DIA 2024 Global Annual Meeting

Component Type: Forum

Join our opening plenary session, Innovation: The Possibilities, The Boundaries: Charting New Horizons, led by Tom and Emily Whitehead, who will give the incredible journey of Emily Whitehead, the pioneering pediatric patient who defied the odds and became the first in the world to undergo CAR T-cell therapy. Tom and Emily will share their invaluable insights into the transformative power of CAR-T therapy, offering a unique perspective that promises to captivate and inspire. Dean Kamen will discuss the Future of Regenerative Therapies, How Public-Private Partnerships Can Impact Advancement. Following your keynotes, we will have a panel discussion. Attendees can expect a lively and engaging discussion, with a diverse range of perspectives and insights from panelists who are leaders and at the forefront of our industry; including panelists from the Gates Foundation, regulatory agencies, and the patient perspective.

Chair

Marwan Fathallah, MBA, MSc

Speaker

Developing Cell Therapies for Cancer Patients
Carsten Linnermann, PhD

Keynote Speaker: Insights into the Transformative Power of CAR-T Therapy
Tom Whitehead

Keynote Speaker: Insights into the Transformative Power of CAR-T Therapy
Emily Whitehead

Keynote Speaker: Future of Regenerative Therapies - How Public-Private Partnerships Can Impact Advancement
Dean Kamen

Plenary Panel: Innovation - The Possibilities, the Boundaries - Charting New Horizons
David Mukanga, PhD, MPH

Panelist: Innovation
Dean Kamen

Panelist: EMA Perspective
Emer Cooke, MBA, MSc

Panelist: FDA Perspective
Peter W. Marks, MD, PhD

Panelist: Patient Perspective
Stacy Hurt, MBA, MHA

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-520-L04-P; CME 1.00; RN 1.00

The past decade has seen significant strides in machine learning and AI technologies. This session will provide an in depth investigate the various uses of machine learning and AI-based simulations within clinical development, ranging from data analysis, endpoint selection, the potential improvement of decision making within trial teams by clarifying tradeoffs to clinicians and statisticians, and more.

Learning Objectives

Describe the potential benefits of simulations in clinical trial protocol development and trial analysis, and the benefits of employing machine learning tools throughout clinical development; Discuss the novel approaches to conducting studies with such tools incorporated and relate to the regulatory guidance for adaptive trial design where relevant.

Chair

Raviv Pryluk, PhD

Speaker

Doing More with Less: Using ML to Drastically Improve Trial Simulation and Design
Raviv Pryluk, PhD

Clinical Trial Simulation: the Antidote to Wishful Thinking
Sam Miller, MSc

Digital Twins for Clinical Trials
Charles Fisher, PhD

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-529-L04-P; CME 1.00; RN 1.00

Artificial Intelligence (AI) is making its presence known in health care, presenting unprecedented opportunities and challenges. It is crucial to devise strategies that ensure its ethical and responsible utilization for the betterment of health care and society. This imperative can only be met by harnessing the collective power of the broad Healthcare ecosystem. Join us for an engaging DIAmond session featuring esteemed panelists from technology companies, pharmaceuticals, patient advocacy groups, and academia/research to delve into how we can leverage the momentum of AI while establishing a foundation of trust. In this session, we will address the following questions: • How is the health care data landscape evolving in conjunction with AI, and what implications does it hold in terms of opportunities and concerns for our stakeholders? • What expectations do stakeholders have of us as leaders in ensuring ethical innovation? • What emerging practices, supported by real examples and lessons learned, are paving the way for the integration of ethical considerations into actionable strategies? • Where should we seek cross-sector partnerships to further propel momentum and establish standards for the ethical and responsible deployment of AI? Let us unite in paving the way towards a future where innovation is fueled by trust, driven by the responsible utilization of our burgeoning capabilities.

Learning Objectives

Define responsible innovation and ethical use of artificial intelligence (AI) in health care and life sciences; Explore the intersection of ethical considerations with technological advancements; Examine the role of cross-sector partnerships in driving trusted and responsible AI use.

