcomes. Often, in vivo animal data are inconsistent with respect to pathology nomenclature and study duration. In vitro data often lack reproducibility and statistical relevance. Data storage and retrieval for both in vivo and in vitro data is often challenging. The desire to accurately predict using one’s own data requires an infrastructure that utilizes data storage, machine learning, a variety of software applications for in silico modeling, and the ability to process and model high throughput high content data. Some the 3Rs approaches such as Adverse Outcome Pathways (AOPs) and in vitro-in vivo extrapolations (IVIVE) could play a role through linking and integrating diverse datasets for drug safety.
This special volume will discuss the new data streams and approaches from emerging methodologies to support drug safety assessment involving the entire drug discovery and development process.
Submission Details (Frontiers of Artificial Intelligence and Frontiers in Big Data)
SAVE THE DATE!
8th Annual Meeting of the American Society for Cellular and Computational Toxicology
September 25-26th, 2019
Gaithersburg, MD
The meeting will include:
- Expert plenary lectures featuring Glenn Myatt (Leadscope) ad
Nicole Kleinstreuer (NICEATM)
Panel discussion on data and methodology quality and transparency
- Social reception and networking event
- Poster and oral presentations drawn from submitted abstracts
- Mentoring activity and awards for young scientists
Oral abstract submission deadline is June 28, 2019
Registration, Information, and Abstract Submission
