ACTO CEO Parth Khanna: AI Trust in Pharma Comes Down to 'Compliant Plus Capable'

Over recent years, the pharmaceutical industry has generally embraced artificial intelligence, with various companies implementing the technology across multiple sectors. Now, the central question is where AI is having an actual impact. In a recent interview with Pharmaceutical Executive, ACTO (搜索)搜索该词条 co-founder and CEO Parth Khanna elaborated on how AI is reshaping field teams and what it takes to build trust in these systems.

Khanna previously wrote a piece for Pharmaceutical Executive in March of this year, arguing that digital health solutions allow companies to both gather larger amounts of data and derive actionable insights from that data. In the months since, he says, the conversation has evolved toward a more fundamental question: what makes AI trustworthy in a regulated, compliance-heavy environment?

The Trust Equation: Compliant Plus Capable

Khanna identifies trust as the single most important factor in any AI rollout. "The most important factor in any AI rollout is the trust the program can generate," he said. Drawing on work with customers and a series of executive roundtables, he distills that trust into a simple formulation: "trust equals compliant plus capable."

He illustrates the failure modes of each component in isolation. A capable but non-compliant tool — such as ChatGPT in its bare form, "where it sometimes goes off in unintended directions" — will not be fully trusted. Conversely, a highly compliant but incapable system — "the AI assistant that pops up on a website and responds to every question with 'Sorry, I can't answer that'" — will eventually be dismissed as a waste of time. "Trust disappears in both cases," Khanna said. "Being compliant and being capable are both essential."

The key insight from ACTO (搜索)搜索该词条's research, Khanna explains, is that these two qualities are not in tension but can be built simultaneously through context. "The more context an AI system has about the role and responsibilities of the human it's designed to support, the more capable and compliant it can be simultaneously," he said.

He uses the medical science liaison (MSL) as a concrete example. "An AI agent that understands what an MSL does, what a scientific exchange looks like, what the parameters of that role are, and the specific ways it should and shouldn't support that person — that system will be both more capable and more compliant than one built without that context. The role knowledge is what makes the difference."

How AI Is Changing the Field Rep

Khanna frames the current moment as "an exciting time to be enabling and supporting life sciences organizations and their frontline teams with AI." He recounts a recent conversation with a chief commercial officer whose company is bringing "a very exciting new treatment-resistant hypertension (搜索)搜索该疾病 drug to market," focused on how to give frontline teams "every possible competitive advantage."

Addressing the prevailing debate over whether a sales rep is still needed in a world where healthcare professionals (HCPs) can access information through tools like OpenEvidence or OpenAI, Khanna argues that reps add the most value when they help physicians apply clinical data and evidence to their own practice. "HCPs can get answers faster than ever — but what they're still looking for is a knowledgeable partner who can help them work through the implications of that information in the context of their patients," he said.

AI can support this across the workflow, from pre-call planning and answering critical product questions to coaching support and helping reps act on development feedback from managers. Khanna describes this through a framework of building "both human intelligence and empathetic agents simultaneously."

Human intelligence, he explains, comes through AI-powered adaptive learning — "ensuring reps get trained faster and are field-ready sooner" — and through AI-based role-play practice, where reps rehearse in front of an AI avatar before speaking to a real customer. "They get more repetitions in, and they can land the message with greater confidence and impact."

Empathetic agents, by contrast, operate "at the point of need" — pre-call planning, HCP targeting, and surfacing complex product information in real time. "Human intelligence working alongside empathetic agents is, in our view, the winning formula for field sales teams today," Khanna said.

Compliance and Governance: From Black Box to Glass Box

On the compliance front, Khanna outlines a multi-layered approach. The first and most important step is "context engineering" — building and designing agents correctly from the start so they understand the standard operating procedures and guardrails within which they must operate.

The second element is building role-based agent systems. "When agents are designed around a specific role, they can inherit the compliance protocols and guardrails that correspond to that role," he said. For a sales rep, for instance, many of the compliance requirements already known from the human world "can be built directly into the agent." Khanna calls placing roles at the center of the design process "an essential architectural principle."

Once agents are designed, the next critical step is observability and testing before deployment. Rather than deploying agents into the field and hoping they respond correctly, Khanna advocates examining and certifying agents in a test environment — "verifying that they respond correctly to a defined set of questions and scenarios." He draws a parallel to field team onboarding: "we make sure people are certified and pass a knowledge assessment before they stand in front of a customer. We should hold our agents to the same standard."

Finally, Khanna emphasizes ongoing observability after launch. "The goal is to move agentic systems from a black box to a glass box," he said — continuously monitoring agent responses and re-administering the same pre-launch assessments at regular intervals "to catch any drift before an agent starts saying or doing something it shouldn't."

The Future of the Field Rep

Looking ahead, Khanna predicts a fundamental evolution in the sales rep role and how reps create value. "There will continue to be a very important role for humans in the field," he said. "But the job description of a sales rep is going to change in a meaningful way."

Tasks currently done manually or in a human-only way will increasingly be augmented by compliant, empathetic agents, freeing reps "to go further and deeper into areas of work they can't fully access today." Khanna also envisions a world where the sales rep and MSL roles become hybridized — "though the regulatory environment will need to catch up to that possibility."

The fundamental driver, he argues, is that "agents that perform at the periphery of human cognition allow humans to do more" — whether taking on more complex clinical questions with healthcare professionals, spending more time building genuine relationships, or developing a deeper understanding of how a physician runs their practice. "There are likely ways that role will evolve that we haven't even imagined yet," Khanna said.

"What we can all agree on is that the future sales rep will be one who creates more value for physicians — capable of doing more, both cognitively with the help of agents, and with the time that gets freed up when agents handle the work that doesn't require human judgment."