AI is a powerful vehicle. But without a well-defined road, it can veer off course. Pharma's challenge is developing the best AI tools and ensuring that they are built in a way that patients, regulators, and HCPs can trust.
AI’s promise and the challenges that follow
Pharma has embraced AI across its value chain. AI-driven drug discovery platforms cut research timelines, digital assistants guide HCPs to better prescribing decisions, and AI-powered chatbots provide 24/7 patient support. But without careful oversight, these advancements could cause more harm than good.
Bias in AI models can lead to inequitable healthcare outcomes, and opaque algorithms may reduce trust from regulators and patients alike. IBM Watson’s early foray into AI-driven oncology recommendations raised concerns about incorrect suggestions due to flawed training data. AI is only as good as its design, training data, and governance.
Regulation and compliance – navigating the AI maze
With the EU AI Act set to introduce stricter guidelines, pharma leaders must rethink how they integrate AI responsibly. The Act will categorise AI systems by risk level, meaning some pharma applications, such as clinical trial decision-making, may fall under high-risk classifications, requiring stricter oversight. Additionally, GDPR enforces transparency in AI-driven decisions, particularly where patient data is involved.
Companies that build compliance into their AI strategy now will be better prepared for future regulations. Responsible AI development is not just about avoiding fines or penalties. It is an opportunity to create systems that patients, regulators, and healthcare providers can trust, ensuring AI strengthens rather than weakens relationships.
For Europe, the challenge is balancing regulation and ethics with competitive forces. AI is driving an innovation race in a way not seen before. The biopharma industry's AI market is expected to grow from $198.3 million in 2018 to $3.88 billion in 2025, with a CAGR of 52.9%.
Responsible AI in action – lessons from leaders
Some pharma companies are already leading the way. Novartis has implemented an internal AI ethics board to review all AI-driven initiatives. Their approach ensures that models used in drug discovery and patient analytics align with ethical guidelines, reducing bias and increasing transparency.
Another example is Sanofi, which has embedded explainability measures into its AI-driven HCP engagement tools. By ensuring that AI recommendations for sales reps and medical teams are fully auditable and based on transparent data sets, Sanofi enhances trust both internally and externally. Like Novartis and other industry leaders, Sanofi has an internal AI ethics board and an ethical AI governance framework.
A blueprint for responsible AI adoption in pharma
To successfully integrate AI while meeting regulatory and ethical standards, pharma companies should focus on these key principles:
Bias mitigation: Train AI models on diverse, representative datasets to avoid biased recommendations that could disadvantage certain patient groups.
Algorithm transparency: Ensure AI-driven decisions are explainable and auditable, particularly in patient care and HCP engagement.
Regulatory foresight: Build compliance into AI development from the outset, aligning with GDPR and the EU AI Act before these regulations tighten.
Ethical AI governance: Establish internal AI ethics committees to review AI deployments and ensure they align with industry best practices.
Human-AI collaboration: AI should assist, not replace, human decision-making, ensuring clinicians, researchers, and HCPs remain central to the process.
AI needs to be an enabler, not a liability.
Pharma is poised for an AI-driven transformation, but the path forward requires a balance of innovation and responsibility. Companies integrating responsible AI into their operations today will avoid regulatory pitfalls and gain a strategic advantage in building patient and stakeholder trust.
JOURNEY believes AI should support customer experience, operational efficiency, and innovation. The companies that will thrive in the next era of pharma see AI as a tool and a commitment to doing things the right way. AI can redefine healthcare only if the industry lays the foundations today.
AI is a powerful vehicle. But without a well-defined road, it can veer off course. Pharma's challenge is developing the best AI tools and ensuring that they are built in a way that patients, regulators, and HCPs can trust.
AI’s promise and the challenges that follow
Pharma has embraced AI across its value chain. AI-driven drug discovery platforms cut research timelines, digital assistants guide HCPs to better prescribing decisions, and AI-powered chatbots provide 24/7 patient support. But without careful oversight, these advancements could cause more harm than good.
Bias in AI models can lead to inequitable healthcare outcomes, and opaque algorithms may reduce trust from regulators and patients alike. IBM Watson’s early foray into AI-driven oncology recommendations raised concerns about incorrect suggestions due to flawed training data. AI is only as good as its design, training data, and governance.
Regulation and compliance – navigating the AI maze
With the EU AI Act set to introduce stricter guidelines, pharma leaders must rethink how they integrate AI responsibly. The Act will categorise AI systems by risk level, meaning some pharma applications, such as clinical trial decision-making, may fall under high-risk classifications, requiring stricter oversight. Additionally, GDPR enforces transparency in AI-driven decisions, particularly where patient data is involved.
Companies that build compliance into their AI strategy now will be better prepared for future regulations. Responsible AI development is not just about avoiding fines or penalties. It is an opportunity to create systems that patients, regulators, and healthcare providers can trust, ensuring AI strengthens rather than weakens relationships.
For Europe, the challenge is balancing regulation and ethics with competitive forces. AI is driving an innovation race in a way not seen before. The biopharma industry's AI market is expected to grow from $198.3 million in 2018 to $3.88 billion in 2025, with a CAGR of 52.9%.
