Cambridge Healthtech Institute’s 22nd Annual
Bio-IT World Conference & Expo
May 16-18, 2023
Do you have a novel and innovative talk for the 22nd Annual Bio-IT World Conference & Expo taking place May 16-18, 2023, in Boston, MA? We would love to hear from you!
We have over 190 speaking slots to fill. We are seeking speakers from the life sciences who want to present their latest research and work via best practice case studies or joint partner presentations that discuss relevant themes including but not limited
to data ecosystems, big data, smart data, cloud computing, trends in IT infrastructure, -omics technologies, high-performance computing, data analytics, precision medicine, AI/machine learning from the research realm to the clinical arena, FAIR Data,
data mesh/data fabric, Lab of the Future, digital health, and more!
Since its debut in 2002, the annual Bio-IT World Conference & Expo has established itself as a premier event showcasing the myriad of IT and informatics applications and enabling technologies that drive biomedical research, drug discovery
& development, and clinical and healthcare initiatives. The Bio-IT World Conference & Expo continues to be a vibrant event that unites 2,500+ life sciences, pharmaceutical, clinical, healthcare, and IT professionals from 30+
Spanning three days, the 2023 meeting taking place May 16-18 in Boston, MA, includes 9 pre-conference workshops, the FAIR Data Symposium, the Knowledge Graphs Symposium, and 12 parallel conference tracks. We have kept many of our flagship tracks as well
as launched new ones that we are excited about! Showcase your research and work at this influential meeting to be seen as an industry expert while helping your colleagues and peers stay abreast of important updates and advances in the field.
SYMPOSIA (Tuesday, May 16)
Symposium 1: FAIR Data
Strengthen Health Outcomes with More Findable, Accessible, Interoperable, and Reusable Data
The volume of life science data, particularly genomic data, continues to rise exponentially, but the capacity for fully making use of this data is often hindered. FAIR is a powerful initiative that has the potential to significantly increase the value
of genomic data sets. Bringing together academic, government, and commercial end-users who are pioneering the use of FAIR data, the FAIR Data Symposium will highlight FAIR applications in software, data repositories, and specific
data types both open source and private. Presentations will discuss FAIR principles and definitions, technology tools and tool differences, as well as application/use cases.
Symposium 2: Knowledge Graphs
Drive Discovery and Innovation with Next-Generation Context and Experience Graphs
Due to their power and versatility, knowledge graphs are being adopted by the pharmaceutical industry to accelerate data science and AI-driven drug discovery at a rapid pace. These graphs enable knowledge sharing by establishing an integration point across
multiple data types and sources. The data shared is then converted to knowledge and a mechanism is built to extract that knowledge in a manner that is both traceable and timely. At the Knowledge Graphs Symposium, you will hear firsthand
how pharma companies are taking on the task of building their own knowledge graphs internally as well as leveraging outside partners to implement them. Presentations will feature how these knowledge graphs show real impact across pharma research and
TRACKS (Wednesday, May 17 – Thursday, May 18)
Track 1: Modern Data Platforms and Storage Infrastructure
Architect, Implement, and Manage Data Storage Solutions that Maximize Speed, Performance, and Cost
Is the burden of managing your data growing larger every day? Do you have a scalable and robust data management infrastructure in place to store, process, analyze, transfer, and secure vast quantities of data according to your organization’s policies?
Do you know how to achieve availability vs interoperability? What are approaches to scalable distributed/federated data analytics? What conversations are you having about speed vs performance vs cost? Which vendors should you use? How do you evaluate
strengths and weaknesses of technology solutions? What data storage and types are efficient? Tremendous efforts and advancements have been made by organizations who have pioneered advances in large-scale data management related to storage platforms,
integration and migration plans, and governance. The Modern Data Platforms and Storage Infrastructure track will explore these questions and share best practices of these efforts.
Track 2: Data Management
Manage Data to Create Value
With the increased demand in computing power from life science researchers and scientists tackling big data issues, data storage infrastructure must be able to scale to handle billions of data points and files efficiently. The problem is administration
of data to ensure information can be integrated, accessed, shared, linked, analyzed, and maintained to effect change across the organization. Are data mesh and data fabric really the answer? How do you make sense of data and its content to create
value? The Data Management track will explore these questions and other themes related to FAIR data, data reuse/governance/literacy, data federation, and standards/data curation/harmonization.
Track 3: Data Science and Analytics Technologies
Best Practice Methods for Large-Scale Data to Advance Biomedical Research
The Data Science and Analytics Technologies track will explore data science and analytics tools, technologies, and languages that data scientists are using to gain extra insights and value from data. Presentations will explore the importance
of scalable platforms vs individual data science support, becoming a data-driven organization, innovative approaches to data management and analytics, understanding real questions that need to be answered, making real impact with data science, and
applying data science and tools.
Track 4: Software Applications and Services
Develop Stable Software Application Architecture to Add Value to All Ecosystem Stakeholders
The Software Applications and Services track explores how biopharma companies are driving data strategies and scientific decision-making by optimizing release management, automated testing, and leveraging software architecture tools and
development trends. As life sciences and healthcare evolves, so will apps and services. What tools are available for developing apps and services? How much personalized software development for an individual company is useful/needed? Software serves
as a foundation for innovation. The more stable the software application architecture is, the more it can add value to an ecosystem of stakeholders. Case studies will be presented on software tools to facilitate data manipulation, data analytics approaches,
data methods and standards approaches, transparency, efficiency, security, and cost-effective solutions.
