AI For Pharma Growth

Hosted by Dr Andree Bates

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Jun 2026

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AI For Pharma Growth is the podcast from pioneering Artificial Intelligence entrepreneur Dr. Andree Bates created to help Pharma, Biotech and other Healthcare companies understand how the use of AI-based technologies can easily save them time and grow their brands and company results. This show blends deep experience in the sector with demystifying AI for biopharma execs from biotech start-ups right through to big pharma. In this podcast, Dr Andree will teach you the tried and true secrets to building results in a pharma company using AI and alert you to some fascinating new tools and applications to benefit you and your company. As the author of many peer-reviewed journals in pharma AI, and having addressed over 500 industry conferences across the globe, Dr Andree Bates uses her obsession with all things AI, futuretech, healthcare and pharma to help you to navigate through the, sometimes confusing, but magical world of AI powered tools to achieve real-world results. This podcast features many experts who have developed powerful AI-powered tools that are the secret behind some time-saving and supercharged revenue-generating business results. Those who share their stories and expertise show how AI can be applied to Discovery, R&D, clinical trials, market access, medical affairs, regulatory, market research, business insights, sales, marketing, including digital marketing, and so much more.

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June 16, 2026Episode 22229 min

Why Most Pharma AI Will Fail Without This One Thing

Most pharma companies are racing to apply AI across drug discovery, development and commercialisation, but many of those efforts will fail for one simple reason: the data underneath is not good enough. In this episode, Dr Andree Bates speaks with Lisa Downey, CEO of DrugBank, about why trusted, structured biomedical intelligence is the foundation pharma AI cannot succeed without.Lisa explains how DrugBank has spent 20 years building and continuously curating a biomedical knowledge layer across drugs, targets, diseases and trials. With more than 156 million structured data points and over 60,000 academic citations, DrugBank is not just another dataset. It is a continuously maintained reference system designed so AI can reason over biomedical knowledge with traceability and trust.The conversation explores why most pharma AI projects fall short. Lisa argues the blocker is rarely the model. Instead, teams hit the wall because internal data lakes are not harmonised, licensed third-party data may not be AI-ready, and public data sources are incomplete or not maintained for enterprise use. Brilliant ML teams then spend most of their time cleaning and reconciling data instead of creating real scientific or commercial value.Lisa also breaks down what pharma buyers should test before trusting any AI vendor: interoperability, harmonisation, evidence lineage and continuous validation. She explains why human pharmaceutical expertise still matters, introducing DrugBank’s “human over the loop” approach, where experts set scientific boundaries, validation criteria and judgement so AI can scale inside trusted guardrails.Topics CoveredWhy most pharma AI projects fail before they scaleData quality as the foundation of trustworthy AIDrugBank’s 20 years of curated biomedical intelligenceInternal data lakes, third-party data and public data limitationsWhy hallucinations often start upstream of the modelHow to evaluate data quality: interoperability, harmonisation, lineage and validationHuman over the loop vs human in the loopWhy defensible AI needs traceable sourced factsThe difference between confident AI and grounded AIWhy proprietary context matters more than raw dataEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.AI platforms and tools solve specific problems. Strategy makes sure you’re solving the right ones, in the right order. If you want help mapping priorities as you evaluate what to roll out next, send me a LinkedIn DM starting with ‘PRIORITIES’ and two lines: what’s already in flight, and the decision you’re trying to make next.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.Dr. Andree Bates LinkedIn | Facebook | X

June 9, 2026Episode 22128 min

E221: The Diagnostic Room: The AI Governance Timeline Moved. Your Governance Exposure Didn't

