A New Chapter in Clinical Trials
Sharon Kim, founder and CEO of MPilotAI, has long believed that the future of drug development depends not only on scientific rigor but on how effectively we translate great ideas into action. With over a decade of experience at the intersection of healthcare innovation and artificial intelligence, Sharon is leading a transformation in one of the industry’s most complex and outdated areas: clinical trial design and planning.
At a time when pharmaceutical innovation is accelerating, the systems that support clinical research haven’t kept pace. Timelines are long, documentation is fragmented, and smaller teams are often left behind, unable to access the same resources as larger players. For Sharon, this imbalance isn’t just inefficient, it’s unjust.
The premise behind MPilot is simple but powerful: to change the way new treatments move from concept to clinic. By automating and simplifying the most burdensome parts of the clinical trial process, Sharon and her team aim to help researchers focus less on paperwork and more on what matters, bringing life-saving therapies to patients faster and more equitably.
What MPilot Actually Does (And Why It Matters)
Clinical trials are full of critical thinking, but the systems that support them often aren’t. Teams are expected to manage complex trial designs, navigate evolving regulatory requirements, and produce highly structured documentation, usually with tools that weren’t built for the job. The result? Time lost, details missed, and opportunities delayed.
MPilot was built to change that. The platform serves as a one-stop shop for clinical trial teams, bringing structure, automation, and clarity to every phase of the process—from study planning to final documentation.
At the front end, the Study Designer helps teams define key trial elements with precision: objectives, endpoints, eligibility criteria, dosing strategies, and more. Instead of working from scratch or copying from old templates, users are guided through a structured framework that reduces inconsistencies and sets the stage for a clean, audit-ready output.
On the back end, the Document Generator transforms that input into full-length clinical documents, protocols, amendments, investigator brochures, and study reports, using a library of over 200 pre-engineered prompt templates. These templates reflect real regulatory language and industry norms, making it faster to generate high-quality content without sacrificing accuracy or compliance.
Everything operates within a secure, closed environment and integrates directly with Microsoft Word, so users can work where they’re comfortable while eliminating formatting chaos, version control issues, and manual rework.
“We didn’t want to build something that required teams to completely change how they work,” Sharon explains. “The goal was to meet researchers where they are, and make their jobs easier, not harder.”
MPilot makes it easier for teams to stay focused, aligned, and responsive—no matter the complexity of the study or the pace of the trial.
Cutting Through the AI Noise
In today’s clinical tech landscape, nearly every solution claims to use artificial intelligence. But when everything is labeled “AI,” it becomes harder for teams to distinguish between real innovation and repackaged automation.
For Sharon, this isn’t a matter of semantics, it’s a matter of safety and integrity. In clinical trials, the technology supporting drug development must be accurate, transparent, and aligned with how clinical teams actually work. Misrepresenting what a tool can do doesn’t just waste time, it creates risk.
That’s why Sharon urges decision-makers to ask harder questions: What does the AI actually do? How is it being used in the product? Is it adapting to real-world input, or simply automating predefined tasks? And most importantly, does the solution fit into the reality of clinical workflows, or does it rely on teams bending to fit the tool?
Cutting through the noise means being skeptical of promises and clear about outcomes. Sharon’s stance is simple: if AI is going to support healthcare, it needs to be understandable, grounded in real use cases, and honest about what it can and can’t do.
Ethics Isn’t Optional, It’s Fundamental
In an age where AI is one of the most powerful tools shaping human decision-making, ethical oversight isn’t optional, it’s essential. The same technologies that can accelerate research and improve outcomes also carry the risk of reinforcing power imbalances: withholding information, centralizing control, or distorting results under the guise of automation.
Sharon believes that responsible AI must be built on three pillars: transparency, accountability, and access. From the start, MPilot has been designed to reflect those values—not just in its outputs, but in how the system operates behind the scenes.
The platform doesn’t obscure how it works or replace clinical expertise with opaque logic. Instead, it provides clearly defined, auditable processes that allow human professionals to remain firmly in control. AI is used to reduce repetitive work and enhance document quality, not to make decisions in a vacuum.
This distinction is especially important in clinical research, where trust is everything. Sharon’s approach is rooted in the belief that AI should amplify human insight, not override it.
“AI should never replace clinical judgment,” Sharon says. “It should support it—helping researchers move faster and with more confidence, not making decisions in their place.”
She believes that every researcher, regardless of company size or geography, should have access to tools that help them work smarter, not harder.
In a field where time and precision can mean the difference between access and delay, MPilot’s commitment is clear: build tools that empower, not exclude.
The Future: Smarter, Faster, More Inclusive Drug Development
As AI continues to evolve, so does its potential to reshape the way clinical research is done. For Sharon, the opportunity lies in building tools that serve a broader range of users, making it easier for more teams to contribute to the future of medicine.
MPilot is designed to support the full spectrum of research organizations, from enterprise R&D teams to academic institutions and emerging biotech startups. The platform’s focus on structured trial design, automation, and real-time guidance helps reduce operational complexity, regardless of team size or budget.
By removing friction from documentation and streamlining the early phases of trial development, MPilot empowers users to stay focused on their scientific goals, not the formatting, cross-referencing, or version control that so often slows progress.
Sharon’s vision is one where innovation is supported at every level, where AI enables more researchers to move ideas into action, and more treatments to move toward the people who need them.
Shared Responsibility, Shared Opportunity
Sharon’s vision for the future of clinical research isn’t built on speed alone. It’s built on a belief that efficiency and ethics can, and must, coexist. That the systems supporting drug development should be just as thoughtful, transparent, and forward-looking as the science they serve.
MPilot is part of that shift but it’s only one piece. The bigger opportunity lies in how we, as an industry, choose to evolve: breaking down barriers to participation, designing technology that supports, not replaces, expertise, and building workflows that are not just faster, but fairer.
Sharon’s call is simple: let’s not just optimize the status quo. Let’s rethink it. Let’s challenge the idea that complexity is inevitable, or that innovation should only be accessible to a few. Let’s build tools, teams, and systems that reflect the future we want to create.
The path forward is smarter, faster, and more inclusive. But it won’t happen by accident, it will happen by design. To connect with Sharon Kim, follow her on LinkedIn.
