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Artificial Intelligence in Health AI in pharma: Embracing transformation

6.3. Advanced technology at hand

Experts anticipate that human-level AI will be achievable
74
Research & • Predictive modelling before the turn of the century. Without maintaining a
Discovery • Drug repurposing
forward-looking perspective when evaluating investment
opportunities for innovative ideas, pharmaceutical
businesses risk losing their market position to future
visionaries who may disrupt the industry.
Clinical
Trials • Patient recruitment 7. Conclusion
• Adverse event prediction
In the quest to advance science and improve public health,
the utility of AI extends across the value chain (Figure 1),
Regulatory • Data review benefiting the clinical and commercial divisions of
Approval • Compliance monitoring pharmaceutical businesses. While sensitive issues, such
as data collection and analysis, require consideration,
regulatory guidelines are in place to provide useful
guardrails. Through pragmatism and collaboration, the
Manufacturing • Supply chain optimisation pharmaceutical industry could shift the paradigm, embrace
• Quality control the new technological era, and leverage the full potential of
AI to shape a better future for everyone.
Acknowledgments
Marketing • Data analysis
& Sales • Personalisation None.
Funding

None.
Pharmacovigilance • Adverse event detection
• Risk management Conflict of interest
There are no conflicts of interest.

Author contributions
Patient • Precision medicine
Adherence • Compliance monitoring This is a single-authored article.

Ethics approval and consent to participate
Not applicable.
Figure 1. Illustrative integration of AI applications across the
pharmaceutical value chain. Consent for publication

Nevertheless, organizational susceptibility to cyberattacks Not applicable.
may also be amplified unless post-quantum cryptographic
security protocols are implemented. 71 Availability of data
Not applicable.
6.2. Low-code development
The advent of low-code and no-code software development References
tools reduces the reliance on specialized coding skill sets, 1. Toffler A. Future Shock. New York: Bantam Books; 1970.
bridging the gap for businesses without access to such 2. Abed S. A literature review exploring the role of technology
expertise. Thus, AI system development may become more in business survival during the Covid-19 lockdowns. Int J
democratized with time as employees feel empowered by their Organ Anal. 2022;30(5):1045-1062.
ability to bring ideas, which they would not have previously
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considered feasible, to market through rapid prototyping and doi: 10.1108/IJOA-11-2020-2501
deployment. Indeed, it has been reported that low-code and 3. Zhu X, Ge S, Wang N. Digital transformation: A systematic
generative AI are accelerating innovation. 73 literature review. Comput Ind Eng. 2021;162:107774.

Volume 1 Issue 3 (2024) 6 doi: 10.36922/aih.2973