On 7 May 2026, the EU reached a provisional agreement to push back the hardest deadlines in the EU AI Act. Many leadership teams heard one message: “we’ve got more time”. In this solo episode, Dr Andree Bates explains why that exhale is dangerous. The timeline moved, but the governance exposure did not.Dr Andree breaks down what the delay does and does not change. The dates may shift, but the architecture of the AI Act remains intact: risk classification, documentation, oversight, robustness, logging, conformity assessment, and post market monitoring. These are not last minute checklist items. They are operational capabilities you have to build, test, and keep running.The real risk, she argues, is misreading “more time” as permission to wait. The hardest work is operational: finding every AI system across the enterprise, including vendor embedded AI inside platforms like CRM and workflow tools, distinguishing genuine AI from marketing labels, classifying systems properly, assigning ownership, and building processes that still hold when vendors update models or features under the hood.She also tackles a costly misconception for US based pharma: the EU AI Act is deliberately extraterritorial. Scope follows where outputs are used, not where the company is headquartered. If AI outputs touch EU employees, regulators, clinicians, or patients, you may be in scope, even if the system is built and operated in the US.Dr Andree’s bottom line: the companies that treat this runway as time to build will compound governance maturity and deploy faster with less risk. The ones that wait will hit 2027 under compression, with more shadow AI, more remediation, and less credibility when scrutiny arrives.Topics CoveredWhat moved in the EU AI Act timeline, and what did notWhy AI governance is an operating model, not a deadline projectThe real work: inventory, classification, ownership, documentationVendor embedded AI and shadow AI as hidden exposureHigh risk obligations and why you can’t assemble them lateExtraterritorial scope and why US pharma is still in scopeWhat to do with the runway: build maturity, not delayEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

June 2, 2026Episode 22023 min

E220: The Intelligence Gap: Why Pharma's Biggest Deals Are Being Lost Before They Even Know They're Competing

In pharma, the biggest deals are increasingly won or lost before a formal process even begins. In this episode, Dr Andree Bates interviews Andrey Doronichev, co-founder and CEO of Bioptic, about the “intelligence gap” in business development, licensing, and corporate strategy, and why many companies are losing opportunities before they even know they’re competing.Andrey shares how his background building products at Google, including launching the YouTube mobile app, shaped his obsession with making messy, unstructured information usable at speed. He argues that pharma intelligence suffers from a similar problem: critical signals exist across scientific, regulatory, and business sources globally, but traditional approaches rely on relationships, conferences, spreadsheets, and slow manual synthesis.A key theme is competitive asymmetry. Deal teams are under pressure to source external innovation while the signal landscape expands rapidly, including an increasing share of patents and assets emerging outside the US. Andrey describes a common pattern: teams work from partial databases and manually maintained lists, then discover a competitor has already secured a preferred position with an asset they never saw coming, often in markets where information is harder to access.Bioptic’s thesis is cadence. If the same landscape work that takes weeks via consultants or days internally can be done in minutes, the operating model changes. Instead of humans acting as data gatherers, they can spend time on the human work: judgement, relationship building, negotiation, and structuring deals. Andrey describes Bioptic as a “self evolving operating system” that can build new integrations and analyses on demand, closing the gap between questions and actionable intelligence.Topics CoveredWhy pharma’s biggest deals are lost before the process startsThe intelligence gap: relationships vs anticipatory signal captureGlobal complexity, China signals, and why databases lagCadence as competitive advantage in BD and strategyFrom spreadsheets to continuously updated intelligence“Operating system” thinking and building capabilities on demandTurning analysts from data gatherers into decision makersWhat changes for BD teams over the next five yearsEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

May 26, 2026Episode 21935 min

E219: Bridging the Data-Use Divide: How QuadraticMed’s Dr. Danielle Bower Bridges Medicine and Data Science to Unlock Real-World Evidence

