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Impact of Generative AI on Medical Affairs

– A POV from the Medical Affairs Digital Strategy Council

Executive Summary

The integration of Generative AI (GenAI) into everyday life science industry practices signifies a pivotal transformation, heralding a new era of efficiency, effectiveness and innovation-driven competitive edge. For Medical Affairs, the extraordinary level of functional efficiency that is possible through GenAI will allow for unprecedented redeployment of resources to strategic pursuits which in turn will be made more insightful and effective by GenAI.

This white paper, the first of a series focused on Medical Affairs and GenAI, examines the expansive potential of this technology across multiple activities, including data collection and analysis, insight generation, content creation, HCP engagement and performance evaluation. Drawing upon a comprehensive roundtable discussion at the Medical Affairs Digital Strategy Council, this document outlines the many opportunities, challenges, and prospective directions for the successful application of GenAI within Medical Affairs.

GenAI's deployment in Medical Affairs can be revolutionary. It represents the most sophisticated tool ever available for strategic decision-making and tactical design. GenAI use by Medical Affairs will be broad and deep and this vast potential represents a challenge in itself. Prioritization and focus will be key. Multiple use cases exist to achieve each of the fundamental goals of efficiency, effectiveness and innovation. Outcomes will range from more compelling content strategy, to more efficient and strategic field medical team utilization and development of a Medical Information response ecosystem and experience that transcends SRDs. Resources will be freed up by technology capable of the medical review of complex materials and the discovery of trends that have been hidden in large datasets. Utilization of GenAI across these broad use cases demonstrate its capacity to significantly reduce time and resource expenditures in almost every Medical Affairs activity. GenAI's ability to parse extensive clinical and patient-level datasets and social media discourse will equip Medical Affairs teams with a far more nuanced understanding of patient needs, HCP perspectives, and healthcare dynamics. Moreover, the application of GenAI in evaluating data produced by Medical Affairs activities will transform our ability to assess performance and make real-time adjustments in strategy and tactics. We will have the luxury and burden of working at unprecedented speed. As one Council member remarked, 'we can get an answer at the point of a question.'

The journey toward the full integration of GenAI in healthcare is laden with challenges. Chief among these are concerns regarding data privacy, ethical considerations, and the imperative for robust regulatory frameworks. Additionally, the rapid evolution of technology necessitates ongoing education and adaptation by healthcare professionals to remain abreast of new capabilities and applications.

In anticipation of the future, GenAI holds immense promise, yet realizing this potential demands a concerted effort among Medical Affairs teams, regulatory bodies, and patients to ensure that GenAI's integration into the industry and the healthcare community is conducted ethically, effectively, and equitably.

As we stand on the brink of this new era, we must navigate its challenges with foresight, ensuring that GenAI serves as a tool for good, augmenting human capabilities and improving health outcomes for all.

Introduction

The Medical Affairs Digital Strategy Council is comprised of 20 Medical Affairs leaders from a diverse set of biopharmaceutical companies with varying worldwide remits. The Medical Council was formed in 2019 to bring together leaders from the industry to connect, collaborate, and learn from each other and propel Medical Affairs towards a digital future.

The focus is to help Medical Affairs organizations embrace technology and innovation through a digital and data-driven model to further unlock growth and maximize impact across internal and external engagements.

The rapid advancements in AI technologies, (more advanced models are being introduced every week), with some specifically designed for healthcare application, and the need to consider how they best fit in Medical Affairs has raised this as an urgent opportunity for the Council to consider. These technologies promise to enhance productivity, streamline operations, and foster innovation. However, their integration into the highly regulated pharma industry necessitates careful consideration of capabilities of the latest AI models, internal capabilities, and infrastructure to address ethical, privacy, and compliance issues.

Where can GenAI improve Medical Affair's Impact?

The continuous release of improved AI models has created a challenge of abundance for Medical Affairs as potential use cases grow in number rapidly.

GenAI's application in Medical Affairs can span across multiple areas and functions:

Content Creation and Dissemination

GenAI revolutionizes the ideation, creation and distribution of content. It can generate an accurate, up-to-date first draft of medical information content in a fraction of time, streamlining content dissemination across multiple platforms and channels, ensuring that healthcare professionals and patients have rapid access to the latest research findings and treatment guidelines.

