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Artificial intelligence is reshaping how biopharmaceutical companies discover, develop, commercialize, and support medicines. But realizing its potential requires far more than adopting the latest tools. Srivatsan Nagaraja speaks with Matt Lasmanis, chief digital officer at Jazz Pharmaceuticals, about building a digital, data, and AI strategy grounded in corporate ambition and measurable outcomes. Lasmanis offers a practical framework that begins with strategy, identifies the business outcomes that matter most, and establishes the metrics needed to demonstrate progress. He also discusses how companies can align people, technology, and partners to build enterprise capabilities that advance precision, efficiency, and innovation.

Artificial intelligence is creating new opportunities to improve clinical development, but successful adoption requires more than choosing the latest model or launching isolated pilots. Krishna Cheriath, vice president and head of digital and AI for biopharma services at Thermo Fisher Scientific, sits down with Srivatsan Nagaraja to discuss what it takes to translate AI’s promise into measurable business and patient impact, why companies should focus on a small number of strategic imperatives, and his practical approach for prioritizing high-value use cases.

Chris Colucci, vice president of information technology at Insmed, sits down with Nagaraja Srivatsan to discuss the company’s shift from AI experimentation to enterprise-scale adoption, using the patient as its North Star guiding decisions across the drug development value chain. He outlines the evolution of Insmed’s AI journey and explains how the company now evaluates opportunities through clear lenses of game-changing impact, productivity gains, and automation. Colucci also discusses what it takes to operationalize AI in an emerging biotech, the practical steps Insmed has taken to scale AI across the value chain, and how anchoring decisions to the goal of getting therapies to patients faster helps prioritize where AI can be most transformative.

Vikram Nair, chief information officer of Amneal Pharmaceuticals, joins Srivatsan Nagaraja to break down what it really takes to turn AI from boardroom buzz into real business impact. From early missteps and skeptical stakeholders to building smarter metrics, Nair shares lessons from the front lines of AI transformation—and introduces a practical control framework to help life sciences companies scale AI, manage risk, and evolve without losing control.

Dennis Salotti, executive director and head of clinical outsourcing and innovation at Jazz Pharmaceuticals, joins Srivatsan Nagaraja to talk about what AI really looks like in day-to-inside a drug company. He explains how large language models and agentic tools can streamline contracting, budgeting, and risk management—mundane but high-impact work that speeds studies and improves trial-site experience. Salotti shares how to design narrow, high‑ROI pilots, build AI fluency, avoid “AI slop,” and turn AI into a thinking partner rather than a shortcut, stacking small wins that remove grunt work, capture lessons learned, and elevate people from doers to critical thinkers.

Tris Pharma Chief Commercial Officer Manesh Naidu sits down with Nagaraja Srivatsan to discuss how the small but growing specialty pharma company is pursuing a deliberately incremental AI strategy, focusing on its biggest pain points rather than chasing grand, enterprise-wide transformations. He explains how the team is using off-the-shelf and vendor tools where possible, rigorously managing data and compliance risk, and letting quick wins in discrete use cases pave the way for broader change. Naidu discusses what practical AI adoption looks like for Tris, how the company is applying the technology to high-value commercial challenges, and how it is reinventing sales training through virtual physician simulations.

Shweta Maniar, global strategy and market leader for life sciences at Google Cloud, sits down with Nagaraja Srivatsan to unpack what it takes to turn AI pilots into durable, enterprise-wide impact. A former biotech executive who now helps biopharma leaders modernize their data and AI strategy, Shweta argues that success starts with fixing fragmented data foundations and reshaping culture—not just deploying the latest model. She explains why AI should be treated as a strategic upgrade to de-risk science rather than a narrow tool for squeezing efficiency, why the hardest problems are less about model performance and more about data and organizational behavior, and how emerging multi-agent systems could compress timelines from discovery to patient access. You can download The ROI of AI in Healthcare and Life Sciences report referenced in the discussion here: https://cloud.google.com/resources/content/roi-of-ai-healthcare-life-sciences

Scotch McClure had a bold plan for Maxwell Biosciences to map and mine the roughly 3 percent of peptides circulating in human plasma. The company has harnessed AI to move from a massive and messy universe of human peptides to a small-molecule candidate that could offer a potential alternative to antibiotics, antifungals, and some antivirals. McClure, CEO of Maxwell, sat down with Nagaraja Srivatsan to discuss why he thinks AI is becoming the central engine that makes modern drug development not just faster but possible at all, how he sees AI as essential to filtering out the noise in vast datasets, and why organizations will need to surrender more of the scientific process to AI while constraining it with a clear vision and guardrails.

Drew McCormick, head of data and analytics at Eversana, sits down with Nagaraja Srivatsan to trace the company’s AI journey from classic predictive modeling in its data and analytics business to an enterprise-wide strategy. He describes how Eversana is building on a strong data foundation to tackle challenges such as patient identification, while also rethinking workflows, governance, and talent to ensure AI delivers value in a highly regulated environment.

Scott Cenci, chief information and data officer for Acadia Pharmaceuticals, sits down with Nagaraja Srivatsan to discuss how generative and agentic AI are reshaping biopharma throughout the enterprise from R&D and clinical development to the commercial field. He discusses how it is changing the roles of people like medical writers into medical editors, why every knowledge worker will soon manage AI agents as part of their job; and the hard problems leaders face in prioritizing AI investments, avoiding experiment fatigue, governing enterprise data, and building a culture of continuous learning.​

Karthik Raman, co-founder and CEO of Persist AI, sits down with the Nagaraja Srivatsan to discuss how robotics, AI, and cloud tech are supercharging drug formulation to address a bottleneck in pharma R&D. He explains how robots outperform humans in consistency and scale, igniting a flywheel of faster prototyping, richer data, and AI-orchestrated workflows that will propel biopharma innovation amid rising drug complexity.

Gabi Tarcic, vice president of product for Evogene, sits down with Srivatsan Nagaraja about applying AI to small molecule drug discovery, the cultural and operational changes required for researchers to adopt these tools, and how AI-driven platforms can improve the efficiency of pharma R&D.

Anita Modi, CEO and founder of Peer AI, joins Srivatsan Nagaraja to discuss the transformative impact of agentic AI on document creation for pharmaceutical companies. She discusses the cultural challenges of integrating AI into a traditionally cautious industry, the need for change management, and why it’s critical to embed human judgment alongside machine intelligence.​

Ronel Veksler, co-founder and CEO of PromiseBio, sits down with Amar Drawid to discuss the company’s AI-enabled proteomics platform, and how post-translational modifications of proteins represent a new frontier for precision medicine in autoimmune diseases; and how AI is enabling deep profiling of the epiproteome for better disease subtyping, improved prediction of drug response, and more personalized therapeutic strategies.

Aaron Cohen, Head of Research Oncology, Clinical Data for Flatiron Health, sits down with Amar Drawid to discuss Flatiron’s use of large language models to extract and analyze unstructured data from electronic health records. Cohen discusses how AI‑extracted data can replicate human‑curated outcomes across multiple cancer types, paving the way for faster, richer insights to guide both clinical decision‑making and drug development.