Technology

By correlating behavior data with performance outcomes, it becomes possible to predict what actually drives results.

Ankit Jain, CEO, Co-Founder, Infinitus touches on the approach to human oversight in an effort to build trust in autonomous patient access workflows by keeping humans and AI in a continuous feedback loop.

Ankit Jain, CEO, Co-Founder, Infinitus, discusses how AI-native patient access infrastructure appears to be less about replacing care teams and more about eliminating the friction between diagnosis and therapy initiation.

In the final part of his conversation with Pharmaceutical Executive, Aravo CCO Dave Rusher discusses the various regulatory updates around the world in the pharma and AI space.

Faruk Capan provides insights into the future of proprietary AI platforms.

New technologies are impacting the speed-to-therapy within hub services.

Dave Rusher, CCO at Aravo, explains the relationship between large, publicly available LLMs and how private LLMs might benefit the pharma industry.

Aravo CCO Dave Rusher discusses the risk of third-party AI usage at pharma companies.

How organizations can gain an edge in the enterprise transformation to unified analytics that's accelerating across pharma.

Conversational AI is pushing engagers to prioritize clear, explainable guidance as patients and clinicians delegate understanding to chatbots.

Large language models and natural language processing are reshaping drug safety surveillance by enabling automated adverse event detection, large-scale analysis of regulatory labeling data, and faster, citation-grounded safety assessments while maintaining human oversight and regulatory compliance.

As AI rapidly reshapes drug development and clinical operations, industry leaders say transparency, governance, and strong data foundations will determine whether the technology accelerates innovation or stalls under regulatory and operational pressure.

The gap between AI’s abilities and how people use could be about capability, but it’s also about confidence, belief and mindset.

As the AI-first era matures, life sciences leaders must pivot from narrow, task-specific models toward integrated, interpretable frameworks that transform biological complexity into a sustainable competitive advantage.

As the pharma industry continues to experiment with AI implantation, certain areas are showing more promise than others.

Most medical digital pilots are designed for success in controlled conditions.

As therapeutic complexity increases, life sciences companies should cultivate open mindsets toward innovative data sources beyond traditional claims and electronic medical record data.

What’s missing from many care strategies today is the actual voice of the patient.

The collaboration will employ Iambi’s AI drug discovery technology to advance several small molecule programs in oncology, gastrointestinal, and inflammatory diseases.

By giving small and mid-size biotechs access to real-world data and advanced analytics once reserved for large pharma, AI platforms are leveling the playing field by enabling lean teams to de-risk clinical strategy, strengthen fundraising narratives, and make faster, more confident decisions across the development lifecycle.

Dave Carey, CEO, Preceptis Medical and Michael Monovoukas, CEO, co-founder, AcuityMD note the importance of shifting ear tube procedures into the office, reducing anesthesia risk, and how AI-driven data and adaptive commercial strategies are becoming critical to scaling new medtech innovations.

Poor visualization techniques can oversimplify reality and make data less potent.

Anders Romare, Advisory Board Member, causaLens, and former Novo Nordisk CDIO, outlines why artificial intelligence represents a structural turning point for the pharmaceutical industry.

The AI dilemma facing biopharma—and what’s at risk.

Pharmaceutical manufacturers must address the question of how exactly does value get created and destroyed inside these organizations and how will AI fundamentally shift that equation?