Real world evidence (RWE) could transform drug development and clinical care, but most organisations still struggle to turn messy clinical data into decisions they can trust. In this episode, Dr Andree Bates speaks with Dr Danielle Bower, CEO of QuadraticMed, about bridging the “data use divide” between clinical expertise and data science, so real world data becomes usable evidence rather than noise.Danielle explains why real world data is both more valuable and more difficult than clinical trial data. It reflects broad, diverse patient populations over longer timelines, with richer signals across labs, medications, imaging, pathology, and increasingly digital sources like wearables. But it’s also incomplete, inconsistent, siloed, and collected through real clinical judgement rather than strict protocols.A core message is that tools don’t replace domain expertise. Danielle shares how data processing without medical context can silently change the meaning of clinical variables, producing flawed conclusions even when the analytics look “correct”. Trustworthy outcomes require the right clinical question, appropriate comparisons, careful handling of missingness, and validation against biological reality.They also unpack what’s real versus hype in healthcare AI. GenAI is already helping with documentation and summarisation, but the bigger value is using RWE at scale to personalise treatment, detect risk earlier, and improve care efficiency. The main constraint is rarely the model. It’s data quality, governance, and cross functional communication.Topics CoveredRWE vs clinical trial dataWhy real world data is messy but essentialDomain expertise and clinical validationData quality, missingness, and contradictionsThe real bottleneck: workflow + communicationWhat GenAI can and can’t do todayRegulation, privacy, and trustMeasuring success in pharma and healthcare systemsEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.Dr. Andree Bates LinkedIn | Facebook | X

May 19, 2026Episode 21831 min

E218: How astrophysics methods used to study dark matter are now being applied to model cancer biology

Some of the most powerful breakthroughs happen when methods built for one discipline get turned on another. In this episode, Dr Andree Bates interviews Dr Irina Babina, CEO of Concr, on how computational techniques originally developed in astrophysics are being applied to oncology, helping predict how individual cancer patients will respond to treatment.Irina shares her journey from genetics and targeted cancer therapy into building applied solutions, driven by a frustration many scientists recognise: good science doesn’t always reach patients fast enough. A pivotal patient experience reinforced her focus on personalised biology, because behind every dataset is a person, and oncology cannot be solved purely through averages.Concr’s approach is built around Bayesian computation and uncertainty-aware modelling. Instead of assuming clean, complete datasets, the system is designed to work with missingness and fragmentation, updating predictions as new evidence comes in. Irina explains how Concr connects mechanistic biological modelling and preclinical drug perturbation data to patient multi-omics, imaging, treatment response, and outcomes data from both clinical trials and real-world settings.A key application is Concr’s patient-level digital twin (“Farsight Twin”), which simulates an individual’s probability of response across therapies, estimates likely benefit, and helps stratify patients earlier in development. Irina shares a use case where Concr supported indication ranking from cell line data, then helped interpret phase 1 signal by estimating which patients benefited from the novel drug versus standard of care, enabling sharper inclusion and expansion planning.Looking ahead, Irina argues we’re moving toward personalised oncology where population-level protocols fade, and decision-making becomes confidence-based, adaptive, and informed by longitudinal monitoring as tumours evolve over time.Topics CoveredApplying astrophysics-inspired methods to cancer biologyBayesian computation and modelling uncertaintyIntegrating multi-omics, imaging, trials, and real-world evidenceTranslational modelling from preclinical to clinical outcomesPatient-level digital twins and therapy response simulationStratification, enrichment, and reducing early-stage uncertaintyPan-cancer modelling to improve rare cancer predictionThe future of personalised oncology and dynamic monitoringEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan. Details at eularis.com.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.Dr. Andree Bates LinkedIn | Facebook | X

May 12, 2026Episode 21747 min

E217: The Diagnostic Room: Pilot purgatory: why pharma AI stalls after the first wins