Stakeholder Engagement and Communication

GenAI-informed communication and engagement strategies can better meet the specific needs of various stakeholders, including patients, healthcare providers, and regulatory bodies. This personalized approach ensures more effective interactions and strengthens relationships within the healthcare ecosystem.

MLR Review Processes

GenAI can enable Medical, Legal, and Regulatory (MLR) review processes, significantly speeding up the review of content, leading to faster content delivery to healthcare professionals and patients.

Customer Data Platforms

By integrating GenAI with various data platforms, organizations can achieve deeper understanding of Key Opinion Leader (KOL) relationships, clinician education preferences and consumer health information seeking dynamics. GenAI's ability to analyze vast datasets enables more personalized and effective engagement strategies, enhancing relationship management with critical stakeholders.

Workflow Integration

Embedding GenAI tools into existing IT systems can significantly enhance productivity and decision-making. GenAI can automate routine tasks, and optimize operational workflows, freeing up Medical Affairs teams to focus on more strategic work.

Training and Education

Developing GenAI-driven simulations and training programs for Field Medical and internal teams. These tools can simulate real-life scenarios, enhancing learning outcomes and clinical skills.

Evidence Generation

GenAI can assist in evidence generation by helping evaluate large volumes of real world data and identifying trends and gaps leading to more effective messages and communication tactics.

By embracing these GenAI applications, Medical Affairs organizations can drive innovation, improve efficiency, and deliver better outcomes for patients and healthcare providers alike.

The Council emphasizes the importance of defining specific and meaningful use cases as the starting point for any GenAI implementation project.

Challenges and Roadblocks

Maximizing the potential of GenAI in Medical Affairs will be challenging. The Council agreed that the successful integration of GenAI by Medical Affairs faces several hurdles and will require diligent attention to factors inside and outside the organization:

Data Privacy and Security

Maintaining absolute confidentiality and integrity of research, HCP and patient data is critical in healthcare. AI systems are driven by access to vast amounts of data, raising concerns about data breaches and unauthorized access. Ensuring robust security measures and compliance with data protection regulations is essential to protect sensitive information.

Regulatory Compliance

AI applications must adhere to a myriad of laws and ethical standards, including those related to patient rights and data usage. Navigating this complex regulatory landscape is a significant challenge for AI integration.

Human Oversight

AI cannot replace human judgment and empathy in healthcare. Ensuring that AI systems operate under the supervision of healthcare professionals is crucial to maintaining accuracy, compliance, and addressing AI limitations. Human oversight also helps make nuanced decisions that AI might not be capable of.

Technical Limitations and Reliability

AI's understanding of complex medical data is not infallible. Technical limitations can lead to reliability issues, affecting diagnoses or treatment recommendations. Continuous improvement and validation of AI models are necessary to enhance their accuracy and reliability.

Integration with Existing Systems

Integrating AI into existing healthcare IT ecosystems without disrupting workflows is challenging. Compatibility issues with EHRs, diagnostic tools, and other software can hinder the seamless adoption of AI technologies.

Bias and Fairness

AI systems can perpetuate biases present in their training data, leading to unfair outcomes for certain groups. Addressing these biases and ensuring fairness in AI-generated recommendations is a significant challenge.

Ethical Considerations

The use of AI in healthcare raises ethical questions, such as the extent to which it informs patient-level HCP support and education. For instance, this is particularly concerning where training data used to inform a decision model do not reflect the diversity of populations encountered in routine clinical practice. Balancing innovation with ethical considerations is crucial to ensure that AI applications benefit patients without compromising their rights or safety.

Building Trust

For AI to be successfully adopted in healthcare, both patients and professionals must trust the technology. This requires transparency in how AI systems make decisions and ensuring those decisions can be explained in terms that are understandable to all stakeholders.

Maintaining Functional Expertise

GenAI systems and products are continuously evolving; improving in capability and growing in complexity. A concerted effort to keep up with these advancements will be essential to maximize their utility while minimizing risks and will require well-designed training programs within the organization and selection of the most capable partners outside the organization.

Addressing these challenges requires a collaborative effort among information technologists, healthcare professionals, regulators, and patients to ensure that AI technologies are developed and implemented in a way that is secure, ethical, and beneficial to all parties involved.

The prospect of advancing Medical Affairs with GenAI is exciting but brings with it significant responsibilities. The Council underscored the importance of being an active participant in the dialogue with Compliance and Regulatory functions within their respective companies. To date, there is little concrete guidance for Medical Affairs, with most legislation focusing on AI providers and regulatory agencies. Acknowledging that regulations have been laggard concerning advancements in GenAI the human-in-the-loop approach will likely be here for the foreseeable future.

