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Latest Projects
This latest projects layout as well as the news and main header layouts from the home page design can be used anywhere.
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Project one: Pharma General Ontology
The Pharma General Ontology project will provide a core framework to create interoperability between FAIR data sets across the pharmaceutical industry by identifying preferred vocabularies for community-wide standardization of core concepts.
The pharmaceutical industry faces significant challenges with information management and knowledge transfer throughout its entire range of operations.
Making information more accessible across a business is an overwhelming challenge facing companies, as the information is often fragmented in various silos. This challenge is made even more difficult by the large volumes of information generated, for example by automated R&D processes.
The challenges above are compounded when different pharmaceutical and other enterprises (e.g. CROs) and organizations (e.g. regulatory agencies) need to exchange data.
“FAIR silos”, namely resources complying with the FAIR principles but only meeting interoperability requirements within a given organization and organisational subunit, are emerging.
On the other hand, models and ontologies proliferate. Their diversity limits semantic interoperability, increases costs, creates semantic siloes and slows the path to data centricity in Life-Sciences organizations. Perhaps more critically, there is a lack of controlled definition around entities and the range of terms used to enumerate them. At a minimum, standardization is needed as far as vocabulary for core concepts is concerned.
The Pharmaceutical General Ontology (PGO) goal is to provide a set of public Uniform Resource identifiers (URIs) for key concepts across R&D that can be used throughout the pharmaceutical sector. The overarching goal is to provide a reference set backed by leading pharma companies to facilitate interoperability across companies in the pharmaceutical and life-sciences ecosystem.
The purpose of PGO is to provide a lingua franca for the pharmaceutical sector. This will be achieved by experts designated by the Steering group which will, among others:
- Identify key concepts
- Select public resources that can provide identifiers for each concept.
Future extension could include defining a minimal acceptable profile for each concept and the public vocabularies that can be used. While the whole of the medicinal product development life cycle is ultimately in scope, we will focus initially on R&D during 2024. Creating a sustainability model to ensure the continuity of PGO as a reference data product through the Pistoia Alliance is a vital aspect of the project.
For more information please contact giovanni.nisato@pistoiaalliance.org.
Project two: Clinical Operations Ontology
The landscape of clinical trials is evolving rapidly, with innovations in treatment modalities and personalized medicine. However, this advancement comes with its own set of challenges. The increasing complexity of clinical trials, lack of standardization, and reliance on non-machine-readable data formats hinder the seamless flow of information and integration of cutting-edge AI technologies in clinical trial operations. These challenges lead to inefficiencies, potential for error, and delays in the delivery of critical therapies to patients.
- Complexity: Clinical trials are becoming more intricate due to diverse protocols and endpoints, which can cause operational bottlenecks.
- Lack of Standardization: Disparate processes and documentation styles across trials and organizations lead to inconsistencies and miscommunication.
- Data Format: Essential data is often locked in formats that are not conducive to AI and machine learning technologies, slowing down the potential for insights and advancements.
Hear directly from our Project Manager, and clinical operations expert, Aditya Tyagi about the purpose and intention for this new developing project.
- Efficiency: Minimizing human error with standardized protocols and AI assistance.
- Accuracy: Minimizing human error with standardized protocols and AI assistance.
- Insight:Enabling deeper analytical insights through advanced data processing capabilities.
- Adaptability:Keeping pace with the evolving landscape of clinical research and regulatory requirements.
The ClinOps-O project is not just an upgrade; it’s a necessary evolution in clinical trial operations. By embracing standardization and the power of AI, we can overcome the current operational challenges and pave the way for a future where clinical trials are more efficient, accurate, and insightful. Join us in revolutionizing clinical operations for the betterment of patients and the acceleration of innovative therapies.
The ClinOps-O project is our attempt in response to these challenges. It is designed to transform clinical operations by standardizing the execution of tasks and documenting them in a machine-readable ontology.
- Standardized Task Execution: Establishing unified protocols for common clinical operations tasks, such as operational site feasibility, to facilitate consistency and quality across trials.
- Machine-Readable Ontology: Implementing a structured, machine-readable format for all documentation, enabling the swift and accurate interpretation of data by AI systems.
- AI Integration: Leveraging AI technologies to automate routine tasks, predict outcomes, and enhance decision-making processes.
- Scalability and Flexibility: Designed to accommodate the diversity of clinical trials, from small-scale early-phase studies to large, multi-site phase III trials.