Pharma doesn’t have an AI experimentation problem. It has an AI execution, scaling, and ROI justification problem. In this solo episode, Dr Andree Bates names one of the most expensive failure patterns in the industry: pilot purgatory.A key theme is misdiagnosis. When AI stalls, organisations often blame platforms, data science capability, training, vendor selection, or “resistance to change”. Dr Andree argues these explanations are usually incomplete because they ignore the structural constraints that determine whether AI gets trusted, governed, adopted, and tied to real decisions at scale.She outlines the core blockers she sees repeatedly: governance ambiguity, unresolved decision rights between global and local teams, data ownership disputes, incentive misalignment across functions, and adoption friction caused by tools that were never designed around real workflows. Treating adoption as a comms issue or solving with yet another pilot simply keeps the constraint untouched.Finally, Dr Andree explains what breaking out of pilot purgatory actually takes: clear executive ownership of business outcomes (not just technical delivery), defined decision points where AI changes action, governance that accelerates scale rather than blocking it, cross functional stewardship models, and defensible value logic that survives board scrutiny. The organisations pulling ahead aren’t running the most pilots. They’re confronting what’s structurally broken early, then building a strategy and sequencing plan that makes scale inevitable.Topics CoveredWhat “pilot purgatory” is and why it’s so costlyThe tell tale signs: pilots, duplication, uneven adoption, decorative AIWhy more pilots can make the stall worseCommon misdiagnoses: tools, training, vendors, “resistance”The real blockers: governance, decision rights, data ownership, incentivesWhy adoption is a downstream symptom, not the core problemRebuilding defensible ROI logic and board ready financial modelsWhat “good” looks like when organisations break out of purgatoryWhy delay compounds scepticism and weakens transformation capacityEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step. About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how the use of AI-based technologies can save them time and grow their brands and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.If you want, I can also pull 3 “quote graphic” alternates that are shorter and sharper from this solo transcript (there are loads of killer lines in here).Dr. Andree Bates LinkedIn | Facebook | X

May 5, 2026Episode 21630 min

E216: When AI meets Cell Engineering

Cell therapies have huge potential, but cost, complexity, and centralised manufacturing have kept many of them confined to last-line use. In this episode, Dr Andree Bates speaks with Armon Sharei, Founder and CEO of Portal Biotechnologies, about what happens when AI meets cell engineering, and why point-of-care delivery could make personalised cell programming more practical, scalable, and safer.Armon explains Portal’s core idea: cells are programmable machines. If you can reliably deliver multiple cargoes into cells, you can instruct new behaviours. Portal’s method briefly “squishes” cells through precision pores to disrupt the membrane so external material can enter, opening the door to complex cell engineering without permanent genome edits.They explore where AI fits in: modelling cell behaviour. By combining perturbation experiments, rich readouts, and phenotypic screening, AI can help generate “virtual cell models” that suggest which RNA instructions to deliver to drive specific outcomes. The bottleneck is data at the right complexity, because many effects only appear when multiple pathways are changed at once.A key takeaway is the safety and flexibility of transient RNA reprogramming. Unlike irreversible genetic modification, RNA fades within days, reducing long-term risk and making earlier-line use more realistic. Armon also discusses how point-of-care workflows may be regulated differently, with the machine treated as a device and the cargo as the drug.Looking ahead, he paints a vision of infusion-centre cell programming: a compact system that takes blood, delivers tailored RNA instructions to immune cells, and returns them within hours, potentially bringing costs closer to mainstream biologics and expanding access.Topics CoveredWhy delivery is the unlock for programmable cell therapiesHow Portal’s “cell squishing” delivery worksUsing AI to model cells and generate functional programmesThe data bottleneck and why multi-perturbation datasets matterPhenotypic screening and lab-to-clinic feedback loopsTransient RNA reprogramming vs permanent genetic modificationRegulatory implications of point-of-care engineeringEconomics and scalability of point-of-care approachesNear-term opportunities in oncology and autoimmunityThe future vision for infusion-centre personalised therapiesEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.AI platforms and tools solve specific problems. Strategy makes sure you’re solving the right ones, in the right order. If you want help mapping priorities as you evaluate what to roll out next, send me a LinkedIn DM starting with ‘PRIORITIES’ and two lines: what’s already in flight, and the decision you’re trying to make next.Dr. Andree Bates LinkedIn | Facebook | X

April 28, 2026Episode 21535 min

E215: Location, Location, Innovation: AI Site Twins and the New Era of Site Selection

Clinical trial site selection is one of the biggest hidden bottlenecks in drug development, and it’s still often driven by legacy relationships, spreadsheets, and habit. In this episode, Dr Andree Bates interviews Simon Arkell, founder of Ryght, Inc, about “AI Site Twins” and why the next era of site selection shifts from institutional memory to predictive, real-time analytics.Simon explains why the current model produces terrible outcomes at scale: too many activated sites under-enrol, competition at sites is poorly understood, and sponsors often don’t see the failure until timelines have already slipped. He argues this is primarily a site selection problem, because “the easy button” of re-using familiar sites reduces data-driven decision making, even as trials get more complex and patient competition intensifies.Ryght’s approach is to build AI-powered digital replicas of research sites, creating a unique identifier and a dynamic “twin” profile that continuously improves as new data arrives. Simon walks through how protocols can be matched to sites across countries, then enriched using harmonised public data, competitive trial context, and automated outreach that dramatically increases engagement. He also describes how different AI agents help fill missing information, find the right contacts, and capture context across email, portals, and voice interactions to improve future matching.The upside is massive: faster feasibility, better site choices, shorter time-to-activation, earlier first-patient-in, and ultimately faster time-to-market. Simon links these operational gains to commercial reality: every month saved can mean earlier revenue, longer effective patent runway, and more lives impacted by getting therapies to patients sooner.Topics CoveredWhy site selection is still a major bottleneck in clinical trialsThe true cost of underperforming sites and enrolment failureWhat an AI Site Twin is and how it differs from legacy databasesGlobal protocol-to-site matching and competitive trial contextData harmonisation from messy public sourcesAgent workflows: enrichment, outreach, contact finding, and context captureEngagement rates and accelerating feasibility timelinesEnrolment curve modelling and predicting site performanceSecurity, HIPAA/GDPR compliance, and sponsor data integrationTime-to-activation, first-patient-in, and time-to-last-patient-in KPIsWhy “execution speed” and flywheels create a moat in AI applicationsEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

April 21, 2026Episode 21438 min

E214: Beyond Copilot

For many life sciences teams, the first wave of AI has looked like copilots: smart search, quick answers, and help on demand. Useful, but passive. In this episode, Dr Andree Bates is joined by Parth Khanna, CEO and co-founder of ACTO, to explore what comes next: moving beyond copilots into role-based AI agents that proactively close knowledge gaps, improve field readiness, and operate safely inside regulated environments.Parth shares his path into life sciences and tech, including founding an early NLP company in 2012 and then building ACTO after speaking with over 100 life science companies about field force effectiveness. Today, ACTO supports tens of thousands of professionals and hundreds of brand launches, and Parth argues the industry is now entering the “agentic era” where the real differentiator is not just model access, but how organisations build context, control, and change management around AI.A key theme is why generic AI tools often fail inside enterprises. Parth outlines four requirements for agent success: context (role and job-specific personalisation), connection (stitching data sources and agent-to-agent workflows), control (testing, monitoring, observability), and change management (reducing fear and driving adoption). Without these, he says, many copilots and assistants end up underused, with people quietly reverting to old workflows.Parth then introduces ACTO’s concept of role-based “super agents”, designed around a real job description (for example an MSL). Rather than a disconnected swarm of task bots, a “queen bee” orchestrator agent delegates to worker agents, checks outputs against compliance guardrails, and can be assessed with exams to quantify risk before deployment. This approach, he argues, makes AI both more powerful and safer for regulated field teams.Finally, the conversation looks ahead. Parth believes the future of work depends on pairing AI capability with distinctly human strengths: strategy, judgement, and human connection. The winners won’t be those who automate the most tasks, but those who redesign roles so humans and agents amplify each other.Topics CoveredWhy copilots are useful but fundamentally passiveThe shift from AI that responds to AI that actsWhy generic tools fail: context, connection, control, change managementAdoption reality: why many AI assistants go unusedQuantifying risk and moving from black box to observable AIRole-based super agents and the “queen bee” orchestrator modelTesting agents with exams before field deploymentGuardrails, compliance, and agent-to-agent quality checksHuman skills AI can’t replace: strategy, judgement, connectionThe future of MSL and field excellence in an agentic eraEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.

April 14, 2026Episode 21327 min

E213: The Diagnostic Room: We have AI initiatives, but do we have a strategy? The quickest self-test

Many pharma and life science organisations have been investing in AI for years: pilots across commercial, medical, regulatory, and R&D, innovation labs, steering committees, vendor spend, and genuine effort from smart teams. And yet the same story keeps showing up in boardrooms: ROI is unclear, adoption is patchy, and leaders struggle to explain how all the AI activity connects to strategic goals.In this solo episode, Dr Andree Bates steps into “The Diagnostic Room” to explain why this happens, and why it’s usually not a technology, talent, or speed issue. It’s a diagnosis issue: organisations often haven’t identified what is actually constraining value, so they end up executing hard on the wrong problem.Dr Andree shares a real example from a mid-sized pharma company that believed its AI programme was failing due to lack of velocity. On the surface, it was a reasonable hypothesis. But a focused diagnostic revealed three hidden structural blockers: unclear decision rights for scaling pilots into production, fragmented data ownership preventing access to the best datasets, and incentive misalignment where the people expected to adopt AI tools were not rewarded for the behaviours those tools required.She then clarifies what a diagnostic is and is not. A diagnostic is not a strategy, roadmap, vendor shortlist, financial model, or implementation plan. Instead, it provides evidence-based clarity: what’s broken, how you compare to peers, what’s at stake, and what questions have been opened that cannot responsibly be answered in ten days. That clarity creates a shared language for leadership, replacing vague frustration with a precise problem statement.The organisations pulling ahead are not simply those with the biggest budgets, but those willing to find what’s actually broken before trying to fix it.Topics CoveredWhy AI initiatives can grow without creating measurable ROIThe gap between pilots and a true AI strategyMisdiagnosis: executing brilliantly on the wrong problemWhat a diagnostic sprint is (and what it is not)Three hidden blockersWhy working groups can’t fix structural AI constraintsWhat a full strategic AI blueprint includesWhy many AI business cases are untested projectionsHow to improve board confidence with evidence, governance, and measurementWhy diagnostics create speed by creating shared clarityEularis helps pharma and biotech leaders turn AI activity into board-defensible strategy and measurable commercial outcomes.If your organisation has plenty of AI in motion but very little that moves the commercial needle in a way the board can see, start with our 10-Day AI Diagnostic Sprint. It’s a focused diagnostic that surfaces what’s actually broken and what’s blocking results, before you invest in a larger strategy effort.The Sprint diagnoses the problem. The AI Strategic Blueprint that follows is where we build the board-defensible strategy and plan.Details at eularis.com.About the PodcastAI For Pharma Growth is the podcast from pioneering Pharma Artificial Intelligence entrepreneur Dr Andree Bates, created to help pharma, biotech and healthcare organisations understand how AI-based technologies can save time, grow brands, and improve company results.This show blends deep sector experience with practical conversations that demystify AI for biopharma leaders, from start-up biotech right through to Big Pharma. Each episode features experts building AI-powered tools that are driving real-world results across discovery, R&D, clinical trials, medical affairs, market access, regulatory, insights, sales, marketing, and more.If this episode described your situation, send me a LinkedIn DM starting with ‘SENSECHECK’ and two things: the question you’re trying to answer internally, and what’s currently in flight. I’ll reply with what I’d need to see to turn that activity into a defensible plan, and the next step.Dr. Andree Bates LinkedIn | Facebook | X