Technology

Companion diagnostics are reshaping precision oncology, but clinical adoption continues to lag behind scientific progress due to regulatory, operational and reimbursement barriers.

The agentic model is emerging as a strategic tool to compress analysis timelines, coordinate cross-functional teams and surface competitive intelligence in real time.

Reliable, domain-specific AI models grounded in validated clinical evidence are emerging as essential to safely scaling generative AI across healthcare applications.

In Part 2 of our podcast video episode with ZS CEO Pratap Khedkar, he breaks down pharma's need to move beyond AI pilots to scalable impact—and how companies can "go from informing to solving" while navigating trust, regulation, and a rapidly shifting patient dynamic.

Boring AI operates quietly in the background, embedded deep within hospital EPR workflows, capturing structured, multimodal clinical data in real time at the point of care.

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

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

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.

Angela Schwab, founder and CEO of Trialynx, discusses the importance of designing trials around patients and how doing so doesn’t have to come at the cost of generating good data.

In the third part of her conversation with PharmExec, Trialynx founder and CEO Angela Schwab discusses the causes and solutions for high failure rates in clinical trials.