AI For Pharma Growth

Dr Andree Bates

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.

  1. Why Most Pharma AI Will Fail Without This One Thing

    22h ago

    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 Covered Why most pharma AI projects fail before they scale Data quality as the foundation of trustworthy AI DrugBank’s 20 years of curated biomedical intelligence Internal data lakes, third-party data and public data limitations Why hallucinations often start upstream of the model How to evaluate data quality: interoperability, harmonisation, lineage and validation Human over the loop vs human in the loop Why defensible AI needs traceable sourced facts The difference between confident AI and grounded AI Why proprietary context matters more than raw data Eularis 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 Podcast AI 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

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

    Jun 9

    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 Covered What moved in the EU AI Act timeline, and what did not Why AI governance is an operating model, not a deadline project The real work: inventory, classification, ownership, documentation Vendor embedded AI and shadow AI as hidden exposure High risk obligations and why you can’t assemble them late Extraterritorial scope and why US pharma is still in scope What to do with the runway: build maturity, not delay Eularis 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 Podcast AI 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.

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

    Jun 2

    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 Covered Why pharma’s biggest deals are lost before the process starts The intelligence gap: relationships vs anticipatory signal capture Global complexity, China signals, and why databases lag Cadence as competitive advantage in BD and strategy From spreadsheets to continuously updated intelligence “Operating system” thinking and building capabilities on demand Turning analysts from data gatherers into decision makers What changes for BD teams over the next five years Eularis 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 Podcast AI 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.

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

    May 26

    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 Covered RWE 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 Podcast AI 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

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

    May 19

    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 Covered Applying astrophysics-inspired methods to cancer biology Bayesian computation and modelling uncertainty Integrating multi-omics, imaging, trials, and real-world evidence Translational modelling from preclinical to clinical outcomes Patient-level digital twins and therapy response simulation Stratification, enrichment, and reducing early-stage uncertainty Pan-cancer modelling to improve rare cancer prediction The future of personalised oncology and dynamic monitoring Eularis 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 Podcast AI 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

    32 min
  6. E217: The Diagnostic Room: Pilot purgatory: why pharma AI stalls after the first wins

    May 12

    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 Covered What “pilot purgatory” is and why it’s so costly The tell tale signs: pilots, duplication, uneven adoption, decorative AI Why more pilots can make the stall worse Common misdiagnoses: tools, training, vendors, “resistance” The real blockers: governance, decision rights, data ownership, incentives Why adoption is a downstream symptom, not the core problem Rebuilding defensible ROI logic and board ready financial models What “good” looks like when organisations break out of purgatory Why delay compounds scepticism and weakens transformation capacity Eularis 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 Podcast AI 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

    47 min
  7. E216: When AI meets Cell Engineering

    May 5

    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 Covered Why 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 Podcast AI 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

    31 min
  8. E215: Location, Location, Innovation: AI Site Twins and the New Era of Site Selection

    Apr 28

    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 Covered Why site selection is still a major bottleneck in clinical trials The true cost of underperforming sites and enrolment failure What an AI Site Twin is and how it differs from legacy databases Global protocol-to-site matching and competitive trial context Data harmonisation from messy public sources Agent workflows: enrichment, outreach, contact finding, and context capture Engagement rates and accelerating feasibility timelines Enrolment curve modelling and predicting site performance Security, HIPAA/GDPR compliance, and sponsor data integration Time-to-activation, first-patient-in, and time-to-last-patient-in KPIs Why “execution speed” and flywheels create a moat in AI applications Eularis 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 Podcast AI 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.

    35 min

Ratings & Reviews

4
out of 5
9 Ratings

About

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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