The Digital Transformation: How Could Artificial Intelligence (AI) Re-Shape Drug Launch?

Author(s)

Robert A1, Foster D1, Brazier M2
1PRMA Consulting Ltd., Fleet, Hampshire, UK, 2PRMA Consulting Ltd., London, LON, UK

Presentation Documents

OBJECTIVES: Within the biotechnology and pharmaceutical industries, the advent of advanced analytics including artificial intelligence and machine learning has triggered a fundamental paradigm shift. These new technologies open a world of opportunity including enhanced drug discovery, advanced precision medicine, and optimized clinical trials. With the first drugs discovered and developed by AI now entering clinical trials, the focus has switched beyond development to exploring the applicability of AI technologies to augment drug launch and market access.

METHODS: A targeted grey literature search was conducted to explore what potential applications of AI are being developed by leading pharmaceutical companies. Examples of material investigated include promotional posts on company websites, articles in leading pharmaceutical magazines and newsletters, and social media posts on platforms such as LinkedIn. A framework was developed to map ongoing priority areas for AI within the Top 20 pharmaceutical companies to different “building blocks” of a successful drug launch strategy. These building blocks include identifying the target population with highest unmet need, developing an impactful value proposition, engaging with external stakeholders, and submission for reimbursement.

RESULTS: Our search revealed four main focus areas for AI in terms of enhancing the drug launch and market access process: patient stratification, predictive pricing, omnichannel marketing, and targeted promotion. In terms of readiness, the latter is the closest to becoming reality, with machine-learning already capable of using a physician’s past prescribing patterns to accurately predict future product uptake. The evolving landscape of cost containment and pricing pressure from policy changes such as the inflation reduction act (IRA) mean that AI’s ability to drive predictive pricing may take longer to become reality.

CONCLUSIONS: The takeaway message is that AI is, and will continue, to profoundly impact market access strategy, and will be a key tool in developing successful launch tactics in the next 3-5 years.

Conference/Value in Health Info

2023-11, ISPOR Europe 2023, Copenhagen, Denmark

Value in Health, Volume 26, Issue 11, S2 (December 2023)

Code

HPR202

Topic

Health Policy & Regulatory, Health Technology Assessment, Methodological & Statistical Research

Topic Subcategory

Artificial Intelligence, Machine Learning, Predictive Analytics, Reimbursement & Access Policy, Systems & Structure

Disease

Drugs, No Additional Disease & Conditions/Specialized Treatment Areas

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