Discover the importance of a purpose-built AI framework and solution that helps life sciences organizations successfully adopt AI and mitigate risk.
AI and generative AI have the potential to help life sciences organizations solve one of their most difficult problems: how to sift through vast pools of data to find high-quality insights. Learn how Sorcero, Google, and USDM are partnering to deliver a joint AI solution for life sciences that addresses this critical need.
What's Inside
- Cloud compliance as the foundation for responsible AI — how the principles that made vertical, life-sciences-specific cloud software trustworthy translate directly to AI adoption.
- Building a responsible AI model — why a deliberate model for proper AI use is urgent, and the challenges of keeping compliance practices aligned with rapidly evolving AI technology.
- Sourcing and validating the right AI solutions — how to identify, assess, and validate tools that meet your needs while offloading technical complexity.
- The value of compliance-ready AI providers — the benefits of partners who maintain compliance throughout product development, delivering built-in and ongoing compliance.
- A path to compliant, ethical AI — how to extract meaningful insights from your data while staying aligned with evolving regulations.
Build on the Principles of Cloud Compliance for Responsible AI
With the introduction of cloud software in the early 2000s, life sciences organizations recognized the need for industry-specific cloud solutions; however, horizontal cross-industry cloud solutions didn’t adequately address the industry's regulatory needs. Thus emerged the field of vertical software-as-a-service (SaaS), which spurred a new market focused on cloud software tailored for the life sciences industry.
Cloud compliance provides a comprehensive framework for deploying and managing cloud software throughout its operational lifecycle, including risk-based release management practices. It enables organizations to add and update applications while adhering to regulatory requirements—the same principles that anchor sound 21 CFR Part 11 compliance as you extend governance from cloud applications to AI.
Develop a Responsible AI Model for Proper AI Use
Many life sciences organizations are already implementing AI tools, so the need for a responsible AI model is urgent. But developing that model poses unique challenges. As AI technology is rapidly evolving, compliance and regulatory requirements are struggling to keep pace.
To fill this gap, life sciences organizations need compliance best practices that evolve with AI tools and platforms. A clear approach to AI governance and compliance gives you that structure—defining how AI is evaluated, deployed, and monitored so responsible use is the default, not an afterthought.
Source and Validate AI Solutions that Meet Your Needs
It can be difficult to identify and assess the right tools, but partnering with AI providers and services companies enable your organization to offload the technical complexities, explore opportunities for automation, and ensure initial and ongoing compliance. A risk-based Computer Software Assurance (CSA) approach helps you focus validation effort where patient safety and data integrity risk is highest, rather than over-testing low-risk functionality.
Third-party experts are knowledgeable in AI and life sciences regulations to help you get the most out of new technologies. An AI provider that maintains compliance throughout product development offers several key benefits for life sciences organizations, including built-in and on-going compliance. Because AI introduces external models and data flows, pairing that diligence with disciplined third-party risk management ensures your vendors meet the same standards you hold yourself to.
Get a Compliant AI Solution for Your Life Sciences Organization
As you adopt AI to extract meaningful insights from your data, prioritizing responsible AI is essential to ensure the technology is implemented and used effectively, ethically, and in compliance with evolving regulations. Trustworthy insights depend on trustworthy inputs, which is why strong data integrity practices underpin everything a responsible AI program produces.
With the right solution to guide the way, your life sciences organization can successfully implement AI, navigate the complexities, and mitigate risks.
Why this matters — USDM's point of view: In regulated life sciences, responsible AI isn't a separate initiative bolted on after the fact—it's an extension of the cloud-compliance discipline organizations already trust. The fastest, safest path to value is choosing AI solutions and partners that build compliance in from the start, validate against real risk, and stay current as both the technology and the regulations evolve. Get the foundation right and AI becomes a reliable engine for high-quality insight rather than a source of audit exposure.
FAQ: Responsible AI for Life Sciences
What is responsible AI in a life sciences context?
It's the practice of implementing and using AI—including generative AI—effectively, ethically, and in compliance with evolving regulations. For life sciences organizations, that means building AI adoption on the same compliance principles that govern cloud software, so the technology delivers high-quality insights without creating regulatory risk.
How does cloud compliance relate to adopting AI?
Cloud compliance provides a comprehensive framework for deploying and managing software throughout its operational lifecycle, including risk-based release management. Those same principles—risk-based controls, lifecycle management, and adherence to regulatory requirements—form the foundation for adopting AI responsibly.
Why do life sciences organizations need a responsible AI model now?
Many organizations are already implementing AI tools, so the need is urgent. Because AI technology is evolving rapidly, compliance and regulatory requirements struggle to keep pace—creating a gap that organizations must close with compliance best practices that evolve alongside the tools and platforms they use.
What are the benefits of working with a compliance-ready AI provider?
Partnering with AI providers and services companies lets your organization offload technical complexity, explore automation opportunities, and ensure initial and ongoing compliance. A provider that maintains compliance throughout product development delivers built-in and ongoing compliance, backed by experts who understand both AI and life sciences regulations.
How do I source and validate the right AI solution?
Identifying and assessing the right tools is difficult on your own. Partnering with knowledgeable third-party experts helps you offload complexity and validate solutions against your actual needs and risk profile, ensuring the tools you adopt are both fit-for-purpose and compliant from day one.
Download the White Paper
Get the full guide to see how a purpose-built, compliance-first framework helps your organization adopt AI responsibly and mitigate risk. To learn more about this joint offering, contact USDM today!
Contributors to this white paper:
Richard Graves, Co-Founder and CCO, Sorcero
Caitlin La Honta, Product Marketing Leader, Sorcero
John Petrakis, Chief AI Officer, USDM Life Sciences
David Blewitt, VP of Cloud Compliance, USDM Life Sciences
Lisa Om, VP of Marketing and Communications, USDM Life Sciences
Rathina Govindaswamy, VP of Digital Cloud and AI, USDM Life Sciences