- Compliance and Security: Ensuring that all data handling is in strict adherence to regulatory standards, with robust cybersecurity measures in place.
Our Supporters
Thanks to the companies who are making this community possible, without their help this community would not exist or collaborate.
Project Steering Team
Project Champions
- Merck KGaA: Gernot Weber, Hrvoje Mohoric, Stefan Gilb
- Roche: Marcel Merfort, Cedric Berger
- Novartis: Artur Schaf, Rudi Ager
- Boehringer Ingelheim: Karsten Quast
Project Management
- Aditya Tyagi (PM)
- Thierry Escudier (Portfolio Management)
- Christian Baber (Chief Portfolio Officer)
- Asiyah Yu Lin, Ontologist and Data Scientist
Project Execution
- Crownpoint Technologies
Project three: Pharmaceutical CMC Process Ontology
Our project aims to develop a pharmaceutical (CMC) process ontology, based on the ISA88/95 framework. This ontology will serve to standardize laboratory and plant production process recipes, and in turn, establish standardized definitions. It will also facilitate digital technology transfers, and integrate with execution systems to capture structured process data for material lot genealogy tracking. This will lead to streamlined technology transfers, advanced process analytics, and ultimately, enhance efficiency and transparency throughout the pharmaceutical production lifecycle.
Chemical development has been supported by the ISA 88 standard for decades. A lot has changed in that time, and a more flexible, comprehensive representation of process data is needed. A contemporary ontology provides the data representation that is needed to facilitate data integration, data exchange and data insights.
The Pistoia Alliance has completed Phase 1 / Proof of Concept to build a pharmaceutical CMC process ontology based on the ISA88/95 framework.
The aim is to standardize laboratory and plant production process recipes to establish standardized definitions, facilitate digital technology transfers and integration with execution systems to capture structured process data for material lot genealogy tracking, streamline technology transfers, and advanced process analytics, and thereby enhance efficiency and transparency throughout the pharmaceutical production lifecycle.
For this project’s initial phase, we worked on three use cases: Process Definition, Process Monitoring, and Comparative Analysis. The focus was on the processes for making the APIs and the drug products, initially focusing on biologics and synthetics.
In this video, we show how we have imported the developed core CMC process ontology as well as two controlled vocabularies for referring to the different parameter measurements as well as the different recipe steps that make up a manufacturing process to create a knowledge graph to answer our competency and business questions.
Hear directly from our Project Manager, and ontology expert, Birthe Nielsen and Cameron Gibs from Crown Point, about the “CMC Process Validation Walkthrough” below…
The scope and key deliverables of this work will include:
- CMC laboratory & manufacturing scale API & Pharmaceutical Product processes
- Biologics & Synthetics with an initial focus on protein and chemical processes
- Develop domain lexicon and domain taxonomy to accomplish seamless convergence of the protein and chemical processes
- An advanced semantic architectural design for a Process Ontology, featuring seamless integration with the established Product (IDMP-O), Analytical (AFO), and Unit of Measure (QUDT) ontologies
- A taxonomy and controlled vocabulary based on the ISA88/95 framework for Process/Stage /Operation/Action, Process Parameters, Process Performance Indicators, and their definitions
Initially, we will work to cover the following use cases:
- Standardize and digitize laboratory production process (stage) definitions, enabling structured process data capture.
- Establish digital API & Pharmaceutical Product process definitions for automated CMC dossier authoring
- Enable digital Process Technology Transfer from laboratory to plant (scale up) and between plants
- Enable advanced process analytics (process performance) across laboratory and process batches (across scale)
Here is some text – you can add text underneath categories, just the same as pages. You can also add images as normal.
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There are also spacers that can be added so you can add a space between elements. Under this text, there is a spacer of 16px.
The links above are supposed to be used with the coloured circle/image links but they can be used on their own too.
You can use tables as shown below.
| Amplify Value of R&D |
| Collaborate with R&D Peers |
| Influence and innovate |
| Initiate cross-company workstreams |
| Cost savings through shared investment |
| Create consensus-based, x-company requirements for key vendors |
| Attend Member-only Meetings and networking events |
| Run for a seat on the Pistoia Alliance board |
| Set Pistoia Alliance direction and control the project portfolio |
| Use PA outreach to demonstrate industry leadership |
| Join project specification workgroups & project teams |
The area below is an example of the coloured circle/image links. These are quite versatile for calls-to-action. Be aware that if you are using a circular image, it will need a link to be added below it.