Chair

Martin Hodosi, MSc

Speaker

Panelist
Junaid Bajwa, MD, MBA, MSc, FRCP

Panelist
Karla Childers, MS

Panelist
Dave deBronkart

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-534-L04-P; CME 1.00; RN 1.00

The explosion of technology and expectations for its use are transforming medical writing. In addition to articulating their value proposition, writers and their managers will have to adapt to this transformation and level-up their skills, in the face of ever-evolving technology and technical challenges. This panel will focus on providing both strategic and tactical considerations for medical writing teams. We will highlight the importance of finding early adopters, developing training for multiple learning styles, building a support network, and surviving the change management process.

Learning Objectives

Discuss how the medical writing role is evolving in the face of technology; Outline the new skillset(s) that medical writers will need and how these change the value proposition of medical writing; Discuss strategies for engaging and training teams through this evolution.

Chair

Robin Whitsell

Speaker

Industry Update
Joanne Hilton, PhD, MBA

Industry Update
Kayla Williams

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-539-L04-P; CME 1.00; RN 1.00

Explore US and EU AI drug regulation with experts from regulator, industry, and academic perspectives. Learn about principles, data privacy, transparency, and real-world examples. Gain insights into vital regulatory nuances.

Learning Objectives

Describe the regulatory frameworks in the US and EU; Discuss the practical necessity of regulation in various AI-driven drug development scenarios.

Chair

Jayne Ware, MPH, MSc

Speaker

EMA Update
Steffen Thirstrup, MD, PhD

FDA Update
Tala Fakhouri, PhD, MPH

Industry Perspective
Rose Purcell, JD, MA

Component Type: Session
Level: Advanced
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-552-L04-P; CME 1.00; RN 1.00

Regulatory intelligence is the key to formulating regulatory strategy. We will share the application of AI and critical thinking in developing science and risk-based strategies for the development and lifecycle management of medicinal product.

Learning Objectives

Apply skills learned in this session to set up regulatory intelligence frameworks for their team and/or company; Develop critical thinking skills that are imperative to the interpretation and proper utilization of intelligence data; Identify how to setup and manage tools and processes for surveilling and monitoring regulatory changes.

Chair

Ana Sengupta, MBA, MS, RAC

Speaker

Designing Regulatory Intelligence Framework: Powered by Critical Thinking
Ana Sengupta, MBA, MS, RAC

Designing Regulatory Intelligence Framework: Powered by Artificial Intelligence
Susan Carino, MBA, MS, PMP, RAC

Designing Regulatory Intelligence Framework: Powered by Artificial Intelligence
Aditi Khurana, MBA, PMP, RAC

Component Type: Workshop
Level: Basic

Join our beginner-friendly Chat GPT workshop! Designed to provide both an overview and hands-on experience, this session will delve into the fundamentals of ChatGPT technology. From understanding its underlying principles to practical applications, participants will gain insight into AI-driven conversations. Through interactive demonstrations and guided exercises, attendees will get firsthand experience in leveraging ChatGPT's capabilities. Whether you're new to AI or seeking practical insights, this session promises to equip you with valuable knowledge and skills

Learning Objectives

Describe the basics of artificial intelligence, large language models, and ChatGPT; Identify with using hands-on experience by interacting with ChatGPT through guided exercises; Discuss best practices for interacting with the technology as well get an overview of ethical considerations and potential limitations of ChatGPT technology; Assess the impact its already creating in pharma R&D, and what are the use cases that you can get started with.

Chair

Ankush Chandna, MSc

Speaker

Facilitator
Anjali Shah, PharmD

Facilitator
Ankush Chandna, MSc

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-576-L04-P; CME 1.00; RN 1.00

This session will describe and identify emerging technology innovations and health authority papers, guidance, and discussion on their use in regulatory filings and development. The session will discuss emerging artificial intelligence (AI) trends, structured content authoring, and structured data including their development, use, risks, and potential future in pharmaceutical development. Attendees will hear from industry experts on the topics and their potential implementation and impacts to the field.

Learning Objectives

Describe and identify emerging technology innovations and health authority papers, guidance, and discussion on their use in regulatory filings and development; Discuss emerging artificial intelligence (AI) trends, structured content authoring, and structured data including their development, use, risks, and potential future in pharmaceutical development; Describe potential implementation and impacts to the field.

Chair

David Meats

Speaker

AI and Technology Trends and Regulation Introduction
David Meats

Regulation Guidance and Concensus Papers
Madhavi Gidh-Jain, PhD

Regulation Guidance
Louise Lind Skov, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-586-L04-P; CME 1.00; RN 1.00

This session will provide perspectives from stakeholders on successes and limitations from practical examples and discuss principles and best practices for maximizing the potential while managing the risks moving forward.

Learning Objectives

Describe the current state of the use of artificial intelligence (AI) in the medicinal product lifecycle including its opportunities and challenges; Discuss principles and best practices to maximize potential of AI while managing risks.

Chair

Hilmar Hamann, PhD

Speaker

EMA Update
Lorenzo De Angelis, PhD

Industry Update
Carlyn Crisostomo, MBA

Industry Update
Alexandra (Zan) Cha, PhD, MA

Industry Update
Timothe Menard, PharmD, MSc

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Application UAN: 0286-0000-24-602-L04-P; CME 1.00; PDU 1.00 PMI 2166XALVLX; RN 1.00

Many project management methodologies, alternative thinking approach and new technologies can be applied to life science project management and bring many benefits. In this session, the adoption of Design Thinking and Generative AI, two of the emerging topics in health care industry, into life science project management will be discussed. The session will also demonstrate, with case studies, the possibilities of implementing new thinking approach for effective project management, team leading and efficient business process development. We will also examine practical applications of Generative AI in project management from optimizing scheduling, resource planning, and risk management. Reflecting on the current adoption efforts, this session provides a platform to explore possibilities to leverage new thinking and technologies to enhance life science project management.

Learning Objectives

Critique how many project management methodologies, thinking approaches, and new technologies can be applied to life science projects, and they may bring various benefits into the practice; Implement applicable methodologies and protocol new technologies in real-world practice.

Chair

Char Leung

Speaker

Industry Update
Rune Bergendorff, MSc

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-625-L04-P; CME 1.00; RN 1.00

This discussion will dive into large language models (LLMs) impact on healthcare, their integration with digital health technology, and ethical/regulatory implications.

Learning Objectives

Describe how digital health technologies (DHTs) and generative artificial intelliegence (AI), including large language models (LLMs) are applied to healthcare context; Examine the various integration points between LLMs and DHT and discover how these technologies can work synergistically to revolutionize patient care, telemedicine, remote, and disease progression.

Chair

Jagdeep Podichetty, PhD, MS

Speaker

Panelist
Qi Liu, PhD

Panelist
Jie Shen, PhD, MBA

Panelist
Sakshi Sardar, PhD

Panelist
Emily Lewis, MS

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-633-L04-P; CME 1.00; RN 1.00

This forum session will explore the transformative potential of Artificial Intelligence (AI) in biotech RA CMC and advanced manufacturing. Discover how AI can optimize processes, improve efficiency, and ensure compliance of your data.

Learning Objectives

Define key concepts and principles of artificial intelligence (AI) in the context of biotech industry, regulatory CMC and advanced manufacturing; Identify the potential applications and benefits of AI including how it can automate deviation and change control processes or support strategic decision-making; Discuss the benefits, challenges and cons of AI i.e. data integrity and security.

Chair

Grzegorz (Greg) Podrygajlo, PhD

Speaker

Application of AI Tools to Support the Decision Process in Regulatory CMC
Grzegorz (Greg) Podrygajlo, PhD

Use of AI and ML in Pharmaceutical Manufacturing: Case Studies from the Shop Floor and Regulatory Landscape
Gert Thurau, DrSc, PhD

How to Use GenAI in a Smart Way for Now and for the Future
Hubert Niewiadomski, PhD

Component Type: Session
Level: Basic
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-638-L04-P; CME 1.00; RN 1.00

Join us for a candid tour of three journeys toward integrating AI into key use cases. We share real-world metrics, best practices, and lessons learned as our teams evolve from traditional document development to effective digital solutions. This session focuses on practical ways in which medical writing organizations are using AI technologies to enable new ways of working, achieve business value, and get drugs to market faster.

Learning Objectives

Compare approaches to incorporating artificial intelligence (AI) in key use cases; Identify potential solutions to challenges within your organization; Appraise your organization’s plans for AI implementation.

Chair

Regina Lynn Preciado

Speaker

Evolution of Technology and Exploring Use of Generative AI in Medical Writing
Madhavi Gidh-Jain, PhD

Using GenAI to Write First Draft of Clinical Study Reports
John Henry April, III, MA

Evolve or Perish: Embracing Automation in Medical Writing
Waheed Jowiya, PhD

Component Type: Session
Level: Advanced
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-639-L04-P; CME 1.00; RN 1.00

Generative AI is gaining traction in trial communications, with goals of expediency and efficiency. New technologies should incorporate patient views and ethical frameworks to keep human interactions that are desirable, necessary, and useful.

Learning Objectives

Describe the ethical framework that encompasses informed consent for clinical research; Evaluate goals for the use of artificial intelligence (AI) in clinical trials and how these goals interact with ethical goals for consent; Discuss how to incorporate patient and participant needs and perspective into AI-assisted clinical trial information and communication.

Chair

Lindsay McNair, MD, MPH, MS

Speaker

Patient Perspective Update
Deborah Collyar

Industry Update
Karla Childers, MS

Industry Update
Catina O'Leary, PhD

Component Type: Session
Level: Basic
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-654-L04-P; CME 1.00; RN 1.00

This session explores four use cases of AI's potential to revolutionize quality management (QM) decision making and enhance organizational processes. Discover how AI is being implemented within QM and AI's role in identifying trends and driving improvement initiatives.

Learning Objectives

Describe the role of AI for quality management (QM) decision making, with a focus on advanced data analysis and pattern recognition, quality risk management, inspection readiness and drive continuous improvement initiatives; Identify practical use cases of AI in enterprise QMS, metadata extraction, risk assessment, and knowledge management systems, showcasing the benefits of AI integration.

Chair

Oliver Fink, MS

Speaker

AI Embedded Capabilities in an Enterprise Quality Management System
Michael Pelosi, MA, MBA, MSc

Augmenting Quality Assurance Activities with AI
Oeystein Kjoersvik, MS, MSc

AI Use Cases in Regulatory Monitoring
Haleh Valian, PhD

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Application UAN: 0286-0000-24-655-L04-P; CME 1.00; RN 1.00

This will be an interactive panel discussion with experts sharing examples how AI/ML can be used to create solutions for better regulatory decision-making and predicting regulatory success. Risks and benefits of using this approach will be discussed.

Panelists will include world-renowned experts on drug development, drug regulations, decision science and data analytics.

Learning Objectives

Evaluate how AI/ML can be used to help with regulatory decision making; Analyze scenarios using case studies by world’s leading expert on drug development, cloud computing, and predicting regulatory success; Compare risks and benefits for using this evolving technology.

Chair

Romi Singh, PhD

Speaker

Panelist
Kilian Weiss

Panelist
Subha Madhavan, PhD, FACMI

Panelist
Lily Li, JD

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-650-L04-P; CME 1.00; RN 1.00

This panel will discuss opportunities and challenges of leveraging artificial intelligence (AI) in the drug development lifecycle, especially in regulatory operations. The panel will include representation from regulatory, and industry.

Learning Objectives

Identify the impact of artificial intelligence (AI) in the drug development lifecycle from health authorities' and, industry's perspectives; Recognize opportunities for the regulators and industry to leverage rapid advancement of AI to the drug development lifecycle; Discuss challenges to implement changes from policy, technology, standard, data security in regulatory operations.

Chair

Ethan Chen, MBA, MS, PMP

Speaker

The Evolving Role of Artificial Intelligence in the Medicinal Product Lifecycle
Hilmar Hamann, PhD

Panelist
Tala Fakhouri, PhD, MPH

Panelist
Nicole Mahoney, PhD

Component Type: Forum
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-662-L04-P; CME 1.00; RN 1.00

In this interactive forum, panelists share how they are working across R&D to improve processes and data flows, govern their data, move toward more data-driven processes, and facilitate the use of artificial intelligence (AI) and advanced technologies.

Learning Objectives

Identify how sponsor companies are optimizing their business processes and getting more value from their data across R&D; Discuss approaches for process optimization, data governance and standardization; Describe ways to move towards data-driven business processes and how to enable greater automation and business efficiency across product development.

Chair

Cary Smithson, MBA

Speaker

Panelist
Linda Chong, MBA

Panelist
Rayna Venook, PhD

Component Type: Session
Level: Basic
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-660-L04-P; CME 1.00; RN 1.00

Unlocking AI's potential to facilitate diversity in clinical trials demands inclusive images capturing skin manifestations of internal diseases across races and ethnicities. Join our panel to learn more about inclusive innovation in AI solutions.

Learning Objectives

Discuss the importance of photographs and images in AI algorithms to identify internal diseases impacting patients of color and how that supports clinical trial enrollment; Identify the questions to ask of AI solution providers to ensure imagery is inclusive; Describe what’s being done to improve imagery in AI learning to drive clinical trial diversity.

Chair

Pamela Simpkins, MBA

Speaker

Patient Update
Tricha Shivas, MS

Industry Update
Lionel Phillips, MBA

Industry Update
Brian H Johnson

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-668-L04-P; CME 1.00; RN 1.00

This session discusses usage of a variety of artificial intelligence (AI) solutions (knowledge-based expert systems, generative AI, machine learning) across the clinical research lifecycle from drug discovery to patient recruitment, data quality management, and submission. We will go over specific problems that lend themselves to AI and how we go about building scalable solutions with emphasis on explainability, reliability, and validity.

Learning Objectives

Discuss the use of generative artificial intelligence (AI) and machine learning in clinical research and measures taken to insure validity and reliability; Describe the role of knowledge graph (KG) in building AI systems.

Chair

Katy Ghantous, PhD, MS

Speaker

Industry Update
John Overington

Industry Update
Joe Mullen, PhD, MS

Academic Update
Ramona Lynn Walls, PhD

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-669-L04-P; CME 1.00; RN 1.00

Artificial intelligence solutions may support and enhance human decision-making and information processing throughout pharmacovigilance. This session aims to outline best practices and potential pitfalls in their use.

Learning Objectives

Recognize key challenges in assessing artificial intelligence solutions and interpreting evaluations of their performance; Describe some best practices for critical appraisal of artificial intelligence solutions; Identify the need for consideration of human computer interactions.

Chair

Jim Barrett, PhD, MSc

Speaker

MHRA Update
Phil Tregunno

FDA Update
Monica Munoz, PharmD, PhD

Industry Update
Andrew Bate, PhD, MA

Component Type: Session
Level: Advanced
CE: ACPE 1.00 Knowledge UAN: 0286-0000-24-686-L04-P; CME 1.00; RN 1.00

This session will discuss use of generative AI to transform clinical data operations across the clinical trials lifecycle across use cases such as integration, summarization, translation, content generation, and knowledge extraction. The use of generative AI will be discussed for applications such as smart data review and edit checks, workflow automation, and real-time data transformation.

Learning Objectives

Discuss the challenges associated with existing clinical data platforms; Identify specific uses cases where such challenges exist in study startup, study conduct, and study closeouts; Describe how generative AI will transform the clinical data platform to operate seamlessly driving faster patient recruitment and efficient site selection or trial conduct.

Chair

Lichen Shen

Speaker

Creating Production Grade (Gen)AI-Powered Software for Clinical Trials
Lichen Shen

Industry Update
Sharmin Nasrullah, MS