Home Page ContentPress Releases GenAI has potential to address high cost, poor patient experience issues in pharma and healthcare, says GlobalData

GenAI has potential to address high cost, poor patient experience issues in pharma and healthcare, says GlobalData

by Anthony Weaver

The implementation of generative artificial intelligence (genAI) in
pharma and healthcare has the potential to address the issues of high
costs and poor patient experiences while enhancing efficiency and
patient outcomes. With a growing focus on data-driven healthcare, genAI
is poised to significantly transform the industry, says GlobalData [1],
a leading data and analytics company.

Kiran Raj, Practice Head of Disruptive Tech [2] at GlobalData,
comments: “GenAI is fundamentally revolutionizing the healthcare
scene, powering a transformative shift across the value chain. Its
ability to customize multi-format content, serving everyone from
pharmaceuticals to patients, bestows precisely targeted communication.
However, adhering to responsible AI is pivotal in building trust and
managing risks within the industry.”

Saurabh Daga, Associate Project Manager of Disruptive Tech [3] at
GlobalData, adds: “GenAI can streamline personalized care and guided
diagnosis by synthesizing key data points from patients’ medical
history, family history, and lifestyle. The technology can help
physicians provide more effective care at lower costs, leading to better
patient outcomes.”

GlobalData’s latest Innovation Radar report, “New prescription:
generative AI meets healthcare [4],” provides a comprehensive view of
how genAI is being implemented across the pharma value chain for
applications ranging from research & development, imaging & diagnostics
to patient care and support.

GenAI is set to revolutionize drug discovery by generating novel drug
candidates based on researcher-provided criteria and constraints.
Predicting the efficacy and safety of new drug candidates and
personalizing drug therapy are additional capabilities that are poised
to improve patient outcomes.

While drug discovery startups such as Huma.AI, Insilico Medicine, and
Absci are developing generative models capable of fast-tracking drug
development, companies like Google and NVIDIA through MedPalm 2 and
BioNeMo Cloud are providing the necessary infrastructure for
genAI-powered drug discovery.

Daga concludes: “While the genAI landscape is not without risks,
especially in regulated industries like pharma and healthcare, there is
potential for significant advancements and benefits. Challenges such as
bias, discrimination, and privacy need to be mitigated through
governance. It is crucial to partner with organizations that offer
industry perspective and technology expertise at the intersection of
responsible AI to fully leverage the potential of recent technological
breakthroughs.”

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