Life Sciences DNA Podcast

Hosted by Levine Media Group

Business Science

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Oct 2026

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About the show

The Life Sciences D’n’A podcast is hosted by AI and data analytics experts and pharma industry veterans Nagaraja Srivatsan and Amar Drawid. They explore the evolving use of AI and data science with innovators working to reshape all aspects of the biopharmaceutical industry from the way new therapeutics are discovered to how they are marketed.

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53 recent

October 23, 2026Episode 5644 min

Why Scaling AI Starts with Leadership, not Technology

Moving AI beyond a pilot requires more than choosing a model or building a tool. It requires leadership support, employee trust, and a clear connection to business results. On this episode of Life Sciences DNA, Marc Raman, chief data and AI officer at Alcon, sits down with Srivatsan Nagaraja to discuss the company’s experience putting AI to work across manufacturing, sales, marketing, and employee services. Raman shares what worked, what needed to change, and why a useful homegrown product can still be worth replacing. He discusses how to manage expectations, capture employees’ expertise, navigate shifting technology economics, and build a workforce prepared to keep learning as AI advances.

October 8, 2026Episode 5545 min

Putting Business Value at the Center of AI in Biopharma

Artificial intelligence may be moving quickly, but life sciences companies cannot afford to treat it as a race for the latest shiny tool. In this episode of Life Sciences DNA, Brinda Banerjee, CIO of Stemline Therapeutics, sits down with Srivatsan Nagaraja to discuss how an oncology-focused biopharma company can pursue AI with rigor, speed, and a clear connection to business and patient impact. Banerjee offers a practical framework for moving from enthusiasm to execution: start with the business problem, build trusted data and governance foundations, keep experts in the loop, and form agile, cross-functional teams that can test, learn, and scale what works.

September 24, 2026Episode 5452 min

Turning Data and AI Into Better Business Outcomes

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.

September 10, 2026Episode 5354 min

Measuring AI by Business Results in Life Sciences

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.

June 11, 2026Episode 5246 min

Lessons from Insmed’s Journey to an AI First Biotech

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.

May 14, 2026Episode 5053 min

Making AI Transformations that Stick

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.

April 9, 2026Episode 4846 min

Finding ROI from AI in the Mundane

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.

March 26, 2026Episode 4736 min

A Pragmatic Path to AI-Enabled Commercial Operations

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.

March 12, 2026Episode 4647 min

Reimagining Scientific Work in the Age of AI Agents

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

February 26, 2026Episode 4546 min

Orchestrating Scientists, Data, and AI to Discover New Drugs

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.