Pistoia Alliance Webinars
Thought provoking webinars discussing areas and opportunities where collaboration will advance innovation in R&D
Our webinars bring experts together to discuss and share their thoughts on the key topics and technologies that can advance R&D in our industry and highlight how collaboration can make a difference. Our 2020 series has just launched, you can find out about our upcoming webinars here.
Watch the past webinars below.
This webinar sponsored by the Pistoia Alliance and the Quantum Economic Development Consortium (QED-C) focuses on the emerging opportunities at the convergence of Quantum Computing (QC) and pharmaceutical R&D. Leading experts provide an overview of QC and of the problems and bottlenecks in medicines discovery and development that may be addressed by advances in QC.
To accelerate QC ability to address the needs of life science researchers, Pistoia Alliance, QuPharm and QED-C are partnering to create a community of interest and explore possible projects in the pre-competitive space.
The speakers are:
This webinar presents the Statistics Ontology, STATO which is a semantic framework to support the creation of standardized analysis reports to help with review of results in the form of data matrices. STATO includes a hierarchy of classes and a vocabulary for annotating statistical methods used in life, natural and biomedical sciences investigations, text mining and statistical analyses.
This webinar, supported by Thermo Fisher Scientific, outlines progress on the Pistoia Alliance Lab of the Future Projects and including updates on the Methods Database and the Universal Integration Layer.
Themes and objectives
Mathew Woodwark,Head of Data Infrastructure and Tools, Data Science & AI, AstraZeneca
Erik Schultes, International Science Coordinator, GO-FAIR
Georges Heiter, Founder & CEO, Databiology
The slides can be found here.
It seems that AI is also becoming a buzzword, like design thinking. Everyone is talking about AI or wants to have AI, and sees all the ideas and benefits – that’s fine, but how do you get started? But what’s different now? Three innovations have finally put AI on the fast track: Big Data, with the internet and sensors everywhere; massive computing power, especially through the Cloud; and the development of breakthrough algorithms, so computers can be trained to accomplish more sophisticated tasks on their own with deep learning. If you use new technology, you need to explore and know what’s possible. With design thinking, it aids to outline the steps and define the ways in which you’re going to create the solution. Starting with mapping the customer journey, defining who will be using that service enhanced with intelligent technology, or who will benefit and gain value from it. We discuss how these two worlds are coming together, and how you get started to transform your venture with Artificial Intelligence using Design Thinking.
Speaker: Claudio Mirti, Principal Solution Specialist – Data & AI, Microsoft
Federated Learning (FL) is a learning paradigm that enables collaborative learning without centralizing datasets. In this webinar, NVIDIA present the concept of FL and discuss how it can help overcome some of the barriers seen in the development of AI-based solutions for pharma, genomics and healthcare. Following the presentation, the panel debate on other elements that could drive the adoption of digital approaches more widely and help answer currently intractable science and business questions.
Innovation applications of microphysiological systems (MPS) have been growing over the past decade, especially with respect to the use of complex human tissues for assessing safety of drug candidates – but broad industry adoption of MPS methods has not yet become a reality.
This webinar addresses some recent advances in MPS development and begins to explore the barriers to increased incorporation of MPS to improve drug safety assessment and to provide safer, more effective drugs into the clinical pipeline.
Data for drug discovery and healthcare is often trapped in silos which hampers effective interpretation and reuse. To remedy this, such data needs to be linked both internally and to external sources to make a FAIR data landscape which can power semantic models and knowledge graphs.
The Webinar begins with a tribute to Sir Alasdair Breckenridge, former Chair of the MHRA and Pistoia Alliance Advisory Board Member from
Prof Carl Peck Advisory Board Member, Pistoia Alliance, Chairman, NDA Partners and Former Center Director, CDER, FD
This is followed by updates on key Pistoia Alliance projects; User Experience in Life Sciences, Unified Data Model and the Controlled Substance Compliance Service (CSCS).
Dr Darren Green discusses how data-driven chemoinformatics methods may automate much of what has historically been done by a medicinal chemist, considering what the balance is between AI approaches and human expertise and uses examples from Bradshaw, GSK’s experimental automated design environment to support his presentation.
The slides can be found here:
Webinar presented by the Pistoia Alliance FAIR/OM Community of Interest, hosted by Ian Harrow
Speaker: Matan Burstin, Clarivate Analytics
This presentation reviewed the challenges in identifying, acquiring and utilizing research data in relation to an evolving data market. Strategic solutions were examined in which the FAIR principles play a key role in the future of data management.
Matan’s current role is Director, R&D Data Science and Informatics at Clarivate Analytics. As Data management practice leader, he leads a global multi-disciplinary team of exceptional consultants, servicing the Life sciences industry and providing solutions which combine knowledge management, software development and machine learning.
Matan has 10 years of leadership experience, guiding R&D, engineering, product and operations teams. In his previous roles, he led the data operations department and data products management at a leading global labour market analytics company, managed an R&D team at Boston Children’s Hospital under Computational Health Informatics Program (CHIP) and developed LabCorp’s first Next Generation Sequencing line of clinical products, supporting R&D bioinformatics and informatics.
Speaker: Dr Mark Musen, Stanford University
With the explosion of interest in both enhanced knowledge management and open science, the past few years have seen considerable discussion about making scientific data “FAIR” — findable, accessible, interoperable, and reusable. The problem is that most scientific datasets are not FAIR. When left to their own devices, scientists do an absolutely terrible job creating the metadata that describe the experimental datasets that make their way in online repositories. The lack of standardization makes it extremely difficult for other investigators to locate relevant datasets, to re-analyse them, and to integrate those datasets with other data. The Center for Expanded Data Annotation and Retrieval (CEDAR) has the goal of enhancing the authoring of experimental metadata to make online datasets more useful to the scientific community. The CEDAR work bench for metadata management will be presented in this webinar. CEDAR illustrates the importance of semantic technology to driving open science. It also demonstrates a means for simplifying access to scientific data sets and enhancing the reuse of the data to drive new discoveries.
Dr. Mark Musen is Professor of Biomedical Informatics and of Biomedical Data Science at Stanford University, where he is Director of the Stanford Center for Biomedical Informatics Research. He conducts research related to open science, intelligent systems, computational ontologies, and biomedical decision support. His group developed Protégé, the world’s most widely used technology for building and managing terminologies and ontologies. He has served as principal investigator of the National Center for Biomedical Ontology and of the Center for Expanded Data Annotation and Retrieval (CEDAR).
Ontologies and Semantic Web technologies play an important role in the life sciences to help make data more interoperable and reusable. EMBL-EBI contributes to the development of biomedical ontologies and makes extensive use of them in the annotation of public datasets especially for large-scale data integration efforts. There is an increasing recognition for the role of ontologies in making data Findable, Accessible, Interoperable and Reusable (FAIR).
The ontologies team (https://www.ebi.ac.uk/spot/ontology/) at EMBL-EBI provide a suite of services to make ontologies more accessible for both humans and machines. They work with scientific data curators and software developers to integrate ontologies and semantics into both the data generation and data presentation workflows. They provide:
In this webinar, Dr Henriette Harmse presents how they are using these services at EMBL-EBI to scale up the annotation of data and deliver added value through ontologies and semantics to our users.
Dr Henriette Harmse is a Senior Scientific Programmer leading the software development of the ontology services at EMBL-EBI. She has worked in the IT industry since 1996 as a developer, architect and consultant software architect, where she has provided consulting and auditing services to clients across various industries (financial, healthcare, mining, publishing etc) ranging from detailed code analysis to high-level conceptual architectures. She has a PhD in Artificial Intelligence
Slides from the webinar:
This webinar was presented jointly by the Pistoia Alliance and ELIXIR.
The FAIR (Findable, Accessible, Interoperable and Reusable) principles aim to maximize the discovery and reuse of digital resources. Using recently developed software and metrics to assess FAIRness and supported through an ELIXIR Implementation Study, Michel worked with a subset of ELIXIR Core Data Resources to apply these technologies. In this webinar, he will discuss their approach, findings, and lessons learned towards the understanding and promotion of the FAIR principles.
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research focuses on the development of computational methods for scalable and responsible discovery science. Previously at Stanford University, Dr. Dumontier now leads the interfaculty Institute of Data Science at Maastricht University to develop sociotechnological systems for accelerating scientific discovery, improving human health and well-being, and empowering communities with ethical data-driven decision making. He is a principal investigator in the Dutch National Research Agenda, the European Open Science Cloud, the NCATS Biomedical Data Translator, and the NIH Data Commons Pilots. He is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data
Slides from the webinar:
Blockchain technology can revolutionise the way information is exchanged between parties by bringing an unprecedented level of security and trust to these transactions. The technology is finding its way into multiple use cases but we are yet to see full adoption and real-world business implementation in the Healthcare industry.
In this webinar we explore the main challenges and considerations for the implementation of Blockchain technology in Healthcare use cases. This is the third webinar in our Blockchain Education series.
Our speakers belong to the wide Blockchain community and are responsible for driving innovation in the Life Sciences and Healthcare industries.
Hosted by Richard Norman (Pistoia Alliance)
Slides from the webinar: