Introduction

The History of Artificial Intelligence

The founding principles of Artificial Intelligence (AI) research were established at a Dartmouth College workshop in the summer of 1956 by computer scientist John McCarthy (Kaplan & Haenlein, 2019). Although participants of this workshop anticipated an AI advent to occur within the following decades, they vastly underestimated the complexity of developing a functional model. Early AI models resembled toys rather than practically-applicable tools due to limited computing power. The field, along with its government-sponsored DARPA funding, all but disappeared from 1974 until AI’s rebirth in the mid-2010s (Agar, 2020). Acquisition of AI Company DeepMind by Google in 2014 preceded the development of the DeepMind gameplay AI known as AlphaGo. Subsequently, the AlphaGo software defeated a professional player of ‘Go’ game, renewing the AI spark that had been extinguished in decades past. An explosion of innovation in AI tools followed, which had direct applications within academic settings by strengthening online learning modules, enabling facial recognition, and facilitating academic coaching. The corporate world took notice, quickly adopting AI in human resources for applicant screening and in chatbot generation in 2018 (Kaplan & Haenlein, 2019). As a result of its potential for elevating profitability, AI’s reach and functionality has since become engrained within the corporate structure itself. With increasing computing capabilities, AI’s usefulness has expanded into myriad corporate sectors, which now includes the field of medical affairs.

Artificial Intelligence’s Future in Medical Affairs

The Accreditation Council for Medical Affairs (ACMA) is a leader of continuing education in medical affairs, possessing the largest database of knowledge specific to the field of medical affairs itself. As the regulations around AI technology have evolved, a unique niche for AI innovation has emerged within ACMA’s purview. ACMA has launched a first-in-class AI tool specifically designed for enhancing the existing capabilities of medical affairs teams: MedAffairsAI. The need for such an AI tool becomes self-evident when examining the job description itself: medical affairs professionals are therapeutic area experts with advanced degrees who rely on massive databases to liaise between pharmaceutical companies and healthcare providers in a manner that is quick, accurate, and trustworthy. To meet these needs, ACMA’s MedAffairsAI tool combines the data-scraping power of AI, ACMA’s proprietary wealth of knowledge in the medical affairs field, and the ability to seamlessly incorporate client documents to inform customized training data. In this way, the MedAffairsAI tool can decrease time spent scraping databases for answers to queries, build large databases of interactions with healthcare providers that inform strategic corporate decisions, and increase engagement with key opinion leaders. Successful adoption of MedAffairsAI for these purposes is expected to fill a profitability gap predicted by McKinsey to approach 3-5 billion USD per year (Viswa et al., 2024). Uniquely, ACMA’s expert panel provides regulatory insight in the design and maintenance of the MedAffairsAI tool to anticipate evolving regulatory and ethical AI considerations. This expert guidance reduces client risk and liability for AI implementation within their medical affairs team, therefore positioning early adopters of this tool to outpace competitors.

Considerations for Adopting Artificial Intelligence

The benefits of utilizing artificial intelligence within the life sciences industry has been recognized in several subfields. Major contributions of AI in life sciences include the acceleration of small molecule drug discovery, pharmacogenomic refinement of personalized medicine, and clinical trial recruitment. Whereas most generally-accessible artificial intelligence models have a shallow, yet wide breadth of knowledge, AI implementation within life sciences requires extensive model training before validation, testing, and finally deployment. Therefore, the development of ACMA’s MedAffairsAI tool necessitated a finely-curated construction. If the implementation of medical affairs AI can be fully realized, McKinsey predicts a staggering increase in efficiency-driven valuation of medical affairs teams by billions of dollars annually.

Advisory boards identify legal and compliance issues arising from AI implementation across industries to strategize risk management for individualized use cases. The expertise and long-standing experience of these advisory boards help strategically implement technologies while adhering to regulatory changes in the rapidly-evolving field of artificial intelligence. Alex Shandro, a partner at Allen & Overy Shearman, is a member of one of the longest-standing firms advising use case risk in artificial intelligence technology. In a highly-informative webinar with ACMA, Shandro highlighted key takeaways from his experiences with risk management in biotechnology companies (Soliman & Shandro, 2024). This advisory relationship helps ACMA’s MedAffairsAI tool stay ahead of the regulatory curve by anticipating compliance issues before they occur. Shandro’s key insights into operational integration, oversight compliance, strategic implementation and use case risk mitigation are discussed in-depth in the following passages.

Seamless Operational Integration

Medical affairs workflows are, in themselves, complicated. This team’s efficacy necessitates the integration of data from myriad sources ranging from Customer Resource Management (CRM) software, preliminary & published clinical trial data, drug safety databases, educational branding material, and proprietary relationship management material for leading figures in the healthcare industry. Although simply consolidating these databases within AI software is tempting, considerations must be made within the design of the AI itself to best consider long-standing workflow needs. Not only must an AI be able to read a multitude of media types, it must also regularly sync up-to-date information while discarding out-of-date material to ensure a seamless experience. While medical affairs teams can benefit greatly from the large breadth and depth of knowledge that AI can provide, pharmaceutical manufacturers must first invest in easily-integratable AI tools that empower their teams with both precision and accuracy. Early adopters of these accessible technologies, like MedAffairsAI, will allow medical affairs teams to effectively analyze the healthcare field and outpace competitors.

Contractual Compliance with Oversight Committees

Initially considered to be primarily an IT concern, rapidly evolving AI tool usage has become increasingly multidisciplinary. There has been an increasing need to regulate implementation strategy across organizational departments. This necessitates integration of AI advisory boards that utilize their expert insights in regulatory compliance to facilitate the construction of organizational AI tool standards. Accredited organizations like ACMA are poised to liaise between these organizations and long-standing field regulatory experts by providing guidance about medical affairs-specific AI implementation while assessing needs specific to each organization. This oversight helps not only build out regulatory guidelines for AI tool use in organizations, but also helps triage individual use cases to mitigate risk. Overall, the use of ACMA’s third-party experts shifts risk from organizational AI implementers to ACMA’s AI advisory experts. Therefore, ACMA enables organizations to develop compliant AI standard operating procedures while remaining focused on existing organizational targets.

Strategic Implementation by Organization

The benefits to be realized from effective and compliant AI tool implementation are vast. Early adopters of medical affairs AI tools are more likely to fully reap these benefits while outpacing their competition. However, organizational leaders must acknowledge the learning curve in implementing this software into preexisting workflows and therefore strategically approach AI tool launch. Instead of launching an AI tool and expecting instant integration, leaders must adopt a gentler approach. ACMA provides trials of its MedAffairsAI software, which can be procured by organizational leaders. To test this trial AI tool, ACMA advises deployment in small projects with a short timeframe to goal completion. Key organizational leaders then recognize the momentum of this AI tool and will organically encourage implementation into their own team workflows. The team members can then be trained to effectively implement MedAffairsAI by using ACMA’s AI tool FAQ and live chat assistance. By using this method, AI tools will be effectively deployed while reducing shock to the organization.

Conclusion

The benefits of AI implementation into Medical Affairs teams are far-reaching. ACMA’s MedAffairsAI is at the forefront of both fields. By providing the largest compendium of medical affairs knowledge and combining it with expert AI advisory boards, ACMA provides a wealth of easily-accessible information that has the potential to transform the efficiency of medical affairs teams.

References:

Agar, J. (2020). What is science for? The Lighthill Report on Artificial Intelligence reinterpreted. The British Journal for the History of Science, 53(3), 289–310. https://doi.org/10.1017/s0007087420000230

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? on the interpretations, illustrations, and implications of Artificial Intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004

Soliman, W., & Shandro, A. (2024, March 22). The Next Frontier: Generative AI in pharma and legal considerations. YouTube. https://www.youtube.com/watch?v=Kg9LpCIZqs0

Viswa, C. A., Bleys, J., Leydon, E., Shah, B., & Zurkiya, D. (2024, January 9). Generative AI in the pharmaceutical industry: Moving from hype to reality. McKinsey & Company.