Responsible AI in action – lessons from leaders
Some pharma companies are already leading the way. Novartis has implemented an internal AI ethics board to review all AI-driven initiatives. Their approach ensures that models used in drug discovery and patient analytics align with ethical guidelines, reducing bias and increasing transparency.
Another example is Sanofi, which has embedded explainability measures into its AI-driven HCP engagement tools. By ensuring that AI recommendations for sales reps and medical teams are fully auditable and based on transparent data sets, Sanofi enhances trust both internally and externally. Like Novartis and other industry leaders, Sanofi has an internal AI ethics board and an ethical AI governance framework.
A blueprint for responsible AI adoption in pharma
To successfully integrate AI while meeting regulatory and ethical standards, pharma companies should focus on these key principles:
Bias mitigation: Train AI models on diverse, representative datasets to avoid biased recommendations that could disadvantage certain patient groups.
Algorithm transparency: Ensure AI-driven decisions are explainable and auditable, particularly in patient care and HCP engagement.
Regulatory foresight: Build compliance into AI development from the outset, aligning with GDPR and the EU AI Act before these regulations tighten.
Ethical AI governance: Establish internal AI ethics committees to review AI deployments and ensure they align with industry best practices.
Human-AI collaboration: AI should assist, not replace, human decision-making, ensuring clinicians, researchers, and HCPs remain central to the process.
AI needs to be an enabler, not a liability.
Pharma is poised for an AI-driven transformation, but the path forward requires a balance of innovation and responsibility. Companies integrating responsible AI into their operations today will avoid regulatory pitfalls and gain a strategic advantage in building patient and stakeholder trust.
JOURNEY believes AI should support customer experience, operational efficiency, and innovation. The companies that will thrive in the next era of pharma see AI as a tool and a commitment to doing things the right way. AI can redefine healthcare only if the industry lays the foundations today.
AI is a powerful vehicle. But without a well-defined road, it can veer off course. Pharma's challenge is developing the best AI tools and ensuring that they are built in a way that patients, regulators, and HCPs can trust.
AI’s promise and the challenges that follow
Pharma has embraced AI across its value chain. AI-driven drug discovery platforms cut research timelines, digital assistants guide HCPs to better prescribing decisions, and AI-powered chatbots provide 24/7 patient support. But without careful oversight, these advancements could cause more harm than good.
Bias in AI models can lead to inequitable healthcare outcomes, and opaque algorithms may reduce trust from regulators and patients alike. IBM Watson’s early foray into AI-driven oncology recommendations raised concerns about incorrect suggestions due to flawed training data. AI is only as good as its design, training data, and governance.
Regulation and compliance – navigating the AI maze
With the EU AI Act set to introduce stricter guidelines, pharma leaders must rethink how they integrate AI responsibly. The Act will categorise AI systems by risk level, meaning some pharma applications, such as clinical trial decision-making, may fall under high-risk classifications, requiring stricter oversight. Additionally, GDPR enforces transparency in AI-driven decisions, particularly where patient data is involved.
Companies that build compliance into their AI strategy now will be better prepared for future regulations. Responsible AI development is not just about avoiding fines or penalties. It is an opportunity to create systems that patients, regulators, and healthcare providers can trust, ensuring AI strengthens rather than weakens relationships.
For Europe, the challenge is balancing regulation and ethics with competitive forces. AI is driving an innovation race in a way not seen before. The biopharma industry's AI market is expected to grow from $198.3 million in 2018 to $3.88 billion in 2025, with a CAGR of 52.9%.
Responsible AI in action – lessons from leaders
Some pharma companies are already leading the way. Novartis has implemented an internal AI ethics board to review all AI-driven initiatives. Their approach ensures that models used in drug discovery and patient analytics align with ethical guidelines, reducing bias and increasing transparency.
Another example is Sanofi, which has embedded explainability measures into its AI-driven HCP engagement tools. By ensuring that AI recommendations for sales reps and medical teams are fully auditable and based on transparent data sets, Sanofi enhances trust both internally and externally. Like Novartis and other industry leaders, Sanofi has an internal AI ethics board and an ethical AI governance framework.
A blueprint for responsible AI adoption in pharma
To successfully integrate AI while meeting regulatory and ethical standards, pharma companies should focus on these key principles:
Bias mitigation: Train AI models on diverse, representative datasets to avoid biased recommendations that could disadvantage certain patient groups.
Algorithm transparency: Ensure AI-driven decisions are explainable and auditable, particularly in patient care and HCP engagement.
Regulatory foresight: Build compliance into AI development from the outset, aligning with GDPR and the EU AI Act before these regulations tighten.
Ethical AI governance: Establish internal AI ethics committees to review AI deployments and ensure they align with industry best practices.
Human-AI collaboration: AI should assist, not replace, human decision-making, ensuring clinicians, researchers, and HCPs remain central to the process.
AI needs to be an enabler, not a liability.
Pharma is poised for an AI-driven transformation, but the path forward requires a balance of innovation and responsibility. Companies integrating responsible AI into their operations today will avoid regulatory pitfalls and gain a strategic advantage in building patient and stakeholder trust.
JOURNEY believes AI should support customer experience, operational efficiency, and innovation. The companies that will thrive in the next era of pharma see AI as a tool and a commitment to doing things the right way. AI can redefine healthcare only if the industry lays the foundations today.
