Introduction: The Transformative Potential of Gen AI
The advent of Generative Artificial Intelligence (Gen AI) promises a seismic shift in the pharmaceutical industry. With its capability to automate tasks, enhance decision-making, and improve customer experiences, Gen AI stands at the forefront of a technological revolution. This blog is based on recent McKinsey report, “The organization of the future: Enabled by gen AI, driven by people”. It serves as a guide to market access and health economics and outcomes research (HEOR) professionals in the pharmaceutical industry on how to leverage Gen AI effectively.
Gen AI: A Tool for All
Remarkably, Gen AI does not demand extensive training or technical expertise. McKinsey research indicates that by 2030, Gen AI could automate up to 70% of business activities, adding trillions to the global economy. However, it’s crucial to recognize that Gen AI is still in its early stages and is poised to become even more sophisticated.
Strategic Approach for Business Leaders
For leaders in Market Access and HEOR, understanding the broader implications of Gen AI is vital. It’s essential to align Gen AI’s capabilities with the company’s strategic goals. Given its potential to accelerate automation, messaging should focus on “augmentation and improvement” rather than “replacement and loss.”
Senior Leadership and Demystifying Gen AI
Senior leaders have the crucial task of demystifying Gen AI. They must evaluate its strategic implications and the associated risks and opportunities. The McKinsey report suggests developing a compelling narrative for Gen AI will require identification of two or three high-impact applications in HEOR and Market Access. This strategy will help moving teams from pilot tests to full-scale integration.
What could be High-Impact Applications in HEOR and Market Access?
- Health Technology Assessment Data Analysis: Generative AI can analyze extensive data from Health Technology Assessment reports, synthesizing important information for decision-makers.
- Predictive and Economic Modeling: Generative AI can be used to build HEOR models that forecast various health outcomes and economic scenarios, enhancing predictive capabilities.
- Literature Review and Analysis: AI can expedite systematic literature reviews, a crucial aspect of HEOR, by swiftly filtering through large volumes of scientific literature, identifying relevant studies, extracting key data, and summarizing findings.
- Automated Report Generation: Generative AI could be trained to draft reports for HTA submissions or internal use, although this may require fine-tuning of existing Large Language Models.
- Interactive Stakeholder Engagement Tools: Generative AI can develop interactive tools and visualizations for communicating complex HEOR findings to various stakeholders, including healthcare providers, payers, and patients, aiding in decision-making and policy development.
- Ethical and Regulatory Compliance: Generative AI can assist in ensuring that HEOR practices adhere to ethical and regulatory standards, identifying potential biases in studies and safeguarding data privacy and patient confidentiality.
- Data Synthesis Caution: While Generative AI can create synthetic data in the HEOR space, this approach is risky and could negatively impact perceptions of Generative AI in this field. It’s recommended to avoid producing synthetic data.
Conclusion: A Call to Action
The integration of Gen AI in Market Access and HEOR is not a passive process. It requires active experimentation, investment, and adaptation. There is no better time than now to start leveraging Gen AI to shape the future of the industry, ensuring that market access and HEOR professionals stay at the cutting edge of technological advancement.
