The Future of Pharma Regulation: Building Trust Through Evidence in an AI-Driven Era

The pharmaceutical industry faces a crisis of confidence at precisely the moment when scientific capabilities have reached unprecedented heights. At the Indegene Digital Summit 2025, Dr. Andrew von Eschenbach, former FDA Commissioner and National Cancer Institute Director, joined Dr. David Shulkin,  former U.S. Secretary of Veterans Affairs, to examine how pharma regulations must evolve alongside accelerating data complexity, deteriorating public trust, and mounting pricing pressures.

The conversation revealed that the path forward demands not just technological adaptation, but a fundamental reorientation toward transparency, evidence discipline, and patient-centered value creation.

The acceleration of pharmaceutical data has transformed drug regulation into what is fundamentally a data management business. The volume, diversity, and complexity of pharmaceutical data have expanded exponentially, moving from basic family histories to comprehensive genetic profiles, from observational clinical notes to molecular mechanism mapping.

This shift places pharma regulatory intelligence at the center of competitive advantage, requiring companies to master not just data acquisition but rigorous aggregation and analysis before reaching actionable knowledge. For pharma leaders, this underscores that investment in data infrastructure is no longer a support function but a primary strategic capability that determines both regulatory success and commercial viability.

Public confidence in health agencies has eroded dramatically, creating situations where isolated data points substitute for systematic analysis. The discussion highlighted recent debates, from vaccine hesitancy to unsubstantiated causal claims linking common medications to adverse outcomes, as symptoms of evidence abandonment.

Restoring trust requires pharmaceutical companies to demonstrate that patients represent the end goal rather than the means to commercial success. This translates operationally into transparent communication of peer-reviewed evidence, educational engagement that acknowledges risk, and disciplined adherence to complete analytical pathways before drawing conclusions. The strategic implication extends beyond reputation management to market access, as regulatory agencies and payers increasingly demand evidence rigor as a precondition for approval and reimbursement.

The current drug pricing debate addresses symptoms rather than systemic dysfunction. The opacity of pharmaceutical pricing mechanisms is such that even board members of pharmaceutical companies find it difficult to trace the path from manufacturer price to patient cost. The fundamental challenge lies in the U.S. market's disproportionate underwriting of global biopharma research and development while other OECD nations decline to share development costs despite benefiting from innovation.

For pharma executives, this signals that traditional pricing models have reached their limit. The FDA's role should remain strictly confined to safety and efficacy determinations, independent of price considerations, while CMS and policy frameworks must address the economic dimension. Strategic positioning requires pharma companies to actively participate in redesigning reimbursement systems rather than defensively responding to price control threats.

There was recognition of a critical shift from traditional component pricing to value-based contracting for integrated solutions. The computer industry demonstrates that isolated components like microprocessors deliver no value until integrated into functional systems, a principle that applies equally to pharmaceutical treatments. Similarly, treating complex diseases like cancer and Alzheimer's will require complex interoperable integration of components rather than standalone pharmaceutical products.

This framework introduces profound questions about calculating value propositions, particularly for interventions like vaccines where societal benefit through herd immunity extends far beyond individual recipients. For commercial leaders, this demands development of outcomes-based payment models, investment in real-world evidence generation, and commercial strategies organized around patient solutions rather than product portfolios. AI tools offer potential mechanisms for quantifying these multidimensional value propositions, but only if pharma companies lead in defining the measurement frameworks.

The panel posited that effective FDA regulation of AI algorithms and large language models requires the agency to become expert and adept at AI processes through joint learning with industry rather than independent evolution. The FDA's decades of accumulated drug, biologic, and device approval data could be viewed as a Fort Knox of data, representing an ideal platform for AI transformation. This perspective suggests that effective pharma regulations in the AI era require collaborative development between industry and regulators.

Pharmaceutical companies possess deep expertise on their own products and technologies, making industry-FDA dialogue essential rather than adversarial. Strategic leaders should position their organizations as partners in developing FDA AI guidelines, contributing technical expertise while ensuring regulatory frameworks enable rather than obstruct innovation. The transparency of this collaborative regulatory process builds the trust foundation that both agencies and companies require.

Pharma leaders are rethinking a more nuanced position on direct-to-consumer pharmaceutical marketing that challenges both blanket prohibition and current practice. Unfortunately, drug advertisements positioned between consumer products often frame patients as customers rather than individuals seeking solutions. However, industry communication directly to physicians and patients can serve a valuable purpose when grounded in peer-reviewed evidence and focused on education about disease states and therapeutic options.

The recent shift by a leading pharmaceutical company toward advertising that emphasizes patient welfare without explicit product promotion represents a positive evolution. For commercial organizations, this signals a strategic pivot toward content that builds trust through education and awareness, particularly for underrecognized conditions, rather than purely transactional messaging. The regulatory environment under current FDA scrutiny of D2C practices reinforces that communication strategies must demonstrate patient-centricity not just in positioning but in substantive content and intent.

The conversation reinforced that pharma's transformation challenge transcends technology adoption, requiring organizational redesign around evidence discipline, transparent value demonstration, and patient-centered purpose. As pharmaceutical data management complexity accelerates and regulatory scrutiny intensifies, competitive advantage will flow to organizations that lead in building collaborative frameworks with regulators, pioneering value based contracting models and restoring public trust through rigorous evidence communication.