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Artificial Intelligence in Health AI in pharma: Embracing transformation

teams to seamlessly collaborate on mission-critical by reviewing claims against the product information,
projects. Although lockdowns have subsided, a hybrid literature, and regulatory guidelines.
working model has persisted, along with the use of digital Considering the volume of material requiring approval,
tools to support project management and communication. the limited number of signatories qualified to review
Fortunately, ongoing digital innovation offers businesses material, and the need for materials to be re-approved
opportunities to future-proof their operations in the face every 2 years, the administrative burden is significant.
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of evolving challenges.
However, AI could help offset this burden by accessing
Artificial intelligence (AI) is integral to the next the latest guidance, conducting initial reviews, and either
phase of digitalization, the so-called “Fourth Industrial flagging potential points of noncompliance for manual
Revolution.” Essentially, AI algorithms emulate human review or suggesting resolutions for conflicts. Although
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intelligence, enabling machines to think or act in a way the final signatory would ultimately hold responsibility
that has traditionally been associated with humans. AI can for approving materials, AI could streamline the approval
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analyze data, identify trends, and share predictive insights. process for signatories, translating into productivity gains for
From a business perspective, AI can improve efficiency and the organization. In recognition of this, a leading consultancy
provide a competitive advantage through automation and has developed such a tool to support pharmaceutical
intelligent decision-making. companies. 13
The pharmaceutical industry is in a favorable position 2.3. Pharmacovigilance
to leverage AI’s capabilities to realize these benefits, owing
to the abundance of data available to companies. However, Pharmacovigilance is an important regulatory requirement
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there is a paucity of evidence considering the role of AI that pharmaceutical companies must comply with
within the industry. Consequently, this review delves into throughout the product’s lifecycle, from pre-market
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the use of AI in the pharmaceutical industry, exploring its to post-market surveillance. Detecting, monitoring,
potential impact, benefits, and challenges. and reporting adverse drug reactions is essential for
maintaining patient safety, and reflects on the reputation
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2. Clinical of organizations.
AI has much to offer in supporting clinical functions As timely intervention is important for risk mitigation,
within the pharmaceutical industry. AI could support the identification of adverse events by
parsing and extracting data from clinical sources such
2.1. Clinical operations as published literature, electronic health records, and
Many pharmaceutical companies seek to improve health other database repositories. Over time, AI may become
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outcomes by supporting diagnosis, monitoring, and more reliable at collating unstructured data stored online,
treatment across specific therapeutic areas. In this way, AI including free text or audiovisual formats on social media.
can deliver the “quadruple aim” of healthcare, by improving This would provide a more comprehensive approach
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population health, cost efficiency, patient experience, and as such data may not be captured from more structured
staff wellbeing. sources. While AI cannot replace manual review entirely,
it can drive efficiency by undertaking a preliminary
For instance, AI could augment diagnostic imaging 16
modalities to help detect and monitor disease. By assisting triage to prioritize incoming reports by severity for
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radiologists in detecting adverse signs on imaging promptly, pharmacovigilance review teams.
AI may facilitate earlier intervention, potentially preventing 2.4. Research and development
disease progression and serious complications. In addition,
AI could help develop personalized management plans Research and development (R&D) are prerequisites for
to improve health outcomes, by identifying the most drug discovery and development. However, the process is
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effective treatment options from the medical literature time- and cost-intensive, especially when considering that
and assessing their suitability based on patient data stored profitability declines rapidly once product patents expire
across electronic health records and genomic servers. and competitors aggressively undercut prices through
generic medicines. Given the product lifecycle, the onus
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2.2. Medical excellence is on pharmaceutical companies to innovate and secure the
future pipeline of drugs.
In the pharmaceutical industry, promotional and non-
promotional materials must be reviewed by registered doctors AI can offer solutions to some of the challenges
or pharmacists, who act as final medical signatories. These associated with R&D by accelerating the process. Initially,
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signatories certify that materials are factual and evidenced AI may help identify novel therapeutic molecules and

Volume 1 Issue 3 (2024) 2 doi: 10.36922/aih.2973