Track 5: Cloud Computing
Enable Collaboration and Drive Better, Faster Analytics Using Cloud Infrastructure and Applications
There is no longer any question -- adoption and deployment of cloud technologies is no longer an aspiration but a necessary mandate to enable digital transformation. There is simply no other way to store, manage, analyze, and share the massive amounts
of data being collected to drive advancements in precision medicine. However, there are countless choices that must be made to determine the best path for your organization. Through case studies and best practices, the Cloud Computing track explores options and provides guidance on how best to determine the right cloud or hybrid infrastructure and applications to advance R&D, enable collaboration and innovation, and support flexibility to stay abreast of technological advances
driving precision medicine.
Track 6: AI for Drug Discovery and Development
Harness the Power of Artificial Intelligence and Machine Learning to Maximize and Accelerate Drug Discovery and Development Pipeline Efforts
The AI for Drug Discovery and Development track will discuss opportunities and challenges that biopharma organizations are experiencing in harnessing the power of artificial intelligence and machine learning technologies to maximize and
accelerate drug discovery and development efforts from early-stage to adoption to practical application. Speakers will explore the role of AI in transforming disease understanding and target ID, approaches using AI and human expertise to help identify
and deliver validated targets, as well as enhancements to chemical drug design and precision medicine. We will also explore how AI/ML efforts compare to tried-and-true successful discovery (drugs-to-market) methods.
Track 7: AI for Oncology, Precision Medicine, and Health
New and Emerging Data Tools that Enable AI
The AI for Oncology, Precision Medicine, and Health track will discuss technology tools that enable artificial intelligence for oncology, precision medicine, and health. First, how do you define the complexity of the problem before applying
technology tools? What data is available for doing any of this well? What are the technology tools, including emerging “new and exciting” ones, to consider? Speakers will present focused use cases that discuss all of these questions that
help leverage information to identify translation efforts from research to clinical.
Track 8: Bioinformatics
Leverage Computational Tools and Methods to Turn Big Data into Smart Data to Advance Pharma R&D
The Bioinformatics track assembles thought leaders who will present case studies using computational resources and tools that take multimodal data analyses across genomics, transcriptomics, proteomics, metabolomics, and other data types
(e.g., imaging), and align it with clinical action. Turning big data into smart data can lead to real-time assistance in disease prevention, prognosis, diagnostics, and therapeutics. With the ever-increasing volume of information generated for curing
or treating diseases and cancers, bioinformatics technologies, tools, and techniques play a critical role in turning data into actionable knowledge to meet unstated and unmet medical needs. Other themes we will explore include new methods of single-cell
data analysis, how bioinformatics can leverage tools/methods from data science and AI to advance research, and deep learning approaches to help with applications of bioinformatics to pharma R&D.
Track 9: Pharmaceutical R&D Informatics
Drive Precision Medicine through the Digitalization of Pharma R&D
The urgency surrounding generating, organizing, and analyzing data in the pharmaceutical industry has not waned. In fact, the desire to develop new technologies and speed development of infrastructure and special projects in our new normal continues to
grow at record speed. The Pharmaceutical R&D Informatics track will explore key challenges and solutions around developing and scaling infrastructure, redefining knowledge management, organizing data generated via new technologies
and services, and creating an effective and efficient informatics ecosystem while meeting scientific, business, and regulatory demands. We’ll explore the continued role FAIR data has in successful projects, strategies around developing analytics
and visualization tools, and novel approaches utilizing AI, NLP, deep learning, and machine learning, and how these initiatives are driving innovation in R&D.
Track 10: Digital Biopharma
Infrastructure, Processes, and Analytics to Support Digitization of Biologics R&D
The continued growth in volume, complexity, and variety of new modalities, including next-generation antibodies, cell and gene therapies, and vaccines, as well as the need to integrate data management and collaboration across discovery and into development
requires a digital infrastructure effectively collect, manage, model, and analyze data. The Digital Biopharma track explores the latest advances in data management and analytics used to increase process efficiency and quality and
to identify the most promising drug candidates to quickly move forward from research into development.
Track 11: Automation, Digital Lab, and Robotics
Design the Lab of the Future
The Automation, Digital Lab, and Robotics track will explore the Lab of the Future. Speakers will share best practices of physical lab automation (devices/device integration) and data automation, data workflows, and pipelines. Other themes
that will be covered include standards for interoperability, vendors, and trends, and how this is all coming together for the Lab of the Future, and proper data management techniques to make FAIR possible.
Track 12: Digitization of Clinical Development and Clinical Trials
Tools and Technologies to Collect and Transform Raw Data into Actionable Insights to Accelerate and Improve Clinical Outcomes
Advancing clinical research and translational research requires transforming raw research data and biological insights into clean, actionable data for integration, visualization, and analysis. The Digitization of Clinical Development and Clinical Trials track explores new and innovative tools and techniques, including digital health technologies, data capture and data analytics, machine learning, and artificial intelligence. Explore how they can be leveraged to address specific challenges faced across
the drug discovery spectrum to accelerate the translation of scientific discoveries from the bench to medical care. Gain practical recommendations and real-world insights from case studies across pharma and academia.
If you would like to submit a proposal to give a presentation at this meeting, please click here.
The deadline for priority consideration is October 21, 2022.
All proposals are subject to review by the Scientific Advisory Committee to ensure the overall quality of the conference program. In your proposal submission, please indicate names and/or organizations of all speakers you intend to participate in the final presentation. Additionally, as per Cambridge Healthtech Institute policy, a select number of vendors and consultants who provide products and services will be offered opportunities for podium presentation slots based on a variety of Corporate Sponsorships.