Advances in GenAI implementation: Introducing 'Agents'

The past year has seen a rapid advancement in the development and implementation of GenAI tools. A particularly exciting development is the introduction of Agents. Until recently, implementation of GenAI almost always meant reliance on one enterprise paid model, refined through prompt engineering, to facilitate organizational use cases. Agents are capable of understanding specific goals or tasks, creating workflows to achieve defined goals, prioritizing tasks, recruiting other Agents, databases, or tool sets, and learning from intermediate actions until the goal is achieved. Agents break down specific problem statements into component instructions and then negotiate, or work with, other agents to pull in required information from related data sources. The Agent can then bring additional tools to the task of completing the problem or answering the question.

Medical Affairs use cases will increasingly rely on source data across multiple functions to solve complex challenges, and so the automated orchestration and planning capabilities of Agents will become fundamental to the Medical Affairs use of GenAI. Some Medical Affairs business challenges will likely require a team of specialized agents situated around larger enterprise models – a 'swarm of agents' approach.

Recommendations

To successfully harness the power of GenAI in the industry, the Council believes that Medical Affairs organizations should look at the following key areas to enable success:

Invest in Training and Development

Organizations must prioritize the education and training of their professionals in the use of GenAI tools. This involves not only understanding how to operate these tools but also comprehending their underlying principles and potential biases. Training programs should cover data literacy, ethical AI use, and scenario-based learning to ensure professionals can effectively leverage GenAI for improved patient care and operational efficiency. A systematic approach for ongoing assessment and comparison of different generative AI tools and vendors will be critical for maintaining an edge in this rapidly evolving environment.

Foster Industry-wide Collaboration

Collaboration across the healthcare sector is crucial for sharing insights, best practices, and innovative solutions related to GenAI. By working together, organizations can address common challenges, such as data interoperability and privacy concerns, and develop standardized approaches for integrating GenAI technologies. This collaborative effort can accelerate the adoption of GenAI and maximize its benefits across the industry.

Monitor and Adapt to the Evolving Regulatory Landscape

The regulatory environment for AI in healthcare is continuously evolving. Organizations must stay informed about new regulations and guidelines to ensure their GenAI applications comply with legal and ethical standards. This includes understanding data protection laws, patient consent requirements, and AI-specific regulations. Proactively engaging with regulators and participating in policy development can also help shape a supportive regulatory framework for GenAI in healthcare.

Prioritize Human Oversight

Despite the advances in GenAI, human oversight remains essential to ensure the accuracy, safety, and ethical use of AI-generated outputs. Healthcare organizations should develop protocols and guidelines for human review of GenAI recommendations, especially in critical areas such as diagnosis and treatment planning. This oversight helps mitigate risks associated with AI errors and biases, ensuring that GenAI tools augment rather than replace human expertise.

By focusing on these key areas, healthcare organizations can effectively harness the power of GenAI, driving innovation and improving patient outcomes while navigating the complex landscape of technological, regulatory, and ethical considerations.

Conclusion

Generative AI holds the potential to revolutionize Medical Affairs by enhancing efficiency and effectiveness, fostering innovation, and improving patient care. Medical Affairs can think bigger than ever before. Its dual goals of improving the business value and clinical impact of medical affairs activities can be greatly expanded by the vast potential of Gen AI. However, realizing this potential requires addressing the challenges of data privacy, regulatory compliance, and maintaining human oversight. As technology evolves, so too will its applications, necessitating ongoing dialogue, collaboration, and adaptation within the industry. The journey toward integrating GenAI into the industry is complex but promising, and not without its challenges.

A Call to Action

As we integrate GenAI into our workflows, careful management, a culture of constant learning and collaboration, ongoing detailed analysis and appropriate scrutiny of products and processes will be prerequisites to success for individual organizations and the industry as a whole. Generative AI has enormous potential to profoundly improve Medical Affairs practices and the value they deliver to HCPs and patients. Dramatic inflection points in patient outcomes have always come about when new technologies are assimilated into care by HCPs and the industry working in close collaboration. GenAI provides Medical Affairs with a golden opportunity to continue this tradition. Doing so will require diligent attention and action.

Acknowledgements

We thank the members of the Medical Affairs Digital Strategy Council for their active contributions